SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
SAND2022-6990 O MPI Partix is an application suite to test user-level threading (ULT) and partitioned communication in MPI. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. The package includes an intuitive "experiment" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.
The Offshore CO2 Saline Storage Calculator is a data-driven tool that applies the adapted DOE CO2 Methodology to calculate all potential distributions of offshore storage efficiency and resource potential at multiple spatial scales for saline formations. The tailored methodology include accounting for changing CO2 density with the overlying water column and sediment differences in unlithified, porous, and permeable offshore saline formations. The latest release of the tool and a tutorial are available in the tools public GitHub repository. We recommend testing out this application using data from the Petrophysical Well Log Interpretation Dataset, which spans the northern Gulf of Mexico and is available on EDX here: https://edx.netl.doe.gov/dataset/petrophysical-well-log-interpretation-dataset
(U) Single Feature Testbeds to Reduce Uncertainty in Simulations and Tests [3] provided an overview for the need of experiments, with accompanying models and simulations, specifically designed to reduce uncertainties and build confidence in complex testing and analysis applications. The Contact Thermal Conductance (CTC) testbed is a joint effort between W-13 (formerly E-13) and MST-8. The objective of this study was to design a testbed, with accompanying finite element models, to quantify, reduce, and propagate measurement uncertainties in contact thermal conductance measurements between two mating components in WR-like thermal environments. The knowledge gained through this simplified experiment would educate more complex assessments and interaction conditions with WR-like materials and geometries.
As part of the Department of Energy response to the novel coronavirus disease (COVID-19) pandemic of 2020, a modeling effort was sponsored by the DOE Office of Science. Through this effort, an integrated planning framework was developed whose capabilities were demonstrated with the combination of a treatment resource demand model and an optimization model for routing supplies. This report documents this framework and models, and an application involving ventilator demands and supplies in the continental United States. The goal of this application is to test the feasibility of implementing nationwide ventilator sharing in response to the COVID-19 crisis. Multiple scenarios were run using different combinations of forecasted and observed patient streams, and it is demonstrated that using a "worst-case forecast for planning may be preferable to best mitigate supply-demand risks in an uncertain future. There is also a brief discussion of model uncertainty and its implications for the results.
In many dynamic systems, interesting events occur locally in time and space. Examples of such systems include ignition events in combustion simulations, material fractures in mechanics simulations, and extreme weather events in climate simulations. Due to memory constraints and data I/O costs, current simulation workflows save data at regularly spaced time-steps, at a fixed rate determined before the start of the simulation. Often this mode of operation results in missed events of interest, necessitating a simulation restart from before an event occurred with more frequent data saves. This data saving workflow is grossly inefficient and is already a bottleneck in the computing process. We propose to develop machine learning algorithms that can detect when interesting dynamical events are occurring, triggering data saves. These machine learning algorithms will perform in situ anomaly detection to flag regions with different dynamical properties than those previously recorded. The adaptive data saves would be local in time and space to match the event of interest, thereby enabling a much more efficient workflow that will reduce data I/O costs and data storage memory requirements. The algorithms will be tested on two applications: auto-ignition simulations and climate simulations. A critical component of this project will be developing machine learning algorithms that can be deployed efficiently in situ on HPC platforms with out-of-the-box functionality. The development of in situ machine learning methods to detect anomalous events would enable a more efficient and effective workflow, in which all the relevant data are saved in a single simulation run, without re-starts or scientist intervention.
We need to expand the variety of applications to rigorously test libraries. Advanced reactors: – Decreasing reactivity for 8.1b2 compared to 8.0, some unexpected nuclides causing major differences (F-19, Cr), no clear performance difference when compared to experiment. Depletion RCA: – High impact isotopes closer to 7.1 – Small improvement on average (U-5, Pu-9, BC FPs), worse for Am and Cm. Fuel reactivity: – 8.1b2 is higher reactivity at high burnups than 8.0, but likely under predicting k eff for PWRs at high burnup.
