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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Notes on Tapered Active Array Antenna Performance

Modern Active Electronically Steerable Array (AESA) antennas offer substantial control over transmit and receive antenna beam forming, including via elemental weighting to achieve a desired tapered aperture. However, these tapers also have the adverse side effect of diminishing total transmitted power and/or raising the system noise figure. This is readily calculated, and must be considered for overall radar performance prediction. Independent tapers for transmit and receive arrays might be play.

42 ENGINEERING↗
DOE OSTI2025

MCNP® Code Version 6.3.1 Release Notes

The Monte Carlo N-Particle® (MCNP® ) code is a general-purpose, continuous-energy, generalized-geometry, time-dependent, radiation transport code developed by the MCNP development team. MCNP calculations provide predictive capabilities that can replace expensive or impossible-to-perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.1, follows the MCNP6.3.0 version. Since the release of MCNP6.3.0, a variety of bug fixes and code enhancements have been completed for MCNP6.3.1. A few new features have also been added to this release to support both ongoing research and the release of the latest ENDF/B-VIII.1 nuclear data library. The MCNP code, version 6.3.1, theory and user input information is documented in MCNP® Code Version 6.3.1 Theory & User Manual, the build guidance for various platforms is documented in MCNP® Code Version 6.3.1 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP® Code Version 6.3.1 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

U.S. Efforts in Support of Examinations at Fukushima Daiichi - September 2024 Meeting Notes

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. Commercial nuclear power plants. A collaborative U.S. and Japanese effort was initiated in 2014 by the Department of Energy Office of Nuclear Energy to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This document summarizes information presented at and findings, action items, and recommendations by U.S. and Japanese experts in reactor safety and plant operations during the September 2024 Forensics Effort meeting. Significant safety insights were obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties and knowledge gaps in severe accident modeling progression, these insights continue to be used to assess whether additional updates are needed in guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional safety and economic benefits to the operating fleet and new light water reactor (LWR) and non-LWR designs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Notes on Bayliss Taper for Monopulse Radar

A radar system’s antenna characteristics are fundamental to its performance. A principal defining feature of an antenna’s performance are its often problematic sidelobes. Often in monopulse antenna topologies, the emphasis has been on the sum channel sidelobes at the expense of difference channel sidelobes. Edward Bayliss published a paper detailing a design procedure for managing the difference channel sidelobes. The resulting aperture taper now is identified by his name. This report analyzes his taper derivation, and resulting performance attributes, after which some implementation comments are rendered.

42 ENGINEERING↗
DOE OSTI2025

Xyce™ Parallel Electronic Simulator Version 7.10 Release Notes

The Xyce™ Parallel Electronic Simulator has been written to support the simulation needs of Sandia National Laboratories’ electrical designers. Xyce™ is a SPICE-compatible simulator with the ability to solve extremely large circuit problems on large-scale parallel computing platforms, but also includes support for most popular parallel and serial computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Watchmen v2.5.2 Release Notes

This document describes the changes to Watchmen. This includes improvements to stability and the importation of station data from non-standard #RASAData block to standard #ProcessSensor block.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Watchmen v3.1.0 Release Notes

This document describes the changes to Watchmen. This includes improvements to stability, search features, display of more detailed sample information and user access via authentication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Watchmen v3.2.0 Release Notes

This document describes the changes to Watchmen. This includes improvements to stability, search features, display of more detailed sample information and user access via authentication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Watchmen 3.3.0 Release Notes

This document describes the changes to Watchmen. This includes improvements to stability, search features, display of more detailed sample information and user access via authentication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

EAMxx 3.25 km Western Pacific RRM Technical Note

The Western Pacific Convection-Permitting (CP) Regionally Refined Model (RRM) used for 2023 Jingjinji Flood event is developed based on the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0 (Fortran code) under the United States (U.S) Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) project (Caldwell et al., 2021) and the regionally refined model (RRM) configuration (Tang et al., 2019, 2023; Zhang et al., 2024; Bogenschutz et al., 2024).

58 GEOSCIENCES↗
DOE OSTI2026

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2025 Meeting Notes

Fifteen years have passed since the March 11, 2011, the Great East Japan Earthquake (GEJE) triggered a tsunami that inundated the Fukushima Daiichi Nuclear Power Station (Daiichi or 1F) and led to severe accidents in multiple units at the plant. During these fifteen years since these events, Daiichi forensics examinations and evaluations have revealed many insights for enhancing the safety of nuclear power plants worldwide. However, uncertainties remain regarding the events after the GEJE. Additional Daiichi forensics information is required to inform future Decontamination and Decommissioning (D&D) activi- ties conducted by the plant owner, Tokyo Electric Power Company Holdings, Incorporated (TEPCO Hold- ings). This forensics information also has important implications for the safety and operation of U.S. commercial nuclear power plants. A collaborative U.S. and Japanese effort, which includes approximately 50 experts in reactor safety and plant operations, was initiated in 2014 by the Department of Energy Office of Nuclear Energy (U.S. DOE-NE) to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This collaborative effort, which is beneficial to the U.S. and Japan, continues as Japan moves forward with D&D activities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Notes on Array Antenna Phase Center

The location of an antenna, and indeed the radar system it serves, is typically presumed to be its phase center. This is the point from which a far-field apparent spherical wavefront seems to be centered. Even when a true phase center doesn’t exist, an ‘apparent’ phase center can still be calculated for the neighborhood of some direction of interest, often the mainlobe of the beam. Such calculations are especially necessary for non-symmetric arrays, or sub-arrays.

