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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 OSTI2021

Summer mean and extreme precipitation over the Mid-Atlantic region: climatological characteristics and contributions from different precipitation types

Based on a long-term observational dataset from the tracking of mesoscale convective systems (MCSs), isolated deep convection (IDC), and tropical cyclones (TCs), we examine the climatological characteristics of summer mean and extreme precipitation during 2004 – 2017 and their respective contributions from MCS, IDC, TC, and non-convective (NC) systems and the local vs. remote influence of MCS and IDC over the MAR. On average, MCS, IDC, TC, and NC contribute 22%, 29%, 4%, and 45% to the total summer mean precipitation in the region. While MCS and TC precipitation primarily occurs in the coastal areas east of the Appalachian Mountains, IDC precipitation is more concentrated in the southern MAR and near the mountain windward slopes. Each summer, ~41 MCSs with an average lifetime of 19.6 hours influence the MAR, with 80% initiated outside and traveling on average 10 hours to the region. Around 13 MCSs initiated in the Great Plains and Midwest propagate across the Appalachian Mountains and contribute 20-40% to summer MCS precipitation in the central Mid-Atlantic coastal areas. In contrast, more than 2000 IDCs with an average lifetime of 2.0 hours influence the MAR each summer, and 77% are initiated locally. MCS, IDC, TC, and NC contribute 31% (30%), 26% (31%), 18% (7%), and 26% (32%) to the top 1% (5%) extreme daily precipitation, respectively. Considering extreme hourly precipitation, however, the IDC contributions increase to 41% (top 1%) and 38% (top 5%) due to the shorter duration of IDC events than the other precipitation types.

Li, Jianfeng↗
DOE OSTI2020

Windowing artefacts likely account for recent claimed detection of oscillating cosmic scale factor

ABSTRACT Using the Pantheon data set of Type Ia supernovae, a recent publication (R20 in this work) reports a 2σ detection of oscillations in the expansion history of the Universe. The study conducted by R20 is wholly worthwhile. However, we demonstrate that there is a $\gt 10{{\ \rm per\ cent}}$ chance of statistical fluctuations in the Pantheon data producing a false oscillatory signal larger than the oscillatory signal that R20 report. Their results are a less than 2σ detection. Applying the R20 methodology to simulated Pantheon data, we determine that these oscillations could arise due to analysis artefacts. The uneven spacing of Type Ia supernovae in redshift space and the complicated analysis method of R20 impose a structured throughput function. When analysed with the R20 prescription, about $11{{\ \rm per\ cent}}$ of artificial ΛCDM data sets produce a stronger oscillatory signal than the actual Pantheon data. Our results underscore the importance of understanding the false ‘signals’ that can be introduced by complicated data analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Data Science Infrastructure SOFTWARE

LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. The Data Science Infrastructure (DSI) project focuses on data-driven approaches to make data more readily available to LANL projects. DSI workflows leverage metadata stored in data-agnostic databases, supported by an abstraction layer API to simplify searching and accessing data across simulation runs, experimental runs, filesystems and environments. The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.

Turton, Terece↗
DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Fortran for the nineties