The development and innovation of floating offshore wind energy in the U.S. requires detailed high-fidelity observations and measurements of turbine and platform loading due to wind, waves, and currents. However, full-scale and quasi-full-scale experiments require significant financial and temporal investments for construction, experimental testing, and long-term field campaigns. To support the commercial advancement of the offshore wind energy industry, specialized wind tunnel and wave basin experimental facilities are critical to be able to test FOWT designs at small scale under controlled conditions prior to full-scale deployment. Oregon State University (OSU) is internationally known as a leader in water and energy research, development, and testing. The O.H. Hinsdale Wave Research Laboratory (HWRL) and the Wallace Energy Systems and Renewables Facility (WESRF) at OSU have extensive experience building, modeling, monitoring, controlling, and actuating scaled systems. Experiments on wave-structure interaction have been performed at the HWRL since its establishment in 1972. Studies have included the interaction of waves with coastal structures (breakwaters, seawalls, buildings, cylinders, bridges, fixed foundations of offshore wind turbines, etc.) and with floating structures (e.g., wave energy converters, maneuvering of vessels, etc.). Hinsdale is actively used by marine energy technology developers, both for private testing and OSU-collaborative research projects. However, despite the availability of several large-scale facilities for hydrodynamic testing (at OSU and elsewhere in the U.S.), existing experimental laboratories are generally limited in their ability to accurately generate combined wind and wave conditions. The simulation of both wind and waves in experimental testing is complicated due to a number of constraints, including: [i] incompatible similitude laws governing the wind and waves for scaled experiments, [ii] producing accurate wind over a large enough control volume via fans, and [iii] generating wind that reasonably represents the atmospheric boundary layer in existing wave basins/flumes. Hence, physical test data providing insight into the simultaneous wave- and wind-structure response of floating offshore wind components can be difficult to generate. Given the aforementioned challenges in classic hydrodynamic experiments, the motivation of this project is to establish a real-time hybrid simulation (RTHS) approach that can apply aero- and hydro-dynamic loading by augmenting wave-only experimental facilities with virtual aerodynamic forces through numerical models representing the remaining dynamic forces. RTHS is a physical-numerical approach that partitions a prototype system into physical and numerical sub-assemblies that interact with each other through actuators and sensors in real time. In coupling physical and numerical models, the hybrid simulation approach applied herein is ideal for problems with: (1) structures subjected to different scaling laws, such as floating offshore wind turbines subjected to combined aero/hydro-dynamic loading, (2) structures that are too large or complex to be tested entirely in a laboratory setting, such as deep-water mooring applications, and (3) component testing, where the behavior of a portion of the assembly is uncertain but still interacts with other portions of the structure, such as testing the fatigue life of turbine blades. Few U.S. experimental facilities are able to test simultaneous aero- and hydro-dynamic loading and none can accurately produce aero/hydro-dynamic response on scaled FOWT models due to conflicting similitude laws between the wind (commonly Reynolds) and the waves (commonly Froude). To aid in accelerating the development of the U.S. floating offshore industry, there is a significant need to develop a flexible, modular framework that can expand the capacities of existing wave-only laboratories. The project goal is to demonstrate a hydrodynamic real-time hybrid simulation (hydro-RTHS) framework that couples numerical wind and physical waves acting on a FOWT, thus representing simultaneous aero/hydro-dynamic loading. The FOWT is partitioned into a full-scale numerical sub-assembly associated with the aerodynamics and a model-scale physical sub-assembly associated with the hydrodynamics. The numerical-physical partition associated with hydro-RTHS mitigates scaling constraints by supplying different scaling laws to the physical and numerical sub-assemblies. Herein, length, force, and time are scaled and exchanged between the sub-assemblies using Froude scaling to represent the open-channel flow in the physical sub-assembly. Other similitude laws could also be utilized depending on the problem definition. It is envisioned that the ability to model FOWTs under waves and wind, with mitigation of similitude distortions, would result in reduced development costs (currently, FOWT concept development is performed with full-size pro- totypes at enormous expense and risk) and increase the reliability of the FOWT industry (since extreme wave and wind conditions and contingency events can be tested safely in a controlled environment).
The High Field Vertical Magnet Test Facility (HFVMTF) at Fermilab is designed to test superconducting magnets up to 20 tons and 1.3 meters in diameter. Central to the facility is a double-bath superfluid helium cryostat reaching 1.8 K at 1.2 bar. Integrated with a 15 T superconducting dipole from LBNL, HFVMTF supports HTS cable testing for fusion applications. This paper presents the design and fabrication of the cryostat, with a focus on two complex components: the 2 K heat exchanger and the lambda plate. The heat exchanger thermally links sub-atmospheric and pressurized helium baths. The 1.4-meter lambda plate provides thermal isolation and structural support for over 20 tons under 1.3 bar pressure differential. Finite Element Analysis validated the vessel’s integrity under maximum load conditions.
In the summer of 2025, I was fortunate enough intern at Sandia National Laboratories in Albuquerque, New Mexico. I was hired into the Southwest Analysis Laboratories for Semiconductor Advancement (SALSA) intern program. In this internship, I applied my knowledge and skills in electrical engineering to conduct hardware failure analysis. I utilized various failure analyze techniques involving the use of Infrared Thermography (IRT) and Laser Scanning Microscopy (LSM) to test different Application-Specific Integrated Circuits (ASIC) chips that are available in the public market.
