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At least 1,441 records · Page 80

Fluorescent excitation of interstellar H2

The infrared emission spectrum of H2 excited by ultraviolet absorption, followed by fluorescence, was investigated using comprehensive models of interstellar clouds for computing the spectrum and to assess the effects on the intensity to various cloud properties, such as density, size, temperature, and the intensity of the UV radiation field. It is shown that the absolute H2 IR line intensities depend primarily on the density of the cloud and the strength of the incident UV radiation, and to a much lesser exent on the temperature of the gas, the total thickness of the cloud, and the optical properties of the grains. A variety of recent observational results are discussed with reference to theoretical models. It is shown that the rich H2 emission spectrum of the reflection nebula NGC 2023 can be reproduced by a model with density of about 10,000/cu cm, temperature of about 80 K, and UV flux approximately 300 times that of the Galactic background starlight.

Black, John H.↗

The design and operational development of self-streamlining 2-dimensional flexible walled test sections

Self streamlining two dimensional flexible walled test sections eliminate the uncertainties found in data from conventional test sections particularly at transonic speeds. The test section sidewalls are rigid, while the floor and ceiling are flexible and are positioned to streamline shapes by a system of jacks, without reference to the model. The walls are therefore self streamlining. Data are taken from the model when the walls are good streamlines such that the inevitable residual wall induced interference is acceptably small and correctable. Successful two dimensional validation testing at low speeds has led to the development of a new transonic flexible walled test section. Tunnel setting times are minimized by the development of a rapid wall setting strategy coupled with on line computer control of wall shapes using motorized jacks. Two dimensional validation testing using symmetric and cambered aerofoils in the Mach number range up to about 0.85 where the walls are just supercritical, shows good agreement with reference data using small height-chord ratios between 1.5 and unity.

Wolf, S. W. D.↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

MODELING THE ASTEROSEISMIC SURFACE TERM ACROSS THE HR DIAGRAM

Asteroseismology is a powerful tool that can precisely characterize the mass, radius, and other properties of field stars. However, our inability to properly model the near-surface layers of stars creates a frequency-dependent frequency difference between the observed and the modeled frequencies, usually referred to as the “surface term.” This surface term can add significant errors to the derived stellar properties unless removed properly. In this paper, we simulate surface terms across a significant portion of the HR diagram, exploring four different masses (M=0.8,1.0,1.2, and 1.5 M{sub ⊙}) at five metallicities ([Fe/H]=0.5,0.0,−0.5,−1.0, and −1.5) from the main sequence to red giants for stars with T{sub eff}<6500 K and explore how well the most common ways of fitting and removing the surface term actually perform. We find that the two-term model proposed by Ball and Gizon works much better than other models across a large portion of the HR diagram, including the red giants, leading us to recommend its use for future asteroseismic analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

An efficient approach for prediction of Warburg-type resistance under working currents

In the present paper, an efficient approach for the prediction of Warburg-type element is proposed via the analysis of the anode-supported solid oxide fuel cell (SOFC) performance under various working conditions. The details of the performance, polarization curves, impedance behavior, and species distribution profiles within the electrode are investigated via the combination of equivalent circuit model (ECM) analysis and multiphysics numerical simulations. The multiphysics simulation is developed and calibrated with experimental results of SOFC button cells under various working currents. With the complete datasets generated from the calibrated simulations, the trends of the element parameters involved in equivalent circuit model are analyzed. Generalized empirical functions are proposed as well as the procedures of prediction of performance under different conditions. The verification cases show good agreement between the predicted results from proposed model and the reference results. This proposed approach can be utilized to quickly predict the properties for desired performance in the manufacturing processes, and it also has the potential of reducing the computational cost in the simulation of large SOFCs.