Fortran has largely enjoyed prominence for the past few decades as the computer programming language of choice for numerically intensive scientific, engineering, and process control applications. Fortran's well understood static language syntax has allowed resulting parsers and compiler optimizing technologies to often generate among the most efficient and fastest run-time executables, particularly on high-end scalar and vector supercomputers. Computing architectures and paradigms have changed considerably since the last ANSI/ISO Fortran release in 1978, and while FORTRAN 77 has more than survived, it's aged features provide only partial functionality for today's demanding computing environments. The simple block procedural languages have been necessarily evolving, or giving way, to specialized supercomputing, network resource, and object-oriented paradigms. To address these new computing demands, ANSI has worked for the last 12-years with three international public reviews to deliver Fortran 90. Fortran 90 has superseded and replaced ISO FORTRAN 77 internationally as the sole Fortran standard; while in the US, Fortran 90 is expected to be adopted as the ANSI standard this summer, coexisting with ANSI FORTRAN 77 until at least 1996. The development path and current state of Fortran will be briefly described highlighting the many new Fortran 90 syntactic and semantic additions which support (among others): free form source; array syntax; new control structures; modules and interfaces; pointers; derived data types; dynamic memory; enhanced I/O; operator overloading; data abstraction; user optional arguments; new intrinsics for array, bit manipulation, and system inquiry; and enhanced portability through better generic control of underlying system arithmetic models. Examples from dynamical astronomy, signal and image processing will attempt to illustrate Fortran 90's applicability to today's general scalar, vector, and parallel scientific and engineering requirements and object oriented programming paradigms. Time permitting, current work proceeding on the future development of Fortran 2000 and collateral standards will be introduced.

Himer, J. T.↗
DOE OSTI2025

Comparative Economic Analysis Between Bioenergy and Forage Types of Switchgrass for Sustainable Biofuel Feedstock Production: A Data Envelopment Analysis and Cost–Benefit Analysis Approach

ABSTRACT The capacity to produce switchgrass efficiently and cost‐effectively across diverse environments can be pivotal in achieving the short‐ and medium‐term Sustainable Aviation Fuel targets set by the U.S. Department of Energy. This study evaluated the economic performance of forage‐ and bioenergy‐type switchgrass cultivars and their response to N fertilization under diverse marginal environments across the US Midwest that included Illinois (IL), Iowa (IA), Nebraska (NE), and South Dakota (SD). Data Envelopment Analysis (DEA) was used to evaluate the efficiency of 23 Decision‐Making Units (DMUs)—cultivar types and N fertilization rate combinations—while a cost–benefit analysis calculated their profitability over 5 years. Results showed that two energy‐type cultivars—“Independence” and “Liberty”—were superior economically to the forage cultivars. Independence performed best with the highest profit margin when fertilized at 56 kg N ha −1 , particularly in the US hardiness zone 6a (Urbana, IL). Liberty exhibited the highest profit margins in hardiness zone 5b (Madrid, IA, and Ithaca, NE) at 56 kg N ha −1 and showed exceptional profitability with 28 kg N ha −1 in hardiness zone 6b (Brighton, IL). Switchgrass cultivar “Carthage” showed better efficiency score and profitability results in hardiness zone 4b (South Shore, SD) at 56 kg N ha −1 . The profit trends observed in current study sites may indicate broader patterns across similar US hardiness zones. This study provides valuable insights for decision‐makers to optimize input strategies for biomass production of bioenergy switchgrass to meet renewable energy demands.

Arshad, Muhammad Umer [Department of Crop Sciences↗
DOE OSTI2022

The relation between accretion rate and jet power in early-type galaxies with thermally unstable hot atmospheres

