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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations

The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.

Bogenschutz, Peter A. [Lawrence Livermore National↗
DOE OSTI2024

Investigating Mechanisms Driving Differences in the Characteristics of Precipitation in the E3SM Multiscale Modeling Framework With 2D Versus 3D Cloud Resolving Model Configurations

Abstract In this study, we compare the Energy Exascale Earth Systems Model (E3SM) multiscale modeling framework (MMF) with the cloud resolving model (CRM) configured in two (2dMMF) and three (3dMMF) dimensions. We explore how CRM dimensionality impacts the representation of mean and extreme precipitation characteristics. Our results show that tropical mean precipitation patterns are better represented in 3dMMF compared to observations (Integrated Multi‐satellitE Retrivals for GPM and Global Precipitation Climatology Project One Degree Daily products), while 2dMMF better captures extreme precipitation intensity, with systematic land‐ocean differences in precipitation and cloud‐associated variables. These differences are attributed to the co‐occurrence of CRM throttling (i.e., suppressed convection in due to smaller numbers of CRM columns and domain size) and dilution (i.e., 3‐D cloud circulations with increased entrainment and lower precipitation efficiency) effects. Overall, throttling results in more low‐level humidity in 2dMMF and dilution contributes to more high clouds with less precipitation efficiency in 3dMMF. Since throttling occurs more strongly over the ocean than land, the 3dMMF tends to have less cloud liquid and precipitation over the ocean and more cloud ice and precipitation over land. These results may serve as a guide for choosing the CRM structure to reduce precipitation and cloud‐related biases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Forecasting and modeling of the COVID-19 pandemic in the USA with a timed intervention model

We propose a novel Timed Intervention S, P, E, I, Q, R, D model for projecting the possible futures of the COVID-19 pandemic in the USA. The proposed model introduces a series of timed interventions that can account for the influence of real time changes in government policy and social norms. We consider three separate types of interventions: (i) Protective interventions: Where population moves from susceptible to protected corresponding to mask mandates, stay-at-home orders and/or social distancing. (ii) Release interventions: Where population moves from protected to susceptible corresponding to social distancing mandates and practices being lifted by policy or pandemic fatigue. (iii) Vaccination interventions: Where population moves from susceptible, protected, and exposed to recovered (meaning immune) corresponding to the mass immunization of the U.S. Population. By treating the pandemic with timed interventions, we are able to model the pandemic extremely effectively, as well as directly predicting the course of the pandemic under differing sets of intervention schedules. We show that without prompt effective protective/vaccination interventions the pandemic will be extended significantly and result in many millions of deaths in the U.S.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Novel Partitioned Approach for Reduced Order Model—Finite Element Model (ROM-FEM) and ROM-ROM Coupling

Partitioned methods allow one to build a simulation capability for coupled problems by reusing existing single-component codes. In so doing, partitioned methods can shorten code development and validation times for multiphysics and multiscale applications. In this work, we consider a scenario in which one or more of the “codes” being coupled are projection-based reduced order models (ROMs), introduced to lower the computational cost associated with a particular component. We simulate this scenario by considering a model interface problem that is discretized independently on two non-overlapping subdomains. Here we then formulate a partitioned scheme for this problem that allows the coupling between a ROM “code” for one of the subdomains with a finite element model (FEM) or ROM “code” for the other subdomain. The ROM “codes” are constructed by performing proper orthogonal decomposition (POD) on a snapshot ensemble to obtain a low-dimensional reduced order basis, followed by a Galerkin projection onto this basis. The ROM and/or FEM “codes” on each subdomain are then coupled using a Lagrange multiplier representing the interface flux. To partition the resulting monolithic problem, we first eliminate the flux through a dual Schur complement. Application of an explicit time integration scheme to the transformed monolithic problem decouples the subdomain equations, allowing their independent solution for the next time step. We show numerical results that demonstrate the proposed method’s efficacy in achieving both ROM-FEM and ROM-ROM coupling.

de Castro, Amy↗
DOE OSTI2021

Particle-in-cell Monte Carlo-collision modeling of non-ideal effects in wave-heated dense microplasmas

A computational model for non-ideal plasma effects during the time evolution of a second-stage laser-heated discharge at high pressures is presented. The model extends a classical one-dimensional particle-in-cell Monte Carlo-collision (PIC-MCC) approach coupled with Maxwell's equations for the laser-heating process of a xenon plasma at 300 K temperature and 10–100 bar pressure. Plasma non-ideality resulting from Coulomb coupling at high plasma densities is manifested as a depression in the effective ionization potential of atoms and enhanced collision cross sections. These non-ideal effects are represented using the Ecker–Kröll model in the context of the PIC-MCC approach. We find that full ionization of the plasma is obtained on the picosecond timescale, starting from the skin layer and quickly expanding throughout the domain through an anomalous extension of the skin depth. More critically, we show that the inclusion of the non-ideal plasma effects results in more rapid ionization compared to an ideal plasma, especially at higher pressures. The ionization delay reduction is of the order of a fraction of a picosecond, corresponding to a 16% decrease at 100 bar. As the amplitude of the wave field is lowered, the ionization rate is lowered, making the plasma non-ideality effects more prominent.

