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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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A questionnaire was sent to EMN project leads, National Lab Node Leads, Industry, academic and international experts in the Spring of 2018. The goal of this effort was to collect broad feedback across the water splitting community with a specific target of obtaining at least a 50% response rate from EMN Level 1 Node Leads and Project PI’s.
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We review criticality data testing performed at Los Alamos with a combination of ENDF/B-VII.1 + potential CIELO nuclear data evaluations. The goal of CIELO is to develop updated, best available evaluated nuclear data files for 1 H, 16 O, 56 Fe, 235,238 U and 239 Pu. because the major international evaluated nuclear data libraries don’t agree on the internal cross section details of these most important nuclides.
The purpose of this report is to provide the reader with an understanding of how a Monte Carlo neutron transport code was written, developed, and evolved to calculate the probability distribution functions (PDFs) and their moments for the neutron number at a final time as well as the cumulative fission number, along with introducing several basic Monte Carlo concepts.
Soils represent the largest terrestrial carbon pool on Earth. Yet emerging theories regarding stabilization of soil organic matter remain poorly represented in global-scale models; thus, underestimating the true uncertainty associated with potential terrestrial carbon cycle – climate feedbacks. With this project we created a testbed to compare and evaluate soil biogeochemical models (W. Wieder at the Univ. of CO, Boulder), data synthesis (R. Phillips, Indiana Univ.) and parameter estimation (S Allison, Univ. CA Irvine) to quantify uncertainty associated with potential soil C changes. This project resulted in 14 Presentations, 14 Publications and helped support the training of three graduate students. A significant accomplishment with this work was the creation of a soil biogeochemical testbed, which forces three soil carbon models (CASA, MIMICS, and CORPSE) with common environmental drivers.
This report discusses the following three new experiments containing lead: HEU/Pb, 'LEU"/Pb, and Pu/Pb.
Two critical experiments with HEU-Lucite were performed using the Planet Universal Critical Assembly Machine at Los Alamos National Laboratory in 2019. HEU foils were interleaved with Lucite in a column stack for moderation and reflection from the square Lucite plates. The evaluation of the experiments is presented. A Monte-Carlo (MCNP6) calculation model was developed for the determination of uncertainties and their effect on the multiplication factor. Experimental uncertainties were found to be low with the overall uncertainty in k eff approximately 240 pcm. The comparison of calculations with experimental data is presented.
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Advanced nuclear reactor designs will for the most part be a departure from low enrichment light water reactor (LWR) designs currently operated around the world. Such advanced designs include but are not limited to new TRISO-fueled high temperature gas reactors, heat-pipe cooled micro-reactors, fluoride salt cooled high-temperature reactors, molten salt reactors, lead cooled fast reactors, nuclear thermal propulsion concepts, and include LWR designs with advanced fuel and clad types. Modeling and simulation methods for advanced reactors is necessary for regulators to approve license requests. However, regulators also require that modeling approaches be validated against experimental measurements. Hence, there is a crucial need for data for advanced reactor systems that will support validation of analysis methods. To this end, this Research Topic includes eleven papers organized into topical seven categories relevant for advanced reactor design.
At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (10 13 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (10 18 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.
We present high-contrast Magellan adaptive optics images of HD 7449, a Sun-like star with one planet and a long-term radial velocity (RV) trend. We unambiguously detect the source of the long-term trend from 0.6–2.15 μm at a separation of ∼0.″54. We use the object’s colors and spectral energy distribution to show that it is most likely an M4–M5 dwarf (mass ∼0.1–0.2 M{sub ⊙}) at the same distance as the primary and is therefore likely bound. We also present new RVs measured with the Magellan/MIKE and Planet Finder Spectrograph spectrometers and compile these with archival data from CORALIE and HARPS. We use a new Markov chain Monte Carlo procedure to constrain both the mass (>0.17 M{sub ⊙} at 99% confidence) and semimajor axis (∼18 AU) of the M dwarf companion (HD 7449B). We also refine the parameters of the known massive planet (HD 7449Ab), finding that its minimum mass is 1.09{sub −0.19}{sup +0.52} M{sub J}, its semimajor axis is 2.33{sub −0.02}{sup +0.01} AU, and its eccentricity is 0.8{sub −0.06}{sup +0.08}. We use N-body simulations to constrain the eccentricity of HD 7449B to ≲0.5. The M dwarf may be inducing Kozai oscillations on the planet, explaining its high eccentricity. If this is the case and its orbit was initially circular, the mass of the planet would need to be ≲1.5 M{sub J}. This demonstrates that strong constraints on known planets can be made using direct observations of otherwise undetectable long-period companions.
A new generation of dedicated Doppler spectrographs will attempt to detect low-mass exoplanets around mid- to late M stars at near-infrared (NIR) wavelengths, where those stars are brightest and have the most Doppler information content. A central requirement for the success of these instruments is to properly measure the component of radial velocity (RV) variability contributed by stellar magnetic activity and to account for it in exoplanet models of RV data. The wavelength coverage for many of these new instruments will not include the Ca ii H and K or H α lines, the most frequently used absorption-line tracers of magnetic activity. Thus, it is necessary to define and characterize NIR activity indicators for mid- to late M stars in order to provide simultaneous activity metrics for NIR RV data. We have used the high-cadence UVES observations of the M5.5 dwarf Proxima Centauri from Fuhrmeister et al. to compare the activity sensitivity of eight NIR atomic lines to that of H α . We find that equivalent-width-type measurements of the NIR K i doublet and the Ca ii NIR triplet are excellent proxies for the canonical optical tracers. The Ca ii triplet will be acquired by most of the new and upcoming NIR Doppler spectrographs, offering a common, reliable indicator of activity.
We present 2.9–4.1 μm integral field spectroscopy of the L4+L4 brown dwarf binary HD 130948BC, obtained with the Arizona Lenslets for Exoplanet Spectroscopy (ALES) mode of the Large Binocular Telescope Interferometer. The HD 130948 system is a hierarchical triple system, in which the G2V primary is joined by two co-orbiting brown dwarfs. By combining the age of the system with the dynamical masses and luminosities of the substellar companions, we can test evolutionary models of cool brown dwarfs and extrasolar giant planets. Previous near-infrared studies suggest a disagreement between HD 130948BC luminosities and those derived from evolutionary models. We obtained spatially resolved, low-resolution (R ∼ 20) L-band spectra of HD 130948B and C to extend the wavelength coverage into the thermal infrared. Jointly using JHK photometry and ALES L-band spectra for HD 130948BC, we derive atmospheric parameters that are consistent with parameters derived from evolutionary models. We leverage the consistency of these atmospheric quantities to favor a younger age (0.50 ± 0.07 Gyr) of the system compared to the older age (0.79{sub −0.15}{sup +0.22} Gyr) determined with gyrochronology in order to address the luminosity discrepancy.