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At least 433 records · Page 24

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DOE OSTI2021

Deep Learning for Ensemble Forecasting

Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components and the use of AI and other tools to design a prediction system comprising a hierarchy of models. Science Challenge: While both climate and weather forecast systems have continued to improve due to substantial efforts to improve computational capabilities, observations, and numerical models, the atmosphere is a chaotic system, and this puts a fundamental limit on our ability to make predictions. Forecasts made by high-resolution models initialized with only slightly different atmospheric states can quickly diverge. Quantifying uncertainty in forecasts is essential to adequately understand them and to make the best-informed policy decisions particularly when it comes to hydrology, extreme weather (including extreme precipitation events), and climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Evidence of Completion of Milestone 3: Experimental Testbed

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

FERMI (Q1 Project Report: May-June 2021): LLNL Contribution (short version)

This work delineates the work accomplished in the 2nd quarter of CY 2021, which consists of the first quarter of funding for LLNL in the FERMI project (Fusion Energy Reactors Modeling Initiative), a project of the GAMOW (Galvanizing Advances in Market-Aligned Fusion for an Overabundance of Watts) program under ARPA-E. LLNL is responsible for the structural mechanics component of FERMI, concentrating on fusion first wall and blankets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Concurrency Supply Chain Optimization (Final Report)

Brunswick is experiencing unprecedented volume for engines and fully produced boats. Supply Chain (parts) has difficulty accurately forecasting demand needs which presents problems in the manufacturing process. Streamline ordering process enabling the Brunswick Boat Group (BBG) to more efficiently forecast part demand for the Mercury Engine Group by setting up an AI/ML model. Initial focus will be 15 SKUs with inaccurate demand forecasting based on current manual processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Evidence of Completion of Milestone 3: Experimental Testbed

Construction and deployment of the experimental testbed encountered scheduling delays, and completion was subsequently further delayed by curtailment of LANL operations due to the COVID-19 pandemic. Between March and October, LANL was in a state of “Limited Operations” such that only certain “mission-critical” work was performed with approximately 25% on-site staffing. In spite of this, much of the lab space preparation was executed and the five initial model house” units were constructed and installed during this period. Still, the pace of construction was impacted by difficulty in coordinating personnel and minimizing contact between workers. Currently, LANL is in the mode of “Normal Operations with Maximum Telework,” which continues to limit the availability of on-site personnel. Nevertheless, Milestone 3 is now complete. This document describes the experiment as it is deployed and provides status for each task for this milestone.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Advancements on Multi-Fidelity Random Fourier Neural Networks: Application to Hurricane Modeling for Wind Energy

Multi-fidelity approaches are emerging as effective strategies in computational science to handle otherwise intractable tasks like Uncertainty Quantification (UQ), training of Machine Learning (ML) models, and optimization, for expensive high-fidelity applications in which the amount of available simulations or data is limited. The main idea is simple: large datasets generated for low-fidelity approximations of the problem at hand are fused with a much sparser dataset for the target (high-fidelity) system. In this paper, we build on our recent success in designing random Fourier Neural Networks (rFNNs) [1] to target problems arising in wind energy applications and in particular problems of interest for hurricane modeling. In this context, data for the high-fidelity models are limited and lower fidelity alternatives are needed. In this work, we introduce a novel multi-fidelity training approach for our rFNNs and demonstrate its use on a simple verification problem and on a hurricane modeling problem in which high-fidelity data are generated via Large-Eddy Simulations (LES), while low-fidelity data are given by a mesoscale model. Initial results demonstrate how the multi-fidelity training approach can improve the quality of the resulting surrogate.

Fourier Neural Networks↗

DOE OSTI2020

Dynamic Topology Reconfiguration of Boltzmann Machines on Quantum Annealers

Boltzmann machines have useful roles in deep learning applications, such as generative data modeling, initializing weights for other types of networks, or extracting efficient representations from high-dimensional data. Most Boltzmann machines use restricted topologies that exclude looping connectivity, as such connectivity creates complex distributions that are difficult to sample. We have used an open-system quantum annealer to sample from complex distributions and implement Boltzmann machines with looping connectivity. Further, we have created policies mapping Boltzmann machine variables to the quantum bits of an annealer. These policies, based on correlation and entropy metrics, dynamically reconfigure the topology of Boltzmann machines during training and improve performance.

Liu, Jeremy (ORCID:0000000172299417)↗

DOE OSTI2025

Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Synchronous Rotation in the (136199) Eris–Dysnomia System

We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1σ formal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with the P = 15.785 90 ± 0.00005 day sidereal period of Dysnomia's orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris's brightness with respect to illumination phase averaged across g, V, and r bands, intermediate between Pluto's and Charon's values. Variations of 0.3 mag are detected in Dysnomia's brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Subgrid-scale horizontal and vertical variation of cloud water in stratocumulus clouds: a case study based on LES and comparisons with in situ observations