ABSTRACT We use Chandra X-ray data and Very Large Array radio observations for a sample of 20 nearby, massive, X-ray bright, early-type galaxies to investigate the relation between the Bondi accretion rates and the mechanical jet powers. We find a strong correlation ($\rho = 0.96^{+0.03}_{-0.09}$; BF10 > 100) between the Bondi accretion power, PBondi, and the mechanical jet power, Pjet, for a subsample of 14 galaxies, which also host cool H α+[N ii] line emitting gas and thus likely have thermally unstable atmospheres. The relation between the Bondi accretion power and the mechanical jet power for this subsample is well described by a power-law model $\log \frac{P_{\mathrm{Bondi}}}{{10^{43} \, \mathrm{erg \, s^{-1}}}} = \alpha + \beta \log \frac{P_{\mathrm{jet}}}{{10^{43} \, \mathrm{erg \, s^{-1}}}}$, where α = 1.10 ± 0.25 and β = 1.10 ± 0.24 with an intrinsic scatter $\sigma = 0.08^{+0.14}_{-0.06}$ dex. The results indicate that in all galaxies with thermally unstable atmospheres the cooling atmospheric gas feeds the central black holes at a similar jet-to-Bondi power ratio. For the full sample of 20 galaxies, the correlation is weaker and in a subset of galaxies with no signs of H α+[N ii] emission, we see a hint for a systematically lower jet-to-Bondi power ratio. We also investigate the dependence of jet power on individual quantities in the Bondi formula such as the supermassive black hole mass (M•) and the specific entropy of the gas (K) at the Bondi radius. For the subsample of H α+[N ii] emitting galaxies, we find a very tight correlation of Pjet with M• ($\rho = 0.91^{+0.06}_{-0.11}$; BF10 > 100) and, although poorly constrained, a hint of an anticorrelation for Pjet and K ($\rho = -0.47^{+0.60}_{-0.37}$; BF10 = 1.1).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Type Ia supernova observations combining data from the Euclid mission and the Vera C. Rubin Observatory

ABSTRACT The Euclid mission will provide first-of-its-kind coverage in the near-infrared over deep (three fields, ∼10–20 square degrees each) and wide (∼10 000 square degrees) fields. While the survey is not designed to discover transients, the deep fields will have repeated observations over a two-week span, followed by a gap of roughly six months. In this analysis, we explore how useful the deep field observations will be for measuring properties of Type Ia supernovae (SNe Ia). Using simulations that include Euclid’s planned depth, area, and cadence in the deep fields, we calculate that more than 3700 SNe between 0.0 < $z$ < 1.5 will have at least five Euclid detections around peak with signal-to-noise ratio larger than 3. While on their own, Euclid light curves are not good enough to directly constrain distances, when combined with legacy survey of space and time (LSST) deep field observations, we find that uncertainties on SN distances are reduced by 20–30 per cent for $z$ < 0.8 and by 40–50 per cent for $z$ > 0.8. Furthermore, we predict how well additional Euclid mock data can be used to constrain a key systematic in SN Ia studies – the size of the luminosity ‘step’ found between SNe hosted in high-mass (>1010 M⊙) and low-mass (<1010 M⊙) galaxies. This measurement has unique information in the rest-frame near-infrared (NIR). We predict that if the step is caused by dust, we will be able to measure its reduction in the NIR compared to optical at the 4σ level. We highlight that the LSST and Euclid observing strategies used in this work are still provisional and some level of joint processing is required. Still, these first results are promising, and assuming that Euclid begins observations well before the Nancy Roman Space Telescope (Roman), we expect this data set to be extremely helpful for preparation for Roman itself.

Astronomy & Astrophysics↗
DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The DEHVILS survey overview and initial data release: high-quality near-infrared Type Ia supernova light curves at low redshift

ABSTRACT While the sample of optical Type Ia supernova (SN Ia) light curves (LCs) usable for cosmological parameter measurements surpasses 2000, the sample of published, cosmologically viable near-infrared (NIR) SN Ia LCs, which have been shown to be good ‘standard candles,’ is still ≲ 200. Here, we present high-quality NIR LCs for 83 SNe Ia ranging from 0.002 < z < 0.09 as a part of the Dark Energy, H0, and peculiar Velocities using Infrared Light from Supernovae (DEHVILS) survey. Observations are taken using UKIRT’s WFCAM, where the median depth of the images is 20.7, 20.1, and 19.3 mag (Vega) for Y, J, and H-bands, respectively. The median number of epochs per SN Ia is 18 for all three bands (Y,J, and H) combined and 6 for each band individually. We fit 47 SN Ia LCs that pass strict quality cuts using three LC models, SALT3, snoopy, and B ayeSN and find scatter on the Hubble diagram to be comparable to or better than scatter from optical-only fits in the literature. Fitting NIR-only LCs, we obtain standard deviations ranging from 0.128 to 0.135 mag. Additionally, we present a refined calibration method for transforming 2MASS magnitudes to WFCAM magnitudes using HST CALSPEC stars that results in a 0.03 mag shift in the WFCAM Y-band magnitudes.

