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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Investigating Secondary Aerosol Processes in the Amazon through Molecular-level Characterization of Semi-Volatile Organics

In areas where biogenic emissions are oxidized in the presence of anthropogenic pollutants, it has become increasingly apparent that secondary organic aerosol (SOA) formation from biogenic volatile organic compounds (BVOCs) is substantially enhanced. The Amazon forest is the dominant source of BVOCs globally, and the forest is rapidly being converted to urban and agricultural uses. We participated in a collaborative field study located in the Amazon region around Manaus, Brazil, in 2014 (Green Ocean Amazon; GoAmazon). This study was designed to comprehensively examine how BVOC emissions (specifically, the most highly emitted non-methane hydrocarbon, isoprene, and lesser studied sesquiterpenes) and their interaction with anthropogenic pollution (i.e., nitrogen oxides, sulfur dioxide, and black carbon) alter the atmosphere’s oxidative capacity, influence secondary aerosol formation, atmospheric composition and, ultimately, affect the earth’s radiation balance and climate. We provide the first hourly, in-situ measurement of 30 sesquiterpenes and 4 diterpenes, roughly estimating that sesquiterpene oxidation contributes to 10-14% of ozone reactive loss by terpenes and at least 0.4–5% (median 1 %) of total submicron OA mass. However, this is likely a low-end estimate, as evidence for additional unaccounted sesquiterpenes and their oxidation products clearly exists. We also provide new perspectives on sulfate, NO x , and particle acidity influencing isoprene-derived SOA, comparing the central Amazon environment with Southeastern U.S.A. summer, representing clean to polluted conditions, respectively. We find that summed concentrations of isoprene-derived SOA tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m -3 reduction in sulfate corresponds with at least ~0.5 μg m -3 reduction in isoprene-derived SOA. We also find that SOA mass derived from isoprene oxidation in the presence of NO x is primarily comprised of aerosol sulfate bound with isoprene oxidation products (i.e. organosulfates), ~97% in the Amazon and ~55% in the Southeastern U.S. We infer under natural conditions in high isoprene emission regions, preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought as representative of anthropogenic influence. We further report the first field observations showing that particle acidity impacts the distribution of isoprene oxidation tracers in the gas and particle phases, providing physicochemical insight into isoprene SOA formation chemistry. Coupled with other co-located measurements by the DOE Atmospheric Radiation Measurement (ARM) team and collaborating PIs at our measurement site (called T3), on the G1 aircraft, and at additional field sites (T0, T1, T2) this data set has been used to understand emission, oxidation, and particle formation pathways at the molecular level, to elucidate how these pathways change when influenced by anthropogenic sources, and to evaluate their importance for the atmospheric budget of aerosols and the earth’s radiation balance on regional scales. Recommendations: Further constraint of the role of sesquiterpenes on ozone (O 3 ) reactivity and SOA formation is limited by the availability of authentic standards and synthesized compounds of sesquiterpenes and their oxidation products. Future research efforts should focus on making such standards available via custom synthesis to allow for accurate quantification and focused oxidation experiments that will fully elucidate the chemistry of these compounds in the atmosphere. Further, reductions in aerosol sulfate (via SO 2 emissions control) continues to be one of the most effective methods to reduce SOA formation from isoprene, but the concerted role of ammonia (NH 3 ) gas emissions from (agricultural) industry and other sources requires more investigation to better understand the role of aerosol acidity in SOA formation and potential controls. As GoAmazon particles can be more acidic compared to areas with greater anthropogenic NH 3 emissions, this promotes relatively greater organosulfate (OS) formation from isoprene even in the presence of NO x . Because OS and inorganic sulfate differ in water uptake properties, this implies preindustrial aerosol sulfate (albeit less abundant) may have been less reflective than current earth system models assume. Further research should investigate the radiative impacts of organic vs inorganic sulfate in aerosols to improve model representation. Finally, future work (currently underway) should include constraint of the contributions of monoterpene (C 10 H 16 ) BVOCs and biomass burning VOCs as precursors to SOA formation in the region as well as their impacts on radiative forcing in the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

RAVEN: Dynamic Event Tree Approach Level III Milestone

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

RAVEN. Dynamic Event Tree Approach Level III Milestone

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.