Excess phosphorus (P) in wastewater effluent poses a serious threat to aquatic ecosystems and can spur harmful algal blooms. Revolving algal biofilm (RAB) systems are an emerging technology to recover P from wastewater before discharge into aquatic ecosystems. In RAB systems, a community of microalgae take up and store wastewater P as polyphosphate as they grow in a partially submerged revolving biofilm, which may then be harvested and dried for use as fertilizer in lieu of mined phosphate rock. In this work, we isolated and characterized a total of 101 microalgae strains from active RAB systems across the US Midwest, including 82 green algae, 9 diatoms, and 10 cyanobacteria. Strains were identified by microscopy and 16S/18S ribosomal DNA sequencing, cryopreserved, and screened for elevated P content (as polyphosphate). Seven isolated strains possessed at least 50% more polyphosphate by cell dry weight than a microalgae consortium from a RAB system, with the top strain accumulating nearly threefold more polyphosphate. These top P-hyperaccumulating strains include the green alga Chlamydomonas pulvinata TCF-48 g and the diatoms Eolimna minima TCF-3d and Craticula molestiformis TCF-8d, possessing 11.4, 12.7, and 14.0% polyphosphate by cell dry weight, respectively. As a preliminary test of strain application for recovering P, Chlamydomonas pulvinata TCF-48 g was reinoculated into a bench-scale RAB system containing Bold basal medium. The strain successfully recolonized the system and recovered twofold more P from the medium than a microalgae consortium from a RAB system treating municipal wastewater. These isolated P-hyperaccumulating microalgae may have broad applications in resource recovery from various waste streams, including improving P removal from wastewater.
We present Galaxy Line Emission & Absorption Modeling (gleam), a Python tool for fitting Gaussian models to emission and absorption lines in large samples of 1D extragalactic spectra. gleam is tailored to work well in batch mode without much human interaction. With gleam, users can uniformly process a variety of spectra, including galaxies and active galactic nuclei, in a wide range of instrument setups and signal-to-noise regimes. gleam also takes advantage of multiprocessing capabilities to process spectra in parallel. With the goal of enabling reproducible workflows for its users, gleam employs a small number of input files, including a central, user-friendly configuration in which fitting constraints can be defined for groups of spectra and overrides can be specified for edge cases. For each spectrum, gleam produces a table containing measurements and error bars for the detected spectral lines and continuum and upper limits for nondetections. For visual inspection and publishing, gleam can also produce plots of the data with fitted lines overlaid. In the present paper, we describe gleam’s main features, the necessary inputs, expected outputs, and some example applications, including thorough tests on a large sample of optical/infrared multi-object spectroscopic observations and integral field spectroscopic data. gleam is developed as an open-source project hosted at https://github.com/multiwavelength/gleam and welcomes community contributions.
Magnetic fields (B-fields) are ubiquitous in the interstellar medium (ISM), and they play an essential role in the formation of molecular clouds and subsequent star formation. However, B-fields in interstellar environments remain challenging to measure, and their properties typically need to be inferred from dust polarization observations over multiple physical scales. In this work, we seek to use a recently proposed approach called the velocity gradient technique (VGT) to study B-fields in star-forming regions and compare the results with dust polarization observations in different wavelengths. The VGT is based on the anisotropic properties of eddies in magnetized turbulence to derive B-field properties in the ISM. We investigate that this technique is synergistic with dust polarimetry when applied to a turbulent diffused medium for the purpose of measuring its magnetization. Specifically, we use the VGT on molecular line data toward the NGC 1333 star-forming region ( 12 CO, 13 CO, C 18 O, and N 2 H + ), and we compare the derived B-field properties with those inferred from 214 and 850 μm dust polarization observations of the region using Stratospheric Observatory for Infrared Astronomy/High-Resolution Airborne Wide-band Camera Plus and James Clerk Maxwell Telescope/POL-2, respectively. We estimate both the inclination angle and the 3D Alfvénic Mach number M A from the molecular line gradients. Crucially, testing this technique on gravitationally bound, dynamic, and turbulent regions, and comparing the results with those obtained from polarization observations at different wavelengths, such as the plane-of-sky field orientation, is an important test on the applicability of the VGT in various density regimes of the ISM. We in general do not find a close correlation between the velocity gradient inferred orientations and the dust inferred magnetic field orientations.
The High Field Vertical Magnet Test Facility (HFVMTF) at Fermilab is designed to test superconducting magnets up to 20 tons and 1.3 meters in diameter. Central to the facility is a double-bath superfluid helium cryostat reaching 1.8 K at 1.2 bar. Integrated with a 15 T superconducting dipole from LBNL, HFVMTF supports HTS cable testing for fusion applications. This paper presents the design and fabrication of the cryostat, with a focus on two complex components: the 2 K heat exchanger and the lambda plate. The heat exchanger thermally links sub-atmospheric and pressurized helium baths. The 1.4-meter lambda plate provides thermal isolation and structural support for over 20 tons under 1.3 bar pressure differential. Finite Element Analysis validated the vessel's integrity under maximum load conditions.
Due to the nature of Helium, it is notoriously difficult to maintain a closed system without experiencing helium inventory loss through leakage in large tubing and piping runs. There are two standard fitting options readily available for piping and tubing assemblies, welded fittings or Swagelok ® . Welding is the best option for leak rate reduction, but more costly than Swagelok ® . A new style of fitting has come to the attention of BNL C-AD Cryo group, and a pressure test and leak rate analysis were performed to evaluate the viability of incorporating this new style fitting into current engineering design of warm helium tubing runs for the purpose of leak rate reduction.
Abstract. Due to its complexity, gas- and particle-phase organic carbon in the atmosphere is often classified by its bulk physicochemical properties. However, there is a dearth of robust, moderate-cost approaches to measure the bulk chemical composition of organic carbon in the atmosphere. This is particularly true for the degree of oxygenation, which critically affects the properties and impacts of organic carbon but for which routine measurement approaches are lacking. This gap has limited the understanding of a wide range of atmospheric components, including particulate matter, the mass of which is monitored worldwide due to its health and environmental effects but the chemical characterization of which requires relatively high capital costs and complex operation by highly trained technical personnel. In this work, we demonstrate a new approach to estimate the mass of carbon and oxygen in analytes and mixtures that relies only on robust, moderate-cost detectors designed for use with gas chromatography. Organic compounds entering a flame ionization detector were found to be converted with approximately complete efficiency to CO2, which was analyzed downstream using an infrared detector to measure the mass of carbon analyzed. The ratio of the flame ionization detector (FID) signal generated to CO2 formed (FID∕CO2) was shown to be strongly correlated (R2=0.89) to the oxygen-to-carbon ratio (O∕C) of the analyte. Furthermore, simple mixtures of analytes behaved as the weighted average of their components, indicating that this correlation extends to mixtures. These properties were also observed to correlate well with the sensitivity of the FID estimated by structure activity relationships (quantified as the relative effective carbon number). The relationships between measured FID∕CO2, analyte O∕C, and FID sensitivity allow the estimation of one property from another with <15 % error for mixtures and <20 % error for most individual analytes. The approach opens the possibility of field-deployable, autonomous measurement of the carbon and oxygen content of particulate matter using time-tested, low-maintenance detectors, though such an application would require some additional testing on complex mixtures. With some instrumental modifications, similar measurements on gas-phase species may be feasible. Moreover, the potential expansion to additional gas chromatography detectors may provide concurrent measurement of other elements (e.g., sulfur, nitrogen).
Fuel fragmentation, relocation, and dispersal are some of the largest issues remaining in the nuclear industry before rod-average burnup can be increased beyond 62 GWd/tU. The issue is primarily related to the potential for fuel to be dispersed into the reactor primary system, which may increase public risk. One way to prevent dispersal is to avoid cladding burst. The objective of this work is to support the high burnup safety case by evaluating cladding burst under high-burnup, full-length fuel rods and to identify uncertainties that could improve model predictions. The results of this analysis will evaluate realistic, prototypic loss-of-coolant accident (LOCA) conditions; support future cladding burst test designs; and inform the development of mechanistic material models. Realistic high-burnup operating conditions were implemented in the BISON fuel performance code to simulate steady-state and LOCA transient fuel rod evolution to the point at which cladding burst occurred. Parametric studies are performed to assess code response to changes in rod internal pressures and heating rates. Results were compared with simulated LOCA experiments to identify inconsistencies between commercial fuel rod analysis and experimental validation. The representative full-length fuel rod LOCA simulation results did not agree with cladding burst tests. Cladding burst tests indicated burst occurring well below (100–150 °C) those calculated in the full-length fuel rod LOCA analysis. Further investigation indicated that the cladding burst tests do not appear to be representative for full-length fuel rods. The inconsistency investigated in this work showed that the differences between the BISON simulation and the experiment's cladding burst conditions arise from an incomplete characterization of the cladding surface temperature, detailed rodlet characterization, lack of cladding strain measurements, and uncertainty in the cladding creep and failure models.
This paper describes a desktop application designed to introduce users to unclassified information for the series of nuclear experiments conducted by the United States, colloquially referred to within the nuclear weapons design community as simply, the “Test History.” The application facilitates simple browsing (by name, by date, and MMDD date code), and more complex analyses based on user-defiend relational database queries.