25 ENERGY STORAGE↗

A numerical investigation on methane combustion and emissions from a natural gas-diesel dual fuel engine using CFD model

Natural gas (NG)-diesel dual fuel engines have been criticized for their high emissions of unburned methane. The past research on methane emissions from dual fuel engines has focused on the measurement of methane concentration in exhaust gases. The development of approaches capable of minimizing methane emissions requests the detailed spatial distribution of methane in-cylinder during the combustion and post combustion processes. However, it is difficult to experimentally measure the spatial distribution of methane in-cylinder. Here this research presents a numerical study on the combustion process of a NG-diesel dual fuel engine using the computational fluids dynamics (CFD) model CONVERGE coupled with a reduced primary reference fuel (PRF) mechanism. The model was validated against the heat release process and the emissions of nitrogen oxide, methane and carbon monoxide measured in a single cylinder dual fuel engine. The validated CFD model was applied to investigate the combustion of methane and n-heptane and the spatial distribution of methane in the dual fuel engine. This is most likely the first attempt to visualize the spatial distribution of methane in dual fuel engines using CFD. The objective of this study is to numerically simulate the methane combustion process, especially the methane present outside the pilot spray, quantify the methane combustion in each combustion stage, and visualize the spatial methane distribution in cylinder. The results showed that the momentum produced by the pilot fuel injection and combustion pushed the combustion products of pilot fuel and methane within the pilot spray plume toward the unburned methane-air mixture. Such a movement enhanced the mixing of the hot combustion products and the relatively cold unburned methane-air mixture during the main combustion process and dominated the combustion of methane presented outside the pilot fuel spray plume. Based on the simulation results at a low load condition (4.05 bar), the main combustion process consumed 43–53% of the methane fumigated into the intake mixture. The post-combustion oxidation process consumed 17–29% of the intake methane, which was 36.2–51.8% methane that survived the main combustion process. In comparison, 27–35% methane emitted the engine without participating the combustion process. The unburned methane at exhaust valve opening was mainly observed at the center of the cylinder. In comparison, the contribution of the crevice and boundary layer around the cylinder liner to methane emissions was relatively small. The slip of methane through the dual fuel engines was due to the fact that the premixed mixture was too lean to support the propagation of the turbulent flame initiated by the pilot fuel and the lack of pilot fuel vapor reaching the center of the combustion chamber because of the geometric limitations of the fuel injection system and the reduced mass of pilot fuel injected into the cylinder. The approaches aiming to enhance the combustion of methane and minimize methane emissions from dual fuel engines should focus on those capable of increasing the volume of pilot fuel vapor formed after injected into the cylinder.

42 ENGINEERING↗

A Fast and Accurate Reduced-Order Model for High-Intensity Transferred Arc Discharges

Arc discharges are widely used in welding, plasma smelting, and other industrial processes, where variations in operating conditions strongly affect arc stability, temperature distribution, and energy transfer. Accurate modeling of these phenomena typically requires computationally expensive high-fidelity simulations. This study presents a hierarchy of three arc discharge models with progressively reduced physical fidelity. The high-fidelity model provides a fully physics-resolved reference, the reduced-order model reproduces the dominant thermal and flow characteristics of the arc with reasonable accuracy, and the Elenbaas-Heller model captures key trends in a simplified, rapid formulation. This hierarchy demonstrates that reduced-order model can effectively balance predictive fidelity and computational efficiency, providing practical tools for arc simulation and parametric studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diagnosis of convective organization and cold pools using ARM datasets and evaluation of a unified convection parameterization (UNICON)

Tropical thunderstorms often cluster together. Studies have suggested that the degree to which the tropical thunderstorms are clustered impacts Earth's energy balance and water cycle, as well as extreme precipitation events. However, the processes controlling the spatial distribution of the thunderstorms are poorly understood and are not properly represented in most computer models for weather and climate prediction. Under the goals of better understanding how convection organizes at the mesoscale and advancing the representation of mesoscale convective organization in global climate models, we i) objectively quantified the degrees of convective organization and diagnosed cold pool processes using ARM field campaign observations, ii) examined the organization processes in storm-resolving model simulations, and iii) evaluated the impacts of mesoscale convective organization in global model simulations. The project yielded a firm reference against which the global model representation of mesoscale convective organization and cold pools can be evaluated against and shed new light into the role of parameterized convective organization in the global model simulation of the basic state and variability. Our results revealed two distinct phases of convective clustering during the two-day rain episodes (Cheng et al. 2018) and a new mechanism through which vertical wind shear in the low-troposphere can aid convective organization over tropical oceans (Cheng et al. 2020). It was demonstrated that the interactive representation of cold pools and mesoscale convective organization is key for global models to successfully simulate both the mean state and intraseasonal variability in the tropics (Ahn et al. 2019; 2020).

