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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 OSTI2020

Determining the ballistic threshold velocity for a composite structure using multiple failure models

A composite structure, such as a laminated composite panel, for example, comprises one or more layers or “plies” embedded in a matrix material or otherwise fixed together in an arrangement, commonly referred to as a “stack up.” Each material in the structure has a corresponding material failure model (MFM) defining the physical characteristics of that material. A ballistic threshold velocity computing device obtains the MFMs for each material in the composite structure, generates a predicted ballistic velocity threshold velocity for each MFM, and then generates a parametric model to compute a composite ballistic velocity threshold velocity for the composite structure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice

Searches for new phenomena in complex scientific data are predominantly model-dependent, optimized for specific hypotheses, and therefore limited in their coverage of the space of possible signals. Recently, new AI-based model-agnostic search strategies, many of which have been pioneered in high-energy physics, have been proposed which provide a complementary paradigm, prioritizing broad exploration over tailored analyses. These techniques offer an opportunity to enhance the overall discovery potential of modern experiments, especially in regimes where theoretical guidance is scarce. In this document, we review the conceptual framework behind the main classes of AI-based model-agnostic strategies. We discuss the potential pitfalls of these methods, and strategies for their validation and interpretation. We aim for this document to serve as a useful reference both for practitioners and for researchers interested in learning more about these model-agnostic search strategies.

Amram, Oz [Fermilab] (ORCID:0000000237653123)↗
DOE OSTI2013

Maps of CMB lensing deflection from N-body simulations in Coupled Dark Energy Cosmologies

We produce lensing potential and deflection-angle maps in order to simulate the weak gravitational lensing of the Cosmic Microwave Background (CMB) via ray-tracing through the COupled Dark Energy Cosmological Simulations (CoDECS), the largest suite of N-body simulations to date for interacting Dark Energy cosmologies. The constructed maps faithfully reflect the N-body cosmic structures on a range of scales going from the arcminute to the degree scale, limited only by the resolution and extension of the simulations. We investigate the variation of the lensing pattern due to the underlying Dark Energy (DE) dynamics, characterised by different background and perturbation behaviours as a consequence of the interaction between the DE field and Cold Dark Matter (CDM). In particular, we study in detail the results from three cosmological models differing in the background and perturbations evolution at the epoch in which the lensing cross section is most effective, corresponding to a redshift of ∼ 1, with the purpose to isolate their imprints in the lensing observables, regardless of the compatibility of these models with present constraints. The scenarios investigated here include a reference ΛCDM cosmology, a standard coupled DE (cDE) scenario, and a ''bouncing'' cDE scenario. For the standard cDE scenario, we find that typical differences in the lensing potential result from two effects: the enhanced growth of linear CDM density fluctuations with respect to the ΛCDM case, and the modified nonlinear dynamics of collapsed structures induced by the DE-CDM interaction. As a consequence, CMB lensing highlights the DE impact in the cosmological expansion, even in the degenerate case where the amplitude of the linear matter density perturbations, parametrised through σ{sub 8}, is the same in both the standard cDE and ΛCDM cosmologies. For the ''bouncing'' scenario, we find that the two opposite behaviours of the lens density contrast and of the matter abundance lead to a counter-intuitive effect, making the power of the lensing signal in this model lower by 10% than in the ΛCDM scenario. Moreover, we compare the behaviour of CDM and baryons in CoDECS separately, in order to isolate effects coming from the coupling with the DE component. We find that, in the bouncing scenario, baryons show an opposite trend with respect to CDM, due to the coupling of the latter with the DE component. These results confirm the relevance of CMB lensing as a probe for DE at the early stages of cosmic acceleration, and demonstrate the reliability of N-body based large scale CMB lensing simulations in the context of DE studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Transient thermal analysis for radioactive liquid mixing operations in a large-scaled tank

A transient heat balance model was developed to assess the impact of a Submersible Mixer Pump (SMP) on radioactive liquid temperature during the process of waste mixing and removal for the high-level radioactive materials stored in Savannah River Site (SRS) tanks. The model results will be mainly used to determine the SMP design impacts on the waste tank temperature during operations and to develop a specification for a new SMP design to replace existing longshaft mixer pumps used during waste removal. The present model was benchmarked against the test data obtained by the tank measurement to examine the quantitative thermal response of the tank and to establish the reference conditions of the operating variables under no SMP operation. The results showed that the model predictions agreed with the test data of the waste temperatures within about 10%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Improving constraints on models addressing the Hubble tension with CMB delensing