Astronomy & Astrophysics↗
DOE OSTI2021

Using Pantheon and DES supernova, baryon acoustic oscillation, and Hubble parameter data to constrain the Hubble constant, dark energy dynamics, and spatial curvature

ABSTRACT We use Pantheon Type Ia supernova (SN Ia) apparent magnitude, DES-3 yr binned SN Ia apparent magnitude, Hubble parameter, and baryon acoustic oscillation measurements to constrain six spatially flat and non-flat cosmological models. These sets of data provide mutually consistent cosmological constraints in the six cosmological models we study. A joint analysis of these data sets provides model-independent estimates of the Hubble constant, $H_0=68.8\pm 1.8\ \rm {km \, s^{-1} \ Mpc^{-1}}$, and the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.294\pm 0.020$. Although the joint constraints prefer mild dark energy dynamics and a little spatial curvature, they do not rule out dark energy being a cosmological constant and flat spatial hypersurfaces. We also add quasar angular size and H ii starburst galaxy measurements to the combined data set and find more restrictive constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

SSL Freeform Generator v1.00

The Orion spacecraft utilizes a system of Compact Unique Identifiers (CUIs) to identify telemetry measurements in the process of communicating with the ground. While avionic systems are still in development, simulation of telemetric data must be used for the development of dependent systems. The SuperScript Language (SSL) developed by Honeywell Aerospace provides users a programming language for simulation of this data. The use of tools that provide SSL generation capabilities at a higher level allows for faster and more efficient generation of simulation waveforms. Previous SSL Generator implementations such as Orion Scripted Interface Generator (OrionSIG) relied on software supported routines to generate simulation points for the SSL scripts. This provided relevant simulation capabilities, but was reduced in flexibility by the available software routines available. For this approach, software supported routines have been entirely dropped. Rather, the user is required to enter their own simulation waveform input. This allows arbitrarily complex functions to be utilized simulated with maximum degree of freedom for the user.: The idea for this version of the SSL Generator was a mapping of arbitrary waveforms to Orion CUI telemetry data. The SSL Generator implemented offers a higher degree of freedom to the user than previous versions while attempting to maintain abstraction from the underlying SSL script and the Orion CUI data types. As such, many mappings of waveforms to CUIs will simply not work. Certain implementation decisions were made to minimize the damage caused by these unintended side-effects, such as saturation of values exceeding the maximum or minimum bounds of the data type. Other details, such as signed values being represented in unsigned data types, present problems which cant be fixed to an acceptable degree of intended behavior without user input. Awareness of the limitations of all layers of the software stack will increase the productivity of the end-user.

telemetry↗
DOE OSTI2022

Constraining ΛCDM cosmological parameters with Einstein Telescope mock data

ABSTRACT We investigate the capability of Einstein Telescope to constrain the cosmological parameters of the non-flat ΛCDM cosmological model. Two types of mock data sets are considered depending on whether or not a short gamma-ray burst is detected, and associated with the gravitational wave emitted by binary neutron stars merger, using the THESEUS satellite. Depending on the mock data set, two statistical estimators are applied: one assumes that the redshift is known, while the other marginalizes over it assuming a specific redshift prior distribution. We demonstrate that (i) using mock catalogues collecting gravitational wave signals emitted by binary neutron stars systems to which a short gamma-ray burst has been associated, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.40$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.09$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.07$; while (ii) using mock catalogues collecting all gravitational wave signals emitted by binary neutron stars systems for which an electromagnetic counterpart has not been detected, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.04$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.01$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.01$, once the redshift probability distribution of GW events is known from from population synthesis simulations and/or the measure of the tidal deformability parameter. These results show an improvement of a factor 2–75 with respect to earlier results using complementary data sets.

