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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dataset for SIAM MPI23 Project "Model inversion for complex physical systems using low-dimensional surrogates"

Training and testing data for the SIAM MPI23 workshop "Model inversion for complex physical systems using low-dimensional surrogates". The data consists of ensembles of input and output pairs corresponding to queries of a 2D saturated groundwater flow model. The inputs consist of random vectors which map to discretized model parameter fields via a Kosambi-Karhunen-Loève expansion. Output corresponds to discretized pressure fields.

basis adaptation, conditional Karhunen-Loève expan↗
DOE OSTI2024

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Phase Field Simulations of Microstructure Evolution in IN718 using a Surrogate Ni–Fe–Nb Alloy during Laser Powder Bed Fusion

The solidification microstructure in IN718 during additive manufacturing was modeled using phase field simulations. The novelty of the research includes the use of a surrogate Ni–Fe–Nb alloy that has the same equilibrium solidification range as IN718 as the model system for phase field simulations, the integration of the model alloy thermodynamics with the phase field simulations, and the use of high-performance computing tools to perform the simulations with a high enough spatial resolution for realistically capturing the dendrite morphology and the level of microsegregation seen under additive manufacturing conditions. Heat transfer and fluid flow models were used to compute the steady state temperature gradient and an average value of the solid-liquid (s-l) interface velocity that were used as input for the phase field simulations. The simulations show that the solidification morphology is sensitive to the spacing between the columnar structures. Spacing narrower than a critical value results in continued growth of a columnar microstructure, while above a critical value the columnar structure evolves into a columnar dendritic structure through the formation of secondary arms. These results are discussed in terms of the existing columnar to dendritic transition (CDT) theories. The measured interdendritic Nb concentration, the primary and secondary arm spacing is in reasonable agreement with experimental measurements performed on the nickel-base superalloy IN718.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Quantitative Analysis of Fission-Product Surrogates in Molten Salt Chloride Aerosols

This work demonstrates laser-induced breakdown spectroscopy (LIBS) applied to a stream of aerosolized salt from molten eutectic LiCl-KCl. We demonstrate analytical capabilities to track fission-product surrogates of Cs, Sr, Pr, and Nd simultaneously, with application to monitor salts in pyroprocessing schemes and molten salt reactors. This work demonstrates limits of detection using LIBS on the order of 100 μg/g, which proves potentially applicable to monitoring fission-product concentrations in pyroprocessing applications. Additionally, this work explores fundamental aspects of plasma temperature and plasma electron density of the aerosolized species during LIBS with a specific focus on potential non-uniform plasma conditions in the aerosol.

74 - ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

MMMnet: A Neural Network Surrogate for Real-Time Transport Prediction Based on the Updated Multi-Mode Model

The Multi-Mode Model (MMM) is a physics-based anomalous transport model integrated into TRANSP for predicting electron and ion thermal transport, electron and impurity particle transport, and toroidal and poloidal momentum transport. While MMM provides valuable predictive capabilities, its computational cost, although manageable for standard simulations, is too high for real-time control applications. MMMnet, a neural network-based surrogate model, is developed to address this challenge by significantly reducing computation time while maintaining high accuracy. Trained on TRANSP simulations of DIII-D discharges, MMMnet incorporates an updated version of MMM (9.0.10) with enhanced physics, including isotopic effects, plasma shaping via effective magnetic shear, unified correlation lengths for ion-scale modes, and a new physics-based model for the electromagnetic electron temperature gradient mode. A key advancement is MMMnet’s ability to predict all six transport coefficients, providing a comprehensive representation of plasma transport dynamics. MMMnet achieves a two-order-of-magnitude speed improvement while maintaining strong correlation with MMM diffusivities, making it well-suited for real-time tokamak control and scenario optimization.