The Hubble Tension is a well-known issue in modern cosmology that refers to the apparent disagreement in inferences of the Hubble constant H 0 as found through low-redshift observations and those derived from the ΛCDM model utilizing early universe observations. Several extensions to ΛCDM have been proposed to address the Hubble Tension that involve new ingredients or dynamics in the early universe. Reversing the effects of gravitational lensing on cosmic microwave background (CMB) maps produces sharper acoustic peaks in power spectra and allows for tighter constraints on cosmological parameters. We investigate the efficacy of CMB delensing for improving the constraints on parameters used in extensions of the ΛCDM model that are aimed at resolving the Hubble Tension (such as varying fundamental constants, contributions from early dark energy, and self-interacting dark radiation). We use Fisher forecasting to predict the expected constraints with and without this delensing procedure. We demonstrate that CMB delensing improves constraints on H 0 by ~ 20% for viable models and significantly improves constraints on parameters across the board in the low-noise regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operated in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

End-Use Savings Shapes Upgrade Package Documentation: LED Lighting, HP-RTU and ASHP-Boiler

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models over the past 3 years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) upgrade measures, or upgrades. "Measures" refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility upgrade applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology and results of the baseline model are discussed in the final technical report of the End-Use Load Profiles project. This documentation focuses on an upgrade package of three end-use savings shapes upgrades - Light Emitting Diode (LED) Lighting, Heat Pump Rooftop Unit (RTU) (HP-RTU), and Air-Source Heat Pump (ASHP) Boiler, which we will refer to collectively as the "Interior Lighting and Heat Pump" package. More details on the individual upgrades can be found on the ComStock Measures Documentation page. An upgrade package applies two or more EUSS upgrades to a single building model simulation. Since ComStock is a bottom-up physics-based model, an upgrade package will go beyond aggregating or summing the individual upgrade results and produce novel results by simulating interactions between the upgrades. For example, pairing an envelope upgrade with an electrification upgrade would likely result in higher savings results than the sum of these upgrades individually, and the size of the heating, ventilating, and air conditioning (HVAC) equipment may be reduced if the envelope upgrade reduces the loads significantly.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

A DISK-BASED DYNAMICAL MASS ESTIMATE FOR THE YOUNG BINARY V4046 Sgr

We present sensitive, arcsecond-resolution Submillimeter Array observations of the {sup 12}CO J = 2-1 line emission from the circumstellar disk orbiting the double-lined spectroscopic binary star V4046 Sgr. Based on a simple model of the disk structure, we use a novel Monte Carlo Markov Chain technique to extract the Keplerian velocity field of the disk from these data and estimate the total mass of the central binary. Assuming the distance inferred from kinematic parallax measurements in the literature (d Almost-Equal-To 73 pc), we determine a total stellar mass M {sub *} = 1.75{sup +0.09} {sub -0.06} M {sub Sun} and a disk inclination i{sub d} = 33.{sup 0}5{sup +0.7} {sub -1.4} from face-on. These measurements are in excellent agreement with independent dynamical constraints made from multi-epoch monitoring of the stellar radial velocities, confirming the absolute accuracy of this precise ({approx}few percent uncertainties) disk-based method for estimating stellar masses and reaffirming previous assertions that the disk and binary orbital planes are well aligned (with |i{sub d} - i {sub *}| Almost-Equal-To 0.{sup 0}1 {+-} 1 Degree-Sign ). Using these results as a reference, we demonstrate that various pre-main-sequence evolution models make consistent and accurate predictions for the masses of the individual components of the binary, and uniformly imply an advanced age of {approx}5-30 Myr. Taken together, these results verify that V4046 Sgr is one of the precious few nearby and relatively evolved pre-main-sequence systems that still hosts a gas-rich accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Shear viscosity coefficient of liquid lanthanides

Present paper deals with the computation of shear viscosity coefficient (η) of liquid lanthanides. The effective pair potential v(r) is calculated through our newly constructed model potential. The Pair distribution function g(r) is calculated from PYHS reference system. To see the influence of local field correction function, Hartree (H), Tailor (T) and Sarkar et al (S) local field correction function are used. Present results are compared with available experimental as well as theoretical data. Lastly, we found that our newly constructed model potential successfully explains the shear viscosity coefficient (η) of liquid lanthanides.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Characterization of the Uranium-Bearing Products of the Ammonia Injection Remediation Method - 15707