Califano, Matteo↗
DOE OSTI2020

Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models

Process-based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass-dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C 3 grasses and (sub)tropical C 4 grasses. Incorporation of species-level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve LSM representations. In this work, our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), situated between species-level trait data and PFT-level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

DABI: A data base for image analysis with nondeterministic inference capability

A description is given of the data base used in the perception subsystem of the Mars robot vehicle prototype being implemented at the Jet Propulsion Laboratory. This data base contains two types of information. The first is generic (uninstantiated, abstract) information that specifies the general rules of perception of objects in the expected environments. The second kind of information is a specific (instantiated) description of a structure, i.e., the properties and relations of objects in the specific case being analyzed. The generic knowledge can be used by the approximate reasoning subsystem to obtain information on the specific structures which is not directly measurable by the sensory instruments. Raw measurements are input either from the sensory instruments or a human operator using a CRT or a TTY.

Yakimovsky, Y.↗
DOE OSTI2023

TOI-908: a planet at the edge of the Neptune desert transiting a G-type star

ABSTRACT We present the discovery of an exoplanet transiting TOI-908 (TIC-350153977) using data from TESS sectors 1, 12, 13, 27, 28, and 39. TOI-908 is a T = 10.7 mag G-dwarf (Teff = 5626 ± 61 K) solar-like star with a mass of 0.950 ± 0.010 M⊙ and a radius of 1.028 ± 0.030 R⊙. The planet, TOI-908 b, is a 3.18 ± 0.16 R⊕ planet in a 3.18 d orbit. Radial velocity measurements from HARPS reveal TOI-908 b has a mass of approximately 16.1 ± 4.1 M⊕, resulting in a bulk planetary density of $2.7^{+0.2}_{-0.4}$ g cm−3. TOI-908 b lies in a sparsely populated region of parameter space known as the Neptune desert. The planet likely began its life as a sub-Saturn planet before it experienced significant photoevaporation due to X-rays and extreme ultraviolet radiation from its host star, and is likely to continue evaporating, losing a significant fraction of its residual envelope mass.

Hawthorn, Faith (ORCID:000000028675182X)↗
DOE OSTI2024

Keck Infrared Transient Survey. I. Survey Description and Data Release 1

Abstract We present the Keck Infrared Transient Survey, a NASA Key Strategic Mission Support program to obtain near-infrared (NIR) spectra of astrophysical transients of all types, and its first data release, consisting of 105 NIR spectra of 50 transients. Such a data set is essential as we enter a new era of IR astronomy with the James Webb Space Telescope (JWST) and the upcoming Nancy Grace Roman Space Telescope (Roman). NIR spectral templates will be essential to search JWST images for stellar explosions of the first stars and to plan an effective Roman SN Ia cosmology survey, both key science objectives for mission success. Between 2022 February and 2023 July, we systematically obtained 274 NIR spectra of 146 astronomical transients, representing a significant increase in the number of available NIR spectra in the literature. Here, we describe the first release of data from the 2022A semester. We systematically observed three samples: a flux-limited sample that includes all transients <17 mag in a red optical band (usually ZTF r or ATLAS o bands); a volume-limited sample including all transients within redshift z < 0.01 ( D ≈ 50 Mpc); and an SN Ia sample targeting objects at phases and light-curve parameters that had scant existing NIR data in the literature. The flux-limited sample is 39% complete (60% excluding SNe Ia), while the volume-limited sample is 54% complete and is 79% complete to z = 0.005. Transient classes observed include common Type Ia and core-collapse supernovae, tidal disruption events, luminous red novae, and the newly categorized hydrogen-free/helium-poor interacting Type Icn supernovae. We describe our observing procedures and data reduction using PypeIt , which requires minimal human interaction to ensure reproducibility.

Tinyanont, S. (ORCID:0000000214814676)↗