DIII-D↗
DOE OSTI2017

The {sup 95}Zr( n , γ ){sup 96}Zr Cross Section from the Surrogate Ratio Method and Its Effect on s -process Nucleosynthesis

The {sup 95}Zr( n , γ ){sup 96}Zr reaction cross section is crucial in the modeling of s -process nucleosynthesis in asymptotic giant branch stars because it controls the operation of the branching point at the unstable {sup 95}Zr and the subsequent production of {sup 96}Zr. We have carried out the measurement of the {sup 94}Zr({sup 18}O, {sup 16}O) and {sup 90}Zr({sup 18}O, {sup 16}O) reactions and obtained the γ -decay probability ratio of {sup 96}Zr* and {sup 92}Zr* to determine the {sup 95}Zr( n , γ ){sup 96}Zr reaction cross sections with the surrogate ratio method. Our deduced Maxwellian-averaged cross section of 66 ± 16 mb at 30 keV is close to the value recommended by Bao et al., but 30% and more than a factor of two larger than the values proposed by Toukan and Käppeler and Lugaro et al., respectively, and routinely used in s -process models. We tested the new rate in stellar models with masses between 2 and 6 M {sub ⊙} and metallicities of 0.014 and 0.03. The largest changes—up to 80% variations in {sup 96}Zr—are seen in models of mass 3–4 M {sub ⊙}, where the {sup 22}Ne neutron source is mildly activated. The new rate can still provide a match to data from meteoritic stardust silicon carbide grains, provided that the maximum mass of the parent stars is below 4 M {sub ⊙}, for a metallicity of 0.03.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Surrogate Modeling of Landau Damping with Deep Operator Networks

Kinetic simulations excel at capturing microscale plasma physics phenomena with high accuracy, but their computational demands make them impractical for modeling large-scale space and astrophysical systems. In this context, we build a surrogate model, using Deep Operator Networks (DeepONets), based upon the Vlasov–Poisson simulation data to model the dynamical evolution of plasmas, focusing on the Landau damping process—a fundamental kinetic phenomenon in space and astrophysical plasmas. The trained DeepONets are able to capture the evolution of electric field energy in both linear and nonlinear regimes under various conditions. Extensive validation highlights DeepONets’ robust performance in reproducing complex plasma behaviors with high accuracy, paving the way for large-scale modeling of space and astrophysical plasmas.

plasma astrophysics↗
DOE OSTI2023

A Study of a Surrogate Nuclear Thermal Propulsion Fuel Element

We report a surrogate fuel, Zirconium Carbide/Titanium Nitride has been prepared using a simple method to obtain a more uniform distribution of titanium nitride in the zirconium carbide matrix. Powders were sintered using Spark Plasma Sintering at 1750oC and 1850oC using a modified sintering profile. This resulted in a fairly uniform distribution of titanium nitride in the zirconium carbide matrix with a density of 95% of theoretical at 1850oC. Scanning electron microscopy, indentation hardness and x-ray diffraction results are given.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

Artificial Intelligence (cs.AI)↗
DOE OSTI2015

Chemical aging of single and multicomponent biomass burning aerosol surrogate particles by OH: implications for cloud condensation nucleus activity

Multiphase OH and O 3 oxidation reactions with atmospheric organic aerosol (OA) can influence particle physicochemical properties including composition, morphology, and lifetime. Chemical aging of initially insoluble or low-soluble single-component OA by OH and O 3 can increase their water solubility and hygroscopicity, making them more active as cloud condensation nuclei (CCN) and susceptible to wet deposition. However, an outstanding problem is whether the effects of chemical aging on their CCN activity are preserved when mixed with other organic or inorganic compounds exhibiting greater water solubility. In this work, the CCN activity of laboratory-generated biomass burning aerosol (BBA) surrogate particles exposed to OH and O 3 is evaluated by determining the hygroscopicity parameter, κ, as a function of particle type, mixing state, and OH and O 3 exposure applying a CCN counter (CCNc) coupled to an aerosol flow reactor (AFR). Levoglucosan (LEV), 4-methyl-5-nitrocatechol (MNC), and potassium sulfate (KS) serve as representative BBA compounds that exhibit different hygroscopicity, water solubility, chemical functionalities, and reactivity with OH radicals, and thus exemplify the complexity of mixed inorganic/organic aerosol in the atmosphere. The CCN activities of all of the particles were unaffected by O 3 exposure. Following exposure to OH, κ of MNC was enhanced by an order of magnitude, from 0.009 to ~ 0.1, indicating that chemically aged MNC particles are better CCN and more prone to wet deposition than pure MNC particles. No significant enhancement in κ was observed for pure LEV particles following OH exposure. κ of the internally mixed particles was not affected by OH oxidation. Furthermore, the CCN activity of OH-exposed MNC-coated KS particles is similar to the OH unexposed atomized 1 : 1 by mass MNC : KS binary-component particles. Our results strongly suggest that when OA is dominated by water-soluble organic carbon (WSOC) or inorganic ions, chemical aging has no significant impact on OA hygroscopicity. The organic compounds exhibiting low solubility behave as if they are infinitely soluble when mixed with a sufficient number of water-soluble compounds. At and beyond this point, the particles' CCN activity is governed entirely by the water-soluble fraction and is not influenced by the oxidized organic fraction. Our results have important implications for heterogeneous oxidation and its impact on cloud formation given that atmospheric aerosol is a complex mixture of organic and inorganic compounds exhibiting a wide range of solubilities.