Commissioned in 1943, the Hanford Site is the home of the world's first full-scale nuclear production facility. After more than 40 years of processing, improper discharge and failed storage tanks have resulted in the contamination of the Hanford vadose zone with radiologically contaminated waste. Remediation methods considered for the area include sequestration of the mobile uranium by injection of ammonia (NH{sub 3}) gas. Injection of this reactive gas increases the pore water pH, promoting the dissolution of soil minerals; a subsequent re-establishment of natural conditions is believed to result in the recrystallization of those soil minerals and the co-precipitation of uranium phases. Characterization of the precipitates formed when the ammonia (NH{sub 3}) injection method, proposed for the Hanford vadose zone, is applied to synthetic pore water on a laboratory scale. This involves: Identification of the uranium-bearing phases; A study of the effect of pore water constitution on the phases produced. Synthetic pore water solutions were prepared to mimic selected constituents of the pore water from the Hanford 200 Area: Varying constituent concentrations; Observations led to modifications to increase relative uranium content: 200 ppm → 500 ppm U; Substituted sodium silicate for silicic acid. Dried samples were analyzed by SEM-EDS and powder X-ray diffraction (XRD). A suspension in ethanol was prepared and analyzed by Transmission Electron Microscope (TEM) with Selective Area Electron Diffraction (SAED). Studied and applied geochemical modeling software (Visual Minteq and Geo-chemist's Workbench) for speciation and prediction of potential species formed. Discussion/Conclusions: - SEM-EDS Analysis: Scanning electron microscopy revealed areas of high average atomic weight which would be confirmed to be uranium-rich by energy dispersive spectroscopy analysis. The samples prepared with a more than two-fold increase in uranium concentration did not show the crystal-like forms spotted in the lower [U] samples. The samples prepared with silicic acid substituted in showed little to no uranium precipitation [not shown]. - Diffraction Analysis: Powder XRD analysis of the low [U] samples confirmed the presence of repeating crystalline patterns in the precipitate samples. Nitratine (NaNO{sub 3}) showed a massive presence, potentially obscuring significant peaks in the low [U] samples. Though it was not predicted, there was a tentative match for cejkaite (Na{sub 4}(UO{sub 2})(CO{sub 3}){sub 3}). Elevated uranium samples showed none of the needle-like crystalline shapes [diffraction data pending]. TEM - SAED confirmed the presence of a polycrystalline phase. Data analysis is complex but a comparison of average d-spacings with those of reference minerals could further support a match with cejkaite. - Geochemical Modeling: The system conditions were input into geochemical modeling software to predict the forms present throughout the reaction process. The model was used to demonstrate that the pH of the system could be increased using [NH{sub 4}{sup +}] in solution to better represent the system. Using the [NH{sub 4}{sup +}] increase, the changes in significant species with increasing pH were observed. Future Work: Repeat samples will be prepared and analyzed to bolster any potential identification. Promising samples will be submitted to the PNNL's EMSL facility, which is better equipped to perform the required analyses. An expanded study on the impact of carbonate (CO{sub 3}{sup 2-}) on the phases produced.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer

The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer biopsy specimens. After completing the pilot study, we found notable variability in the sTILs estimates as well as inconsistencies and gaps in the provided training to pathologists. Using the pilot study data and an expert panel, we created custom training materials to improve pathologist annotation quality for the pivotal study. We categorized regions of interest (ROIs) based on their mean sTILs density and selected ROIs with the highest and lowest sTILs variability. In a series of eight one-hour sessions, the expert panel reviewed each ROI and provided verbal density estimates and comments on features that confounded the sTILs evaluation. We aggregated and shaped the comments to identify pitfalls and instructions to improve our training materials. From these selected ROIs, we created a training set and proficiency test set to improve pathologist training with the goal to improve data collection for the pivotal study. We are not exploring AI/ML performance in this paper. Instead, we are creating materials that will train crowd-sourced pathologists to be the reference standard in a pivotal study to create an AI/ML model validation dataset. The issues discussed here are also important for clinicians to understand about the evaluation of sTILs in clinical practice and can provide insight to developers of AI/ML models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

MELCOR Code Change History (Revision 14959 to 18019)

This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 14959and 18019. Revision 14959 represents the previous official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 18019. Along with the newly updated MELCOR Users Guide and Reference Manual, users are aware and able to assess the new capabilities for their modeling and analysis applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no systematic evaluation exists of how well vision-language models (VLMs) interpret them. We introduce QCalEval, the first VLM benchmark for quantum calibration plots: 243 samples across 87 scenario types from 22 experiment families, spanning superconducting qubits and neutral atoms, evaluated on six question types in both zero-shot and in-context learning settings. The best general-purpose zero-shot model reaches a mean score of 72.3, and many open-weight models degrade under multi-image in-context learning, whereas frontier closed models improve substantially. A supervised fine-tuning ablation at the 9-billion-parameter scale shows that SFT improves zero-shot performance but cannot close the multimodal in-context learning gap. As a reference case study, we release NVIDIA Ising Calibration 1, an open-weight model based on Qwen3.5-35B-A3B that reaches 74.7 zero-shot average score.