42 ENGINEERING↗
DOE OSTI2026

Notes on Complex (Including Phase-Only) Tapered Active Array Antenna Performance

Modern Active Electronically Steerable Array (AESA) antennas offer substantial control over transmit and receive antenna beam forming, including via elemental weighting to achieve a desired tapered aperture. Elemental taper weighting may generally be complex, with both amplitude and phase components. This includes phase-only tapers. However, array tapers may also have the adverse side effect of diminishing transmit and/or receive effectiveness. This is readily calculated, and must be ...

Doerry, Armin Walter [Sandia National Laboratories↗
DOE OSTI2022

A Note on the Effects of Linear Topology Preservation in Monte Carlo Simulations of Knotted Proteins

Monte Carlo simulations are a powerful technique and are widely used in different fields. When applied to complex molecular systems with long chains, such as those in synthetic polymers and proteins, they have the advantage of providing a fast and computationally efficient way to sample equilibrium ensembles and calculate thermodynamic and structural properties under desired conditions. Conformational Monte Carlo techniques employ a move set to perform the transitions in the simulation Markov chain. While accepted conformations must preserve the sequential bonding of the protein chain model and excluded volume among its units, the moves themselves may take the chain across itself. We call this a break in linear topology preservation. In this manuscript, we show, using simple protein models, that there is no difference in equilibrium properties calculated with a move set that preserves linear topology and one that does not. However, for complex structures, such as those of deeply knotted proteins, the preservation of linear topology provides correct equilibrium results but only after long relaxation. In any case, to analyze folding pathways, knotting mechanisms and folding kinetics, the preservation of linear topology may be an unavoidable requirement.

Especial, João N. C. (ORCID:0000000254765370)↗
DOE OSTI2020

Technical note: Deep learning for creating surrogate models of precipitation in Earth system models

Abstract. We investigate techniques for using deep neural networks to produce surrogatemodels for short-term climate forecasts. A convolutional neural network istrained on 97 years of monthly precipitation output from the 1pctCO2 run (theCO 2 concentration increases by 1 % per year) simulated by the second-generation Canadian Earth System Model (CanESM2). The neural network clearly outperforms a persistence forecast anddoes not show substantially degraded performance even when the forecast lengthis extended to 120 months. The model is prone to underpredicting precipitationin areas characterized by intense precipitation events. Scheduled sampling(forcing the model to gradually use its own past predictions rather than groundtruth) is essential for avoiding amplification of early forecasting errors.However, the use of scheduled sampling also necessitates preforecasting(generating forecasts prior to the first forecast date) to obtain adequateperformance for the first few prediction time steps. We document the trainingprocedures and hyperparameter optimization process for researchers who wish toextend the use of neural networks in developing surrogate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Technical note: Uncertainties in eddy covariance CO 2 fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches

Abstract. Gap-filling eddy covariance CO2 fluxes is challenging at dryland sites due to small CO2 fluxes. Here, four machine learning (ML) algorithms including artificial neural network (ANN), k-nearest neighbors (KNNs), random forest (RF), and support vector machine (SVM) are employed and evaluated for gap-filling CO2 fluxes over a semiarid sagebrush ecosystem with different lengths of artificial gaps. The ANN and RF algorithms outperform the KNN and SVM in filling gaps ranging from hours to days, with the RF being more time efficient than the ANN. Performances of the ANN and RF are largely degraded for extremely long gaps of 2 months. In addition, our results suggest that there is no need to fill the daytime and nighttime net ecosystem exchange (NEE) gaps separately when using the ANN and RF. With the ANN and RF, the gap-filling-induced uncertainties in the annual NEE at this site are estimated to be within 16 g C m−2, whereas the uncertainties by the KNN and SVM can be as large as 27 g C m−2. To better fill extremely long gaps of a few months, we test a two-layer gap-filling framework based on the RF. With this framework, the model performance is improved significantly, especially for the nighttime data. Therefore, this approach provides an alternative in filling extremely long gaps to characterize annual carbon budgets and interannual variability in dryland ecosystems.

Yao, Jingyu↗
DOE OSTI2025

Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

Abstract. The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

54 ENVIRONMENTAL SCIENCES↗