Slade, J. H.↗
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 OSTI2015

Chemical aging of single and multicomponent biomass burning aerosol surrogate-particles by OH: Implications for cloud condensation nucleus activity

Multiphase OH and O₃ oxidation reactions with atmospheric organic aerosol (OA) can influence particle physicochemical properties including composition, morphology, and lifetime. Chemical aging of initially insoluble or low soluble single-component OA by OH and O₃ can increase their water-solubility and hygroscopicity, making them more active as cloud condensation nuclei (CCN) and susceptible to wet deposition. However, an outstanding problem is whether the effects of chemical aging on their CCN activity are preserved when mixed with other organic or inorganic compounds exhibiting greater water-solubility. In this work, the CCN activity of laboratory-generated biomass burning aerosol (BBA) surrogate-particles exposed to OH and O₃ is evaluated by determining the hygroscopicity parameter, κ, as a function of particle type, mixing state, and OH/O₃ exposure applying a CCN counter (CCNc) coupled to an aerosol flow reactor (AFR). Levoglucosan (LEV), 4-methyl-5-nitrocatechol (MNC), and potassium sulfate (KS) serve as representative BBA compounds that exhibit different hygroscopicity, water solubility, chemical functionalities, and reactivity with OH radicals, and thus exemplify the complexity of mixed inorganic/organic aerosol in the atmosphere. The CCN activities of all of the particles were unaffected by O₃ exposure. Following exposure to OH, κ of MNC was enhanced by an order of magnitude, from 0.009 to ~0.1, indicating that chemically-aged MNC particles are better CCN and more prone to wet deposition than pure MNC particles. No significant enhancement in κ was observed for pure LEV particles following OH exposure. κ of the internally-mixed particles was not affected by OH oxidation. Furthermore, the CCN activity of OH exposed MNC-coated KS particles is similar to the OH unexposed atomized 1:1 by mass MNC: KS binary-component particles. Our results strongly suggest that when OA is dominated by water-soluble organic carbon (WSOC) or inorganic ions, chemical aging has no significant impact on OA hygroscopicity. The organic compounds exhibiting low solubility behave as if they are infinitely soluble when mixed with a sufficient amount of water-soluble compounds. At and beyond this point, the particles' CCN activity is governed entirely by the water-soluble fraction and not influenced by the oxidized organic fraction. Our results have important implications for heterogeneous oxidation and its impact on cloud formation given that atmospheric aerosol is a complex mixture of organic and inorganic compounds exhibiting a wide-range of solubilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A Systematic Approach to Offshore Wind Turbine Jacket Pre-Design and Optimization: Geometry, Cost, and Surrogate Structural Code Check Models

The main obstacles in preliminary design studies or optimization of jacket substructures for offshore wind turbines are high numerical expenses for structural code checks and simplistic cost assumptions. In order to create a basis for fast design evaluations, this article provides the following: firstly, a jacket model is proposed that covers topology and tube sizing with a limited set of design variables. Secondly, a cost model is proposed that goes beyond the simple and common mass-dependent approach. And thirdly, the issue of numerical efficiency is addressed by surrogate models both for fatigue and ultimate limit state code checks. In addition, this work shows an example utilizing all models. The outcome can be utilized for preliminary design studies and jacket optimization schemes and is suitable for scientific and industrial applications.