Solmaz, Evrim (ORCID:0000000211830881)↗
DOE OSTI2021

Exact solution of two simple non-equilibrium electron-phonon and electron-electron coupled systems: The atomic limit of the Holstein-Hubbard model and the generalized Hatsugai-Komoto model

One of the challenges in many-body physics is determining the effects of phonons on strongly correlated electrons. The difficulty arises from strong correlations at differing energy scales—for band metals, Migdal-Eliashberg theory accurately determines electron-phonon coupling effects due to the absence of vertex corrections, but strongly correlated electrons require a more complex description, and the standard Migdal-Eliashberg approach does not necessarily apply. In this work, we solve for the atomic limit Green's function of the Holstein-Hubbard model with both time-dependent electron-electron and electron-phonon couplings. Then, we examine the photoemission spectra of this model in and out of equilibrium. Next, we use similar methods to exactly solve an extended version of the Hatsugai-Komoto model and examine its behavior in and out of equilibrium. These calculations lead us to propose using the first moment of the photoemission spectra to signal non-equilibrium changes in electron-electron and electron-phonon couplings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Model-Independent Determination of Nuclear Weak Form Factors and Implications for Standard Model Precision Tests

We analyze the recoil corrections in superallowed beta decays of T = 1, J P = 0 + nuclei by fixing the mean square charged weak radius model independently using the data of multiple charge radii across the nuclear isotriplet. By comparing to model estimations, we argue that the existing theory uncertainty in the statistical rate function f might have been substantially underestimated. Here, we discuss the implications of our proposed strategy for precision tests of the standard model, including a potential alleviation of the first-row CKM unitarity deficit, and motivate new experiments for charge radii measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Advancing Dynamic Modeling of Grid-Connected PV Inverter Using Bi-LSTM-Based AI Model

Power electronic converters (PECs) are widely used in modern power systems to facilitate the interconnection between various AC or DC sources and loads. Because of the extensive integration, the power system has grown into a more dynamic system in which the dynamics of the PECs must be adequately modeled. The paper presents a new bidirectional long short-term memory (Bi-LSTM) method for evaluating grid-connected inverter-based resources (IBR) dynamics. The method is tested using real hardware data from a grid -connected commercial inverter in laboratory experiments. Results show the Bi-LSTM model accurately reproduces the detailed IBR model's dynamics, even when the internal structure is unknown and parameters are unknown, preventing the disclosure of the manufacturer's confidential data.

Subedi, Sunil [ORNL] (ORCID:000000034069090X)↗
DOE OSTI2024

Data-driven Modeling for Grid Edge IBRs: A Digital Twin Perspective of User-Defined Models

Recent events in Odessa have brought attention to the challenges associated with the interaction between Inverter- Based Resources (IBRs) and the transmission and distribution system. The NERC event diagnosis report has highlighted sev- eral issues, emphasizing the need for continuous performance monitoring of these IBRs by system operators. Key areas of concern include the mismatch of control and protection perfor- mance of IBRs between the original equipment manufacturer (OEM)-provided models and field measurements. The inability to replicate the realistic response can result in incorrect reliability and resilience studies. In this paper, we developed an approach on how to emulate the behavior of an IBR using measurement data obtained for system operators to utilize in real-time and long- term planning. Two experiments are conducted in the phasor domain and electromagnetic transients (EMT) domain to emulate the behavior for grid forming and grid following inverters under various operating conditions and the effectiveness of the proposed model is demonstrated in terms of accuracy and ease of utilizing user-defined models (UDMs)

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2022

Modeling of Supercritical CO2 Shell-and-Tube Heat Exchangers Under Extreme Conditions: Part II: Heat Exchanger Model

Abstract Heat exchangers play a critical role in supercritical CO2 Brayton cycles by providing necessary waste heat recovery. Supercritical CO2 thermal cycles potentially achieve higher energy density and thermal efficiency operating at elevated temperatures and pressures. Accurate and computationally efficient estimation of heat exchanger performance metrics at these conditions is important for the design and optimization of sCO2 systems and thermal cycles. In this paper (Part II), a computationally efficient and accurate numerical model is developed to predict the performance of shell-and-tube heat exchangers (STHXs). Highly accurate correlations reported in Part I of this study are utilized to improve the accuracy of performance predictions, and the concept of volume averaging is used to abstract the geometry and reduce computation time. The numerical model is validated by comparison with computational fluid dynamics (CFD) simulations and provides high accuracy and significantly lower computation time compared to existing numerical models. A preliminary optimization study is conducted and the advantage of using supercritical CO2 as a working fluid for energy systems is demonstrated.

Engineering↗
DOE OSTI2020

A constitutive model for sheared dense suspensions of rough particles

In a concentrated suspension, particles come into contact due to the presence of asperities on their surfaces. As a result, the contact forces and interparticle friction become one of the important factors governing the rheology of rigid particle suspensions at high concentrations. We show that a load-dependent friction model can be used to reproduce the experimentally observed shear thickening [ST—continuous and discontinuous (DST)] behavior with an increase in the asperity size. Increasing the particle surface roughness size leads to a decrease in the critical shear rate above which shear-thickening takes place, a reduction in the critical volume fraction for DST and an increase in the viscosity jump across non-shear-thickened to shear-thickened regime. In this paper, we propose a constitutive model to quantify the effect of increasing the roughness size on the rheology of dense ST suspensions as well as on the critical shear rate for ST and the critical volume fraction for DST. We fit this model to our simulation data for stress controlled shear flow of dense rough particle suspensions. Once the fitting is complete, these equations are used to predict exact volume fractions and shear stress values for transitions between three regimes on the shear stress-shear rate flow state diagram for different roughness values. Furthermore, the results of this study can be used to tune the particle surface roughness for manipulating the dense suspension rheology according to different applications.

42 ENGINEERING↗
DOE OSTI2020

SD-pair shell model: Vibrational and rotational limits in the interacting boson–fermion model for like-nucleon system

Typical features of the Bose–Fermi symmetries associated with [Formula: see text] and [Formula: see text] limits in the interacting boson model are described in the SD-pair shell model (SDPSM) framework for like-nucleon system. It is found that the limiting spectra associated with [Formula: see text] (vibrational) and [Formula: see text] (rotational) in the interacting boson–fermion model can be well reproduced in the SDPSM framework. It is shown that coupling of collective degree of freedom with the single-particle degree of freedom in the pairing interaction almost has no effect on the spectrum of odd-A system comparing to the adjacent even–even system, while the coupling of the collective degree of freedom with the single-particle degree of freedom in the quadrupole–quadrupole interaction results in the level splitting of several excited levels.

Physics↗
DOE OSTI2021

Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response

Motivation: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems such as protein complexes, metabolic reactions, and signal transduction pathways. Hypergraphs are generalizations of graphs that naturally model multi-way interactions in data, and we therefore seek to understand how they can more faithfully identify, and potentially predict, complex relationships in genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges are differentially expressed genes and vertices represent conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Our results demonstrate the utility of using hypergraphs to represent complex biological systems, and highlight potentially interesting biological results about host response to highly pathogenic viruses.

systems biology, hypergraph, viral infection, biol↗
DOE OSTI2024

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Abstract Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive

This archive contains the data and Python scripts required to reproduce the analyses and figures in the study: Gomez-Velez, J. D., Rathore, S. S., Cohen, M. J., & Painter, S. L. (2025). Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model. Submitted to Water Resources Research. The analysis utilizes the subgrid model Advection Dispersion Equation with Lagrangian Subgrids (ADELS) implemented in the Advanced Terrestrial Simulator (ATS; https://amanzi.github.io/ats/stable/). In this case, the ATS and Amanzi versions are (1) ATS version 1.5.1_f5ba18f8 and (2) Amanzi version 1.6-dev_53444cca4. The repository includes a Jupyter Notebook and the necessary data (Pandas DataFrames stored as pickle files) to generate the figures for the manuscript. Additionally, it contains Python scripts to create ATS input files, run the ATS simulations, and post-process the results. Finally, it provides routines for parameter estimation using the Single-Station Metabolism (SSM) model with the Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm with ZS enhancements (DREAM-ZS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

MCNP modelling of the Thermo SPA3 with Tungsten (Rees model) collimator

A Thermo Model SPA3 2”x2” NaI probe fitted with a Tungsten collimator has been modelled using MCNP6. The collimator was assumed to be machinable Tungsten which typically includes Ni and Fe. Various ratios of these additives are used in industry and for the purposes of these calculations the collimator was assumed to contain 7% Ni and 3% Fe with a density of 17.0 g/cm 3 . The dimensions of the collimator were based on measurements taken by Mike Fanning. The above detector model was used, in a manner similar to the approach described in LA-UR-19-32358, to calculate photopeak count rates per unit activity per unit area (i.e. cpm per pCi/cm 2 ) conversion factors for various contamination scenarios.

61 RADIATION PROTECTION AND DOSIMETRY↗