Abstract. Stratocumulus clouds in the marine boundary layer cover a large fraction of ocean surface and play an important role in the radiative energy balance of the Earth system. Simulating these clouds in Earth system models (ESMs) has proven to be extremely challenging, in part because cloud microphysical processes such as the autoconversion of cloud water into precipitation occur at scales much smaller than typical ESM grid sizes. An accurate autoconversion parameterization needs to account for not only the local microphysical process (e.g., the dependence on cloud water content qc and cloud droplet number concentration Nc) but also the subgrid-scale variability of the cloud properties that determine the process rate. Accounting for subgrid-scale variability is often achieved by the introduction of a so-called enhancement factor E. Previous studies of E for autoconversion have focused more on its dependence on cloud regime and ESM grid size, but they have largely overlooked the vertical dependence of E within the cloud. In this study, we use a large-eddy simulation (LES) model, initialized and constrained with in situ and surface-based measurements from a recent airborne field campaign, to characterize the vertical dependence of the horizontal variation of qc in stratocumulus clouds and the implications for E. Similar to our recent observational study (Zhang et al., 2021), we found that the inverse relative variance of qc, an index of horizontal homogeneity, generally increases from cloud base upward through the lower two-thirds of the cloud and then decreases in the uppermost one-third of the cloud. As a result, E decreases from cloud base upward and then increases towards the cloud top. We apply a decomposition analysis to the LES cloud water field to understand the relative roles of the mean and variances of qc in determining the vertical dependence of E. Our analysis reveals that the vertical dependence of the horizontal qc variability and enhancement factor E is a combined result of condensational growth throughout the lower portion of the cloud and entrainment mixing at cloud top. The findings of this study indicate that a vertically dependent E should be used in ESM autoconversion parameterizations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗

NASA NTRS1976

Research on regional numerical weather prediction

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

Kreitzberg, C. W.↗

NASA NTRS1977

On probing the outer planets with the Raman effect

The paper examines the feasibility of using the H2 rotational Raman spectrum to study the physical structure of the atmospheres of the outer planets. Computations of the strengths of the S(0) and S(1) lines are made for a wide range of physical conditions on the basis of a semi-infinite homogeneous pure H2 atmospheric model. Initial applications of the Raman probe technique to Jupiter and Uranus are reported.

Price, M. J.↗

NASA NTRS1979

How tidal heating in Io drives the Galilean orbital resonance locks

The mechanisms by which orbital resonance locks are maintained among Io, Europa and Ganymede are analyzed, and the effects of the dissipative tides in Jupiter and Io on their establishment and evolution are considered. According to the proposed model, initially all three satellites are in orbits far from the 2:1 commensurabilities or the three body lock. The tide raised on Io damps down the free eccentricity; only modest tidal heating occurs. Subsequently the dissipative tide raised on Jupiter by Io causes Io's orbit to spiral outwards; Io approaches the 2:1 commensurability with Europa. Io's forced eccentricity increases rapidly to a critical value, and thereafter the resonant interaction causes Europa's orbit to expand at half that of Io's orbit. A fluid core is probably formed as the result of tidal heating. Finally Europa approaches the 2:1 commensurability, angular momentum is transferred from Europa's orbit to Ganymede's, and a steady state is attained. On the basis of the observed three-body resonance amplitude (0.066 deg), it is concluded that three-body resonance may have formed less than 500 million years ago; a measurement of the rate of tidal heating in Io may determine the Q value of both Io and Jupiter. Upper and lower limits for the Jovian Q value of 2 million and 20,000 are suggested.

Yoder, C. F.↗

NASA NTRS1981

Requirements and preliminary design for a general purpose real-time executive for flight computers

The requirements and preliminary design of a general purpose, real-time executive computers program for flight computers are provided. A description and the requirements are included for the major elements of the executive: an initialization model, a task scheduler, and an interrupt handler. Task priorities and various process interrupts are discussed. System parameters and variables are identified which make the design adaptable to various flight computer and applicaton specifications.

Smith, K. A.↗

NASA NTRS1983

Symmetric linear systems

Employment as a means of transportation in the civilian construction trades represents one of the many applications of the helicopter. However, a major limitation to its use in heavy construction has been that the mass which can be effectively and safely transported is severely restricted. The construction of the so-called 'heavy lift' helicopter provided one solution to this problem. But it has been found that there are physical and economic limitations to the payload which can be transported. The proposal has been made to overcome these limitations by making use of multiple helicopters to move a single mass. A study of the feasibility of this proposal showed that automatic control would be needed to make the concept successful. The present investigation is concerned with some initial models in regard to the twinlift problem, taking into account the control theoretic problems.

Lewis, J.↗

NASA NTRS1984

Impact phenomena as factors in the evolution of the Earth

It is estimated that 30 to 200 large impact basins could have been formed on the early Earth. These large impacts may have resulted in extensive volcanism and enhanced endogenic geologic activity over large areas. Initial modelling of the thermal and subsidence history of large terrestrial basins indicates that they created geologic and thermal anomalies which lasted for geologically significant times. The role of large-scale impact in the biological evolution of the Earth has been highlighted by the discovery of siderophile anomalies at the Cretaceous-Tertiary boundary and associated with North American microtektites. Although in neither case has an associated crater been identified, the observations are consistent with the deposition of projectile-contaminated high-speed ejecta from major impact events. Consideration of impact processes reveals a number of mechanisms by which large-scale impact may induce extinctions.

Grieve, R. A. F.↗

NASA NTRS1984

The problem of iron partition between Earth and Moon during simultaneous formation as a double planet system

A planetary model is described which requires fractional vapor/liquid condensation, planet accumulation during condensation, a late start for accumulation of the Moon, and volatile accretion to the surfaces of each planet only near the end of the accumulation process. In the model, initial accumulation of small objects is helped if the agglomerating particles are somewhat sticky. Assuming that growth proceeds through this range, agglomeration continues. If the reservoir of vapor is being preferentially depleted in iron by fractional condensation, an iron-rich planetary core forms. As the temperature decreases, condensing material becomes progressively richer in silicates and poorer in iron, forming the silicate-rich mantle of an already differentiated Earth. A second center of agglomeration successfully forms near the growing Earth after most of the iron in the reservoir has been used up. The bulk composition of the Moon then is similar to the outer mantle of the accumulating Earth.

Cassidy, W. A.↗