17 WIND ENERGY↗
NASA NTRS1981

Surrogate-equation technique for simulation of steady inviscid flow

A numerical procedure for the iterative solution of inviscid flow problems is described, and its utility for the calculation of steady subsonic and transonic flow fields is demonstrated. Application of the surrogate equation technique defined herein allows the formulation of stable, fully conservative, type dependent finite difference equations for use in obtaining numerical solutions to systems of first order partial differential equations, such as the steady state Euler equations. Steady, two dimensional solutions to the Euler equations for both subsonic, rotational flow and supersonic flow and to the small disturbance equations for transonic flow are presented.

Johnson, G. M.↗
NASA NTRS1990

Surrogate oracles, generalized dependency and simpler models

Software reliability models require the sequence of interfailure times from the debugging process as input. It was previously illustrated that using data from replicated debugging could greatly improve reliability predictions. However, inexpensive replication of the debugging process requires the existence of a cheap, fast error detector. Laboratory experiments can be designed around a gold version which is used as an oracle or around an n-version error detector. Unfortunately, software developers can not be expected to have an oracle or to bear the expense of n-versions. A generic technique is being investigated for approximating replicated data by using the partially debugged software as a difference detector. It is believed that the failure rate of each fault has significant dependence on the presence or absence of other faults. Thus, in order to discuss a failure rate for a known fault, the presence or absence of each of the other known faults needs to be specified. Also, in simpler models which use shorter input sequences without sacrificing accuracy are of interest. In fact, a possible gain in performance is conjectured. To investigate these propositions, NASA computers running LIC (RTI) versions are used to generate data. This data will be used to label the debugging graph associated with each version. These labeled graphs will be used to test the utility of a surrogate oracle, to analyze the dependent nature of fault failure rates and to explore the feasibility of reliability models which use the data of only the most recent failures.

Wilson, Larry↗
NASA NTRS1998

A Rigorous Framework for Optimization of Expensive Functions by Surrogates

The goal of the research reported here is to develop rigorous optimization algorithms to apply to some engineering design problems for which design application of traditional optimization approaches is not practical. This paper presents and analyzes a framework for generating a sequence of approximations to the objective function and managing the use of these approximations as surrogates for optimization. The result is to obtain convergence to a minimizer of an expensive objective function subject to simple constraints. The approach is widely applicable because it does not require, or even explicitly approximate, derivatives of the objective. Numerical results are presented for a 31-variable helicopter rotor blade design example and for a standard optimization test example.

Booker, Andrew J.↗
NASA NTRS1999

Software Surrogate

In 1994, Blackboard Technology received a NASA Phase I SBIR award entitled "A Blackboard-Based Framework for Mixed-Initiative, Crewed- Space-System Applications." This research continued in Phase II at JSC, where a generic architecture was developed in which a software surrogate serves as the operator's representative in the fast-paced realm of nearly autonomous, intelligent systems. This SBIR research effort addressed the need to support human-operator monitoring and intervention with intelligent systems such as those being developed for NASA's crewed space program.

Source record↗
NASA NTRS2003

Experimental Study of the Angle of Repose of Surrogate Martian Dust

Accumulation of wind-blown dust particles on solar cells and instruments will be a great challenge in the exploration of Mars, significantly reducing their lifetime, durability, and power output. For future Mars Lander missions it is crucial to gain information about the ideal angle at which solar panels can be positioned to minimize dust deposition and thus, maximize the power output and lifetime of the solar cells. The major determinant for the optimal panel angle is the angle of repose of the dust particles that is dependent on a variety of physical and chemical properties of the particles, the panel surface, and the environmental conditions on the Mars surface. To gain a basic understanding of the physical and chemical processes that govern dust deposition and to get feedback for the design of an experiment suitable for one of the future Mars Lander missions we simulate atmospheric conditions expected on the Mars surface in a controlled chamber, and observe the angle of repose of Mars dust surrogates. Dust deposition and angle of repose were observed on different sized spheres. To cover a range of potential materials we will use spheres made of 7075 aluminum (10 mm, and 15 mm), alumina oxide ceramic (10 mm), and Teflon(trademark) (10 mm) and wafers of gallium arsenide, silicon.

Moeller, L. E.↗