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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
DOE OSTI2020

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

In this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery. The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L -1 ) agreed—to within a factor of about 2—with aircraft data at flight levels (-10° to -15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations. The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Thermal chains and entrainment in cumulus updrafts, Part 1: Theoretical description

Recent studies have shown that cumulus updrafts often consist of a succession of discrete rising thermals with spherical vortex-like circulations. Herein, a theory is developed for why this “thermal chain” structure occurs. Theoretical expressions are obtained for a passive tracer, buoyancy, and vertical velocity in axisymmetric moist updrafts. Analysis of these expressions suggests that the thermal chain structure arises from enhanced lateral mixing associated with intrusions of dry environmental air below an updraft’s vertical velocity maximum. This dry air entrainment reduces buoyancy locally. Consequently, the updraft flow above levels of locally reduced buoyancy separates from below, leading to a breakdown of the updraft into successive discrete thermals. The range of conditions in which thermal chains exist is also analyzed from the theoretical expressions. A transition in updraft structure from isolated rising thermal, to thermal chain, to starting plume occurs with increases in updraft width, environmental relative humidity, and/or convective available potential energy. Corresponding expressions for the bulk fractional entrainment rate ε are also obtained. These expressions indicate rather complicated entrainment behavior of ascending updrafts, with local enhancement of ε up to a factor of ~2 associated with the aforementioned environmental air intrusions, consistent with recent large eddy simulation (LES) studies. These locally large entrainment rates contribute significantly to overall updraft dilution in thermal chain-like updrafts, while other regions within the updraft can remain relatively undilute. Part 2 of this study compares results from the theoretical expressions to idealized numerical simulations and LES.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Bimodal Diagnostic Cloud Fraction Parameterization. Part I: Motivating Analysis and Scheme Description

Cloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional midlatitude forecasts, the Met Office uses a diagnostic cloud fraction scheme that relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. Additionally, for model grid boxes located in this entrainment zone, collocated moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given gridbox mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the southern Great Plains in the United States, it is shown that the new scheme improves the relation between cloud fraction, relative humidity, and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in Part II.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

COVID-19-Related Experiences and Perspectives of Peruvian College Students: A Descriptive Study

The COVID-19 pandemic drastically affected higher education and higher education students around the world, but few studies of college students’ experiences during the COVID-19 pandemic have been conducted in Latin America. This study describes the COVID-19-related experiences and perspectives of Peruvian college students. We surveyed 3,427 full-time college students (average age: 23 years) attending a multi-campus Peruvian university in fall 2020. Participants were recruited through the digital platform of the learning management system at their university, email, and social media. We asked participants how they were managing risks related to COVID-19; the continuity of social, educational, and work activities; and the psychological and economic impacts of the pandemic on their lives. Since March 2020, 73.0% of participants reported COVID-19-related symptoms, but only 33.9% were tested for COVID-19. During the national quarantine imposed by the Peruvian government (March 15–June 30, 2020), 64.3% of participants remained in their house. Furthermore, while 44.0% of participants were working in February 2020 (95% CI: [41.7%, 46.4%]), only 23.6% (95% CI: [21.7%, 25.7%]) were working immediately after the pandemic began (i.e., at the end of April 2020). Participants were more stressed about the health and educational implications of COVID-19 for Peruvian society and their families than about themselves. The public health, economic, and educational implications of COVID-19 on college students are continuing to unfold. This study informed Peruvian higher education institutions’ continued response to the COVID-19 pandemic, the progressive return to postpandemic activities, as well as other future pandemics and other crises.

Bazo-Alvarez, Juan Carlos↗
DOE OSTI2020

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Multimode description of self-mode locking in a single-section quantum-dot laser

This paper describes a theory for mode locking and frequency comb generation by four-wave mixing in a semiconductor quantum-dot active medium. The derivation uses a multimode semiclassical laser theory that accounts for fast carrier collisions within an inhomogeneous distribution of quantum dots. Numerical simulations are presented to illustrate the role of active medium nonlinearities in mode competition, gain saturation, carrier-induced refractive index and creation of combination tones that lead to locking of beat frequencies among lasing modes in the presence of cavity material dispersion.

Chow, Weng W.↗
DOE OSTI2020

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hydroxylpyromorphite, a mineral important to lead remediation: Modern description and characterization

Abstract Hydroxylpyromorphite, Pb5(PO4)3(OH), has been documented in the literature as a synthetic and naturally occurring phase for some time but has not previously been formally described as a mineral. It is fully described here for the first time using crystals collected underground in the Copps mine, Gogebic County, Michigan. Hydroxylpyromorphite occurs as aggregates of randomly oriented hexagonal prisms, primarily between about 20–35 μm in length and 6–10 μm in diameter. The mineral is colorless and translucent with vitreous luster and white streak. The Mohs hardness is ~3½–4; the tenacity is brittle, the fracture is irregular, and indistinct cleavage was observed on {001}. Electron microprobe analyses provided the empirical formula Pb4.97(PO4)3(OH0.69F0.33Cl0.06)Σ1.08. The calculated density using the measured composition is 7.32 g/cm3. Powder X-ray diffraction data for the type material is compared to data previously reported for hydroxylpyromorphite from the talc mine at Rabenwald, Austria, and from Whytes Cleuch, Wanlockhead, Scotland. Hydroxylpyromorphite is hexagonal, P63/m, at 100 K, a = 9.7872(14), c = 7.3070(10) Å, V = 606.16(19) Å3, and Z = 2. The structure [R1 = 0.0181 for 494 F>4σ(F) reflections] reveals that hydroxylpyromorphite adopts a column anion arrangement distinct from other members of the apatite supergroup due to the presence of fluorine and steric constraints imposed by stereoactive lone-pair electrons of Pb2+ cations. The F– anion sites are displaced slightly from hydroxyl oxygen anions, which allows for stronger hydrogen-bonding interactions that may in turn stabilize the observed column-anion arrangement and overall structure. Our modern characterization of hydroxylpyromorphite provides deeper understanding to a mineral useful for remediation of lead-contaminated water.

Geochemistry & Geophysics↗
DOE OSTI2020

Dimer description of the SU(4) antiferromagnet on the triangular lattice

In systems with many local degrees of freedom, high-symmetry points in the phase diagram can provide an important starting point for the investigation of their properties throughout the phase diagram. In systems with both spin and orbital (or valley) degrees of freedom such a starting point gives rise to SU(4)-symmetric models. Here we consider SU(4)-symmetric "spin" models, corresponding to Mott phases at half-filling, i.e. the six-dimensional representation of SU(4). This may be relevant to twisted multilayer graphene. In particular, we study the SU(4) antiferromagnetic "Heisenberg" model on the triangular lattice, both in the classical limit and in the quantum regime. Carrying out a numerical study using the density matrix renormalization group (DMRG), we argue that the ground state is non-magnetic. We then derive a dimer expansion of the SU(4) spin model. An exact diagonalization (ED) study of the effective dimer model suggests that the ground state breaks translation invariance, forming a valence bond solid (VBS) with a 12-site unit cell. Finally, we consider the effect of SU(4)-symmetry breaking interactions due to Hund's coupling, and argue for a possible phase transition between a VBS and a magnetically ordered state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

EXCESS workshop: Descriptions of rising low-energy spectra

Many low-threshold experiments observe sharply rising event rates of yet unknown origins below a few hundred eV, and larger than expected from known backgrounds. Due to the significant impact of this excess on the dark matter or neutrino sensitivity of these experiments, a collective effort has been started to share the knowledge about the individual observations. For this, the EXCESS Workshop was initiated. In its first iteration in June 2021, ten rare event search collaborations contributed to this initiative via talks and discussions. The contributing collaborations were CONNIE, CRESST, DAMIC, EDELWEISS, MINER, NEWS-G, NUCLEUS, RICOCHET, SENSEI and SuperCDMS. They presented data about their observed energy spectra and known backgrounds together with details about the respective measurements. In this paper, we summarize the presented information and give a comprehensive overview of the similarities and differences between the distinct measurements. The provided data is furthermore publicly available on the workshop's data repository together with a plotting tool for visualization.

Adari, Prakruth↗
DOE OSTI2024

Metadata for a systematic description of signal data

This chapter aims to provide a comprehensive overview of metadata types that may be useful during system design, optimization, and automation. Metadata are grouped into three main categories: (a) metadata describing signal generation, (b) metadata describing signal quality, and (c) contextual information in the form of annotations. Each of these categories is introduced and explained in three separate sections. Importantly, this chapter mainly answers what is considered metadata. To a lesser degree, recommendations are made regarding the selection of metadata for long-term storage. Chapter 4 will explain where and how to store metadata. Chapters 5 and 6 explain how to collect certain metadata through dedicated sensor validation tests (Chapter 5) or algorithmic analysis (Chapter 6).

Alferes, Janelcy↗
DOE OSTI2020

Surface Cloud Grid Version 2 (SFCCLDGRID2) Value-Added Product: Description of Update"

This document describes the algorithm used for the Surface Cloud Grid Value-Added Product (VAP). This VAP uses as input the 15-min. output from the Shortwave (SW) Flux Analysis VAP (see Long 2001; Long and Ackerman 2000; Long et al. 1999) from the Atmospheric Radiation Measurement (ARM) Climate Reseach Facility (ACRF) Southern Great Plains (SGP) Central Facility and extended facilities. This network of 21 sites is unevenly spaced over northern Oklahoma into southern Kansas, covering an area from 95.5° to 99.5° west longitude and 34.5° to 38.5° north latitude. For research applications such as single-column modeling, an estimate of the cloud and cloud effects distribution over this entire domain is desirable. The Surface Cloud Grid VAP applies a multi-pass weighted sum analytic approximation technique (Caracena 1987), which uses Gaussian weighting and an imposed scale length, to interpolate to a 0.25° by 0.25° lat/long grid over the SGP domain. The output, like the input, includes solar elevation angles of 10° or greater.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Description of the LASSO Data Bundles Product

The U. S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has evolved into the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) datastream. The datastream, broadly termed data bundles, contains high-resolution model output, input files, observations for evaluation, and skill scores for the simulations. The initial focus of LASSO is on shallow convection at the ARM Southern Great Plains (SGP) atmospheric observatory. The availability of LES simulations with concurrent observations serves many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES adds value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further, it elucidates unobservable processes and properties. LASSO generates a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It also provides tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. The LASSO library of data bundles is designed to facilitate a wide range of research. For an observationalist, LASSO can help inform instrument remote-sensing retrievals, conduct observation system simulation experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO can help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model personally. For a modeler, LASSO can help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at https://www.arm.gov/capabilities/modeling/lasso.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

IHE Material and IHE Subassembly Qualification Test Description and Criteria (v. 14.7)

The purpose of the deflagration-to-detonation test is to demonstrate that an IHE material will not undergo deflagration-to-detonation transition (DDT) under stockpile relevant conditions of scale, confinement, and material condition. Inherent in this test design is the assumption that ignition does occur, with onset of deflagration. The test design will incorporate large margins and replicates to account for the stochastic nature of DDT events.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Goldsim Modeling of Vadose Zone Transport for E-Area Naval Reactor Component Disposal Areas: Model Description and Benchmarking

This report documents the development of a GoldSim® model of flow and radionuclide transport to the water table through the Naval Reactor Components Disposal Area (NRCDA) waste disposal sites and underlying vadose zones. The model is designed to be used for Monte Carlo uncertainty analysis in support of the E-Area Performance Assessment (PA). This report describes the model and shows results obtained from benchmarking the model to best-estimate deterministic results obtained using a PORFLOW model of NRCDA vadose zone transport. The PORFLOW model is three-dimensional while the GoldSim model is a simplified one-dimensional treatment. Nevertheless, the GoldSim model was able to accurately reproduce PORFLOW results with some adjustment to the nominal dispersion coefficient and vadose zone flow area used as “tuning” parameters. An example of the results obtained comparing GoldSim and PORFLOW calculation of releases of I-129, Tc-99, C-14 and Ni-59 from waste disposal containers at the 643-26E site is shown in Figure 1 below. For all of the test cases evaluated, GoldSim predicted peak concentrations within 6% of the PORFLOW values and peak times agreed within 8% with the majority of the results in better agreement. The close agreement between the two models provides confidence that GoldSim will give results accurately reflecting the behavior of releases from the NRCDA under off-normal operating conditions for sensitivity and uncertainty analysis

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

This technical report introduces a Three-Dimensional Constrained Variational Analysis (3DCVA) (Tang and Zhang 2015) and its product of three-dimensional large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM), and large-eddy simulation (LES) models, and to evaluate model results. The 3DCVA algorithm is an extension of the original 1D constrained variational analysis (1DCVA) (Zhang and Lin 1997, Zhang et al. 2001). The three-dimensional structure of the forcing data allows studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales. In the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the 3D forcing data are assigned the datastream name varanal3d. In this technical report, 3DCVA will be used to refer to the algorithm, while VARANAL3D will be used to refer to the data product.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

MSTAR2019 Code Description and User's Manual

This report describes an ideal cascade model of uranium enrichment that includes side feed and side product streams and flexible input options. It is based on the original MSTAR model developed by Ed Von Halle and implemented in a Visual Basic code. The current version allows the user to specify integer numbers of stages or the stage numbers of external flows instead of assays in those flows. The computational engine is written in FORTRAN-90 and is invoked by a user-friendly GUI written in C++. This version of MSTAR has been demonstrated to operate on Linux, Mac, and Windows platforms, and has undergone significant testing and quality analysis. A number of examples are presented to illustrate the operation of the code and guide the user. The code is extremely fast, and results are returned immediately. The input and output have been specially configured for analysis by the environmental sampling team of the International Atomic Energy Agency (IAEA). A number of additional output features are included to assist the user in visualizing computational results and downloading data to files for use in other analysis software.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