42 ENGINEERING↗
DOE OSTI2022

Simultaneous Optimization of Nuclear–Electronic Orbitals

Accurate modeling of important nuclear quantum effects, such as nuclear delocalization, zero-point energy, and tunneling, as well as non-Born-Oppenheimer effects, requires treatment of both nuclei and electrons quantum mechanically. The nuclear–electronic orbital (NEO) method provides an elegant framework to treat specified nuclei, typically protons, on the same level as the electrons. In conventional electronic structure theory, finding a converged ground state can be a computationally demanding task; converging NEO wavefunctions, due to their coupled electronic and nuclear nature, is even more demanding. Herein, we present an efficient simultaneous optimization method that uses the direct inversion in the iterative subspace method to simultaneously converge wavefunctions for both the electrons and quantum nuclei. In conclusion, benchmark studies show that the simultaneous optimization method can significantly reduce the computational cost compared to the conventional stepwise method for optimizing NEO wavefunctions for multicomponent systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Measurement of dijet cross-sections in pp collisions at 7 TeV centre-of-mass energy using the ATLAS detector

Double-differential dijet cross-sections measured in pp collisions at the LHC with a 7 TeV centre-of-mass energy are presented as functions of dijet mass and half the rapidity separation of the two highest-p T jets. These measurements are obtained using data corresponding to an integrated luminosity of 4.5 fb -1 , recorded by the ATLAS detector in 2011. The data are corrected for detector effects so that cross-sections are presented at the particle level. Cross-sections are measured up to 5TeV dijet mass using jets reconstructed with the anti- k t algorithm for values of the jet radius parameter of 0.4 and 0.6. The cross-sections are compared with next-to-leading-order perturbative QCD calculations by NLOJet++ corrected to account for non-perturbative effects. Comparisons with POWHEG predictions, using a next-to-leading-order matrix element calculation interfaced to a partonshower Monte Carlo simulation, are also shown. Electroweak effects are accounted for in both cases. The quantitative comparison of data and theoretical predictions obtained using various parameterizations of the parton distribution functions is performed using a frequentist method. In general, good agreement with data is observed for the NLOJet++ theoretical predictions when using the CT10, NNPDF2.1 and MSTW 2008 PDF sets. Disagreement is observed when using the ABM11 and HERAPDF1.5 PDF sets for some ranges of dijet mass and half the rapidity separation. An example setting a lower limit on the compositeness scale for a model of contact interactions is presented, showing that the unfolded results can be used to constrain contributions to dijet production beyond that predicted by the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2015

Self-consistent Kohn-Sham method based on the adiabatic-connection fluctuation-dissipation theorem and the exact-exchange kernel

A self-consistent Kohn-Sham method based on the adiabatic-connection fluctuation-dissipation (ACFD) theorem, employing the frequency-dependent exact exchange kernel f{sub x} is presented. The resulting SC-exact-exchange-only (EXX)-ACFD method leads to even more accurate correlation potentials than those obtained within the direct random phase approximation (dRPA). In contrast to dRPA methods, not only the Coulomb kernel but also the exact exchange kernel f{sub x} is taken into account in the EXX-ACFD correlation which results in a method that, unlike dRPA methods, is free of self-correlations, i.e., a method that treats exactly all one-electron systems, like, e.g., the hydrogen atom. The self-consistent evaluation of EXX-ACFD total energies improves the accuracy compared to EXX-ACFD total energies evaluated non-self-consistently with EXX or dRPA orbitals and eigenvalues. Reaction energies of a set of small molecules, for which highly accurate experimental reference data are available, are calculated and compared to quantum chemistry methods like Møller-Plesset perturbation theory of second order (MP2) or coupled cluster methods [CCSD, coupled cluster singles, doubles, and perturbative triples (CCSD(T))]. Moreover, we compare our methods to other ACFD variants like dRPA combined with perturbative corrections such as the second order screened exchange corrections or a renormalized singles correction. Similarly, the performance of our EXX-ACFD methods is investigated for the non-covalently bonded dimers of the S22 reference set and for potential energy curves of noble gas, water, and benzene dimers. The computational effort of the SC-EXX-ACFD method exhibits the same scaling of N{sup 5} with respect to the system size N as the non-self-consistent evaluation of only the EXX-ACFD correlation energy; however, the prefactor increases significantly. Reaction energies from the SC-EXX-ACFD method deviate quite little from EXX-ACFD energies obtained non-self-consistently with dRPA orbitals and eigenvalues, and the deviation reduces even further if the Coulomb kernel is scaled by a factor of 0.75 in the dRPA to reduce self-correlations in the dRPA correlation potential. For larger systems, such a non-self-consistent EXX-ACFD method is a competitive alternative to high-level wave-function-based methods, yielding higher accuracy than MP2 and CCSD methods while exhibiting a better scaling of the computational effort than CCSD or CCSD(T) methods. Moreover, EXX-ACFD methods were shown to be applicable in situation characterized by static correlation.

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

WE-EF-BRA-07: High Performance Preclinical Irradiation Through Optimized Dual Focal Spot Dose Painting and Online Virtual Isocenter Radiation Field Targeting

Purpose: Advances in radiotherapy practice facilitated by collimation systems to shape radiation fields and image guidance to target these conformal beams have motivated proposals for more complex dose patterns to improve the therapeutic ratio. Recent progress in small animal radiotherapy platforms has provided the foundation to validate the efficacy of such interventions, but robustly delivering heterogeneous dose distributions at the scale and accuracy demanded by preclinical studies remains challenging. This work proposes a dual focal spot optimization method to paint spatially heterogeneous dose regions and an online virtual isocenter targeting method to accurately target the dose distributions. Methods: Two-dimensional dose kernels were empirically measured for the 1 mm diameter circular collimator with radiochromic film in a solid water phantom for the small and large x-ray focal spots on the X-RAD 225Cx microirradiator. These kernels were used in an optimization framework which determined a set of animal stage positions, beam-on times, and focal spot settings to optimally deliver a given desired dose distribution. An online method was developed which defined a virtual treatment isocenter based on a single image projection of the collimated radiation field. The method was demonstrated by optimization of a 6 mm circular 2 Gy target adjoining a 4 mm semicircular avoidance region. Results: The dual focal spot technique improved the optimized dose distribution with the proportion of avoidance region receiving more than 0.5 Gy reduced by 40% compared to the large focal spot technique. Targeting tests performed by irradiating ball bearing targets on radiochromic film pieced revealed the online targeting method improved the three-dimensional accuracy from 0.48 mm to 0.15 mm. Conclusion: The dual focal spot optimization and online virtual isocenter targeting framework is a robust option for delivering dose at the preclinical level and provides a new experimental option for unique radiobiological investigations This work is supported, in part, by the Natural Sciences and Engineering Research Council of Canada and a Mitacs-Accelerate fellowship. P.E. Lindsay, and D.A. Jaffray are listed as inventors of the system described herein. This system has been licensed to Precision X-Ray Inc. for commercial development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

EGS Collab Testbed 1: Second Set Tracer Test Results

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead, South Dakota, where hydraulic fractures were created at an injection well drilled sub-horizontal from the drift. This file contains the second set of tracer data (also include the data uploaded previously, https://gdr.openei.org/submissions/1128) for the EGS Collab testbed. The tracer tests were conducted during October 2018 - November 2019. Injected tracers include DNA, C-dots (fluorescein nano particles), fluorescein, rhodamine-b, sodium chloride, lithium bromide and cesium iodine. The tracers have been detected in three flowing wells located about 7.5 to 9 meters away from the injection interval. The tracer breakthrough curves from these locations have been adjusted to account for the residence time in the injection and production tubing. The details about the tracer test can be found in Background and Methods of Tracer Tests (Mattson et al. (2019,a,b)) (also included in this package). References Mattson, E.D., Neupane, G., Plummer, M.A., Hawkins, A., Zhang, Y. and the EGS Collab Team 2019a. Preliminary Collab fracture characterization results from flow and tracer testing efforts. In Proceedings 44th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California. Mattson, E.D., Neupane, G., Hawkins, A., Burghardt, J., Ingraham, M., Plummer, M., and the EGS Collab Team, 2019b. Fracture tracer injection response to pressure perturbations at an injection well. GRC Transactions, Vol. 43, 2019. Neupane, Ghanashyam, Earl Mattson, Adam Hawkins, Mitchell Plummer, and Yuran Zhang. EGS Collab Testbed 1: Tracer data sets. No. 1128. DOE Geothermal Data Repository; Idaho National Laboratory, 2019.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Guidance on Including Social, Organizational and Technical Influences in Nuclear Utility and Plant Modernization Plans

The objective of this report is to provide the nuclear power industry with guidance on including socio-technical issues in plans developed for current and future modernization efforts. Socio-technical issues of concern include social, organizational and related technical aspects of modernized systems. These can be addressed using a set of systematic analysis and design methods developed to address socio-technical issues of the sort facing the nuclear power industry. The next phase of this work will involve developing and implementing a modernization plan that includes socio-technical tools and methods identified and discussed in a report by Dainoff and colleagues (2020). The plan is expected to be developed and implemented in cooperation with a nuclear utility that has expressed interest in participating. The Dainoff et al report provides the foundation for the present effort and presents a methodological tool set for analyzing socio-technical issues applicable to many modernization efforts. The tools described by Dainoff et al are based on principles of human factors engineering, safety engineering, and systems engineering and are discussed within the specific context of nuclear utility modernization and transformation efforts. It is expected that the plan and the concepts described in the current report will be developed and implemented with a nuclear utility partner. The plan developed with the nuclear utility partner will have a substantially higher level of detail than the guidance provided in this report, particularly with regard to details of plan logistics, etc.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Scalable Computational Methods for the Analysis of High-Throughput Biological Data

This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A hybrid calibration approach to Hertz-type contact parameters for discrete element models

This study aims at providing a hybrid calibration framework to estimate Hertz-type contact parameters (particle-scale shear modulus and Poisson ratio) for both two-dimensional and three-dimensional discrete element modelling (DEM). On the basis of statistically isotropic granular packings, a set of analytical formulae between macroscopic material parameters (Young modulus and Poisson ratio) and particle-scale Hertz-type contact parameters for granular systems are derived under small-strain isotropic stress conditions. However, the derived analytical solutions are only estimated values for general models. By viewing each DEM modelling as an implicit mathematical function taking the particle-level parameters as independent variables and employing the derived analytical solutions as the initial input parameters, an automatic iterative scheme is proposed to obtain the calibrated parameters with higher accuracies. Considering highly nonlinear features and discontinuities of the macro-micro relationship in Hertz-based discrete element models, the adaptive moment estimation algorithm is adopted in this study because of its capacity of dealing with noise gradients of cost functions. Here, the proposed method is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. Noticeable improvements in terms of calibration efficiency and accuracy have been made.

Constitutive law↗
DOE OSTI2022

Linking the singularities of cosmological correlators

Much of the structure of cosmological correlators is controlled by their singularities, which in turn are fixed in terms of flat-space scattering amplitudes. An important challenge is to interpolate between the singular limits to determine the full correlators at arbitrary kinematics. This is particularly relevant because the singularities of correlators are not directly observable, but can only be accessed by analytic continuation. In this paper, we study rational correlators — including those of gauge fields, gravitons, and the inflaton — whose only singularities at tree level are poles and whose behavior away from these poles is strongly constrained by unitarity and locality. We describe how unitarity translates into a set of cutting rules that consistent correlators must satisfy, and explain how this can be used to bootstrap correlators given information about their singularities. We also derive recursion relations that allow the iterative construction of more complicated correlators from simpler building blocks. In flat space, all energy singularities are simple poles, so that the combination of unitarity constraints and recursion relations provides an efficient way to bootstrap the full correlators. In many cases, these flat-space correlators can then be transformed into their more complex de Sitter counterparts. As an example of this procedure, we derive the correlator associated to graviton Compton scattering in de Sitter space, though the methods are much more widely applicable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: a tomographic measurement of cosmic structure growth and expansion rate based on optimal redshift weights

We develop a new method, which is based on the optimal redshift weighting scheme, to extract the maximal tomographic information of baryonic acoustic oscillations (BAO) and redshift space distortions (RSD) from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 14 quasar (DR14Q) survey. We validate our method using the Extended Zel’dovich mocks, and apply our pipeline to the eBOSS DR14Q sample in the redshift range of 0.8 < z < 2.2. We report a joint measurement of fσ8 and two-dimensional BAO parameters D A and H at four effective redshifts of z eff = 0.98, 1.23, 1.52, and 1.94, and provide the full data covariance matrix. Using our measurement combined with BOSS DR12, Main Galaxy Sample (MGS), and 6 degree Field Galaxy Survey (6dFGS) BAO measurements, we find that the existence of dark energy is supported by observations at a 7.4σ significance level. Combining our measurement with BOSS DR12 and Planck observations, we constrain the gravitational growth index to be γ = 0.580 ± 0.082, which is fully consistent with the prediction of general relativity. This paper is part of a set that analyses the eBOSS DR14 quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Intercomparison of Commercially Available Active Radon Measurement Devices in a Discovered Radon Chamber

An unventilated 70 m 3 underground space, with 2.1 m high ceilings and an inner set of concrete walls to damp vibrations, was discovered to have relatively stable radon levels of ~1,080 Bq m -3 over a 1-y period. The addition of radium sources was not required to achieve high and somewhat variable radon levels, as these arise naturally in the space. Several active radon monitoring devices designed for homeowners, radon screeners, radon mitigation professionals, and researchers were tested in the space. These devices were variable in both cost and intended user sophistication. Data were collected at specific time intervals that varied for each device. A cellphone was deployed with an available camera application to periodically capture photographs of the displays of devices not enabled for automatic temporal recording. Attempts were made to alter the radon concentration using fans, radium-laden objects, and radon impermeable sheets. Statistical methods were employed to compare the device's performance under the minor radon transients produced by the addition of 226 Ra sources during the test period. The evaluation of the overall accuracy, noise, and response to transients revealed highly affordable devices that may be useful for future research applications.While unsuitable for precise calibrations at stable radon levels, the space was determined to be adequate as a radon chamber for general research purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Using butterfly survey data to model habitat associations in urban developments

Abstract One approach for measuring the potential biodiversity in new urban construction projects is through ecological models that predict how wildlife will respond. For the United Kingdom, such models have only been developed for birds, but to maximise the extent to which models represent overall biodiversity, species from different indicator groups must be considered. Here, we assess this possibility for butterflies by combining citizen science survey data with high‐resolution digital maps. We derive detailed characteristics of urban landscapes around survey sites using previously established methods and quantify their relationship to counts of adults of 18 butterfly species in urban and peri‐urban settings. Higher butterfly counts were found when traversing urban sites with larger areas of semi‐natural grassland, other managed greenspaces and adjacent arable land. Most of the butterfly community were found to have negative relationships with highly built‐up or fragmented landscapes. We found high species‐specificity for different details of urban form, particularly in habitat elements such as gardens, vegetation around railways and grass verges. Policy implications . Improving biodiversity is now part of legislation governing new construction projects from England and Wales. However, predicting quantitative changes from hypothetical land‐use modifications remains challenging. Our models provide the foundation through which butterfly abundance could be integrated into an urban biodiversity assessment tool, providing species‐ and community‐level statistics to non‐specialists from the urban planning and design sector. This would allow them to hone configurations for built surfaces, private gardens, greenspaces and wildlife areas and assess their capacity to provide residents with the intended access to nature.

Cooper, Joseph E. J.↗
DOE OSTI2017

Pillars of the Mantle: Imaging the Interior of the Earth with Adjoint Tomography. In: PEARC17 Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact, Article No. 75

In this work, we investigate global seismic tomographic models obtained by spectral-element simulations of seismic wave propagation and adjoint methods. Global crustal and mantle models are obtained based on an iterative conjugate-gradient type of optimization scheme. Forward and adjoint seismic wave propagation simulations, which result in synthetic seismic data to make measurements and data sensitivity kernels to compute gradient for model updates, respectively, are performed by the SPECFEM3D_GLOBE package [1] [2] at the Oak Ridge Leadership Computing Facility (OLCF) to study the structure of the Earth at unprecedented levels. Using advances in solver techniques that run on the GPUs on Titan at the OLCF, scientists are able to perform large-scale seismic inverse modeling and imaging. Using seismic data from global and regional networks from global CMT earthquakes, scientists are using SPECFEM3D_GLOBE to understand the structure of the mantle layer of the Earth. Visualization of the generated data sets provide an effective way to understand the computed wave perturbations which define the structure of mantle in the Earth.

Pugmire, David↗