Cao, Shuxiang↗
DOE OSTI2020

A long short-term memory embedding for hybrid uplifted reduced order models

In this paper, we introduce an uplifted reduced order modeling (UROM) approach through the integration of standard projection based methods with long short-term memory (LSTM) embedding. Our approach has three modeling layers or components. In the first layer, we utilize an intrusive projection approach to model dynamics represented by the largest modes. The second layer consists of an LSTM model to account for residuals beyond this truncation. This closure layer refers to the process of including the residual effect of the discarded modes into the dynamics of the largest scales. However, the feasibility of generating a low rank approximation tails off for higher Kolmogorov n -width systems due to the underlying nonlinear processes. The third uplifting layer, called super-resolution, addresses this limited representation issue by expanding the span into a larger number of modes utilizing the versatility of LSTM. Therefore, our model integrates a physics-based projection model with a memory embedded LSTM closure and an LSTM based super-resolution model. In several applications, we exploit the use of Grassmann manifold to construct UROM for unseen conditions. We performed numerical experiments by using the Burgers and Navier-Stokes equations with quadratic nonlinearity. Finally, our results show robustness of the proposed approach in building reduced order models for parameterized systems and confirm the improved trade-off between accuracy and efficiency.

42 ENGINEERING↗
DOE OSTI2023

Schematic model for induced fission in a configuration-interaction approach

We model fission at barrier-top energies in a simplified model space that permits comparison of different components of the residual nucleon-nucleon interaction. The model space is built on particle-hole excitations of reference configurations. These are Slater determinants of uniformly spaced orbitals characterized only by their quantum numbers and orbital energies. The residual interaction in the Hamiltonian includes the diabatic interaction connecting similar orbitals at different deformations, the pairing interaction between like nucleons, and a schematic off-diagonal neutron-proton interaction. We find that the fission reaction probability is sensitive to the off-diagonal neutron-proton interaction much more than to the pairing and the diabatic interactions. In particular, the transmission coefficients become insensitive to the strength of the pairing interaction when the neutron-proton interaction is large. Here, we also find that the branching ratio is insensitive to the final-state scission dynamics, as is assumed in the well-known Bohr-Wheeler theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Communication: Orientational self-ordering of spin-labeled cholesterol analogs in lipid bilayers in diluted conditions

Lipid-cholesterol interactions are responsible for different properties of biological membranes including those determining formation in the membrane of spatial inhomogeneities (lipid rafts). To get new information on these interactions, electron spin echo (ESE) spectroscopy, which is a pulsed version of electron paramagnetic resonance (EPR), was applied to study 3β-doxyl-5α-cholestane (DCh), a spin-labeled analog of cholesterol, in phospholipid bilayer consisted of equimolecular mixture of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and 1,2-dioleoyl-sn-glycero-3-phosphocholine. DCh concentration in the bilayer was between 0.1 mol.% and 4 mol.%. For comparison, a reference system containing a spin-labeled 5-doxyl-stearic acid (5-DSA) instead of DCh was studied as well. The effects of “instantaneous diffusion” in ESE decay and in echo-detected (ED) EPR spectra were explored for both systems. The reference system showed good agreement with the theoretical prediction for the model of spin labels of randomly distributed orientations, but the DCh system demonstrated remarkably smaller effects. The results were explained by assuming that neighboring DCh molecules are oriented in a correlative way. However, this correlation does not imply the formation of clusters of cholesterol molecules, because conventional continuous wave EPR spectra did not show the typical broadening due to aggregation of spin labels and the observed ESE decay was not faster than in the reference system. So the obtained data evidence that cholesterol molecules at low concentrations in biological membranes can interact via large distances of several nanometers which results in their orientational self-ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A hybridizable discontinuous Galerkin method for modeling fluid–structure interaction

This study presents a novel application of the hybridizable discontinuous Galerkin (HDG) finite element method to the multi-physics simulation of coupled fluid–structure interaction (FSI) problems. Recent applications of the HDG method have primarily been for single-physics problems including both solids and fluids, which are necessary building blocks for FSI modeling. Utilizing these established models, HDG formulations for linear elastostatics, a nonlinear elastodynamic model, and arbitrary Lagrangian–Eulerian Navier–Stokes are derived. The elasticity formulations are written in a Lagrangian reference frame, with the nonlinear formulation restricted to hyperelastic materials. With these individual solid and fluid formulations, the remaining challenge in FSI modeling is coupling together their disparate mathematics on the fluid–solid interface. This coupling is presented, along with the resultant HDG FSI formulation. Verification of the component models, through the method of manufactured solutions, is performed and each model is shown to converge at the expected rate. The individual components, along with the complete FSI model, are then compared to the benchmark problems proposed by Turek and Hron [1]. The solutions from the HDG formulation presented in this work trend towards the benchmark as the spatial polynomial order and the temporal order of integration are increased.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