54 ENVIRONMENTAL SCIENCES↗

Atmospheric disturbance modelling requirements for flying qualities applications

Flying qualities are defined as those airplane characteristics which govern the ease or precision with which the pilot can accomplish the mission. Some atmospheric disturbance modelling requirements for aircraft flying qualities applications are reviewed. It is concluded that some simplifications are justified in identifying the primary influence on aircraft response and pilot control. It is recommended that a universal environmental model be developed, which could form the reference for different applications. This model should include the latest information on winds, turbulence, gusts, visibility, icing and precipitation. A chosen model would be kept by a national agency and updated regularly by feedback from users. A user manual is believed to be an essential part of such a model.

Moorhouse, D. J.↗

Spectral decontamination of a real-time helicopter simulation

Nonlinear mathematical models of a rotor system, referred to as rotating blade-element models, produce steady-state, high-frequency harmonics of significant magnitude. In a discrete simulation model, certain of these harmonics may be incompatible with realistic real-time computational constraints because of their aliasing into the operational low-pass region. However, the energy is an aliased harmonic may be suppressed by increasing the computation rate of an isolated, causal nonlinearity and using an appropriate filter. This decontamination technique is applied to Sikorsky's real-time model of the Black Hawk helicopter, as supplied to NASA for handling-qualities investigations.

Mcfarland, R. E.↗

The role of ionospheric plasma in the magnetosphere

During the course of this project we have made a great deal of progress developing and using a new plasma modeling technique which we now refer to as the Generalized Semikinetic (GSK) model. It has been used to study the development of plasma flows in the plasmasphere, the polar cap and auroral zones, and the transition region. Below we describe some of the major accomplishments of this grant.

Wilson, Gordon R.↗

Overview of Base Model in Parametric Studies Specific to Performance of U-Mo Plates

This paper provides an overview of the base model specifically developed to perform parametric sensitivity studies on the U-10Mo monolithic fuel system. U-Mo monolithic fuels are being considered for the conversion of test reactors into high-performance research reactors that operate using proliferation-resistant, low-enriched uranium (LEU) fuels. These plate-type fuels contain a high-density, low-enrichment fuel sandwiched between zirconium diffusion barriers and encapsulated in aluminum claddings. All U.S. high-performance research reactors have released the designs of their LEU monolithic fuel reactor cores. These designs include nearly 50 distinct fuel plate geometries with different operational parameters. Consequently, a single generic plate geometry representing all the extreme points in this design matrix is unrealistic. To evaluate the performance for various parameters, a set of sensitivity studies was performed. These studies considered various input parameters (i.e., geometric, operational, and material property-related). The results revealed valuable information about plate performance and the sensitivity of this performance to various modeling inputs. To establish a reference state for comparing these result, base model featuring representative irradiation conditions was developed. To capture in-reactor behavior accurately, incorporation of representative constitutive models capable of evolving properties with respect to temperature, irradiation time, and burnup was needed. The behavioral models considered burnup-dependent properties, swelling, creep, and degradation. This paper introduces the base model created for the parametric sensitivity studies. The detailed description of the procedure includes the model geometry, model discretization, thermo-mechanical coupling, material properties and behavioral models. This paper also provides selected results and assesses the performance of the base model.

42 ENGINEERING↗

Reproducible benchmark for the SNAP 8 experimental reactor at operating conditions

This work presents fully reproducible multiphysics benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor at operating conditions with coolant flow. Wet experiment (with coolant, at power) validation benchmarks are presented using both deterministic (Serpent-Griffin) and Monte-Carlo (OpenMC-Cardinal) multiphysics frameworks coupled with thermal-hydraulic solvers in MOOSE. Reactivity coefficient measurements including fuel temperature, isothermal temperature, and power coefficients show good agreement with experiments, with discrepancies within experimental uncertainty. Reactivity worth experiments for coolant, samarium, and xenon poisoning are reproduced with differences under 200 pcm. Comparison between Serpent-Griffin and OpenMC-Cardinal frameworks reveal multiphysics coupling introduces positive reactivity effects (100-200 pcm) compared to uniform temperature and density fields at nominal operating conditions. Comparison between Serpent-Griffin and reference Serpent solution shows that power distributions maintain consistent radial and axial peaking behavior. All models, assumptions, thermophysical and thermomechanical properties, and material definitions are thoroughly documented with cited references; model inputs and model generating scripts are stored in the snapReactors GitHub repository.

SNAP↗

Interparameter trade-off quantification and reduction in isotropic-elastic full-waveform inversion: synthetic experiments and Hussar land data set application

The problem of inverting for multiple physical parameters in the subsurface using seismic full-waveform inversion (FWI) is complicated by interparameter trade-off arising from inherent ambiguities between different physical parameters. Parameter resolution is often characterized using scattering radiation patterns, but these neglect some important aspects of interparameter trade-off. More general analysis and mitigation of interparameter trade-off in isotropic-elastic FWI is possible through judiciously chosen multiparameter Hessian matrix-vector products. We show that products of multiparameter Hessian off-diagonal blocks with model perturbation vectors, referred to as interparameter contamination kernels , are central to the approach. We then apply the multiparameter Hessian to various vectors designed to provide information regarding the strengths and characteristics of interparameter contamination, both locally and within the whole volume. With numerical experiments, we observe that S-wave velocity perturbations introduce strong contaminations into density and phase-reversed contaminations into P-wave velocity, but themselves experience only limited contaminations from other parameters. Based on these findings, we introduce a novel strategy to mitigate the influence of interparameter trade-off with approximate contamination kernels. Furthermore, we recommend that the local spatial and interparameter trade-off of the inverted models be quantified using extended multiparameter point spread functions (EMPSFs) obtained with pre-conditioned conjugate-gradient algorithm. Compared to traditional point spread functions, the EMPSFs appear to provide more accurate measurements for resolution analysis, by de-blurring the estimations, scaling magnitudes and mitigating interparameter contamination. Approximate eigenvalue volumes constructed with stochastic probing approach are proposed to evaluate the resolution of the inverted models within the whole model. With a synthetic Marmousi model example and a land seismic field data set from Hussar, Alberta, Canada, we confirm that the new inversion strategy suppresses the interparameter contamination effectively and provides more reliable density estimations in isotropic-elastic FWI as compared to standard simultaneous inversion approach.

58 GEOSCIENCES↗

Recent improvements to and validation of the one dimensional NASA wave rotor model

A numerical model has been developed at the NASA Lewis Research Center which can predict both the unsteady flow quantities within a wave rotor passage and the steady averaged flows in the ports. The model is based on the assumptions of one-dimensional, unsteady, perfect gas flow. The model assesses not only the dominant wave behavior, but the loss effects of finite passage opening time, leakage from the passage ends, viscosity, and heat transfer to and from the passages. The model operates in the rotor reference frame; however, until recently no account was made for the often significant effect of the rotor circumferential velocity component. The present model accounts for this by modifying the passage boundary conditions, allowing the internal computational scheme to remain the rotor reference frame, while quantities such as inlet duct stagnation properties may be specified in the fixed or absolute reference frame. Accurate modeling of this effect is critical to successful wave rotor analysis and design, particularly in off-design predictions where the flows in the inlet ducts are mismatched with the rotor passages and significant turning may take place (i.e., work is done on the gas). The relative simplicity of the model makes it useful for design and optimization, as well as analysis, of wave rotor cycles for many applications. This report, building on several earlier papers, describes the most recent modifications to the model. These include accounting for the relative/absolute transition at the passage boundaries and refinements to the viscous source term correlation which resulted from this accounting. Comparison of model predictions with measured data is then presented and discussed.

Paxson, Daniel E.↗

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

THREE-DIMENSIONAL MHD MAGNETIC RECONNECTION SIMULATIONS WITH A FINITE GUIDE FIELD: PROPOSAL OF THE SHOCK-EVOKING POSITIVE-FEEDBACK MODEL

Using a three-dimensional (3D) magnetohydrodynamic model, we simulate the magnetic reconnection in a single current sheet. We assume a finite guide field, a random perturbation on the velocity field, and uniform resistivity. Our model enhances the reconnection rate relative to the classical Sweet–Parker model in the same configuration. The efficiency of magnetic energy conversion is increased by interactions between the multiple tearing layers coexisting in the global current sheet. This interaction, which forms a positive-feedback system, arises from coupling of the inflow and outflow regions in different layers across the current sheet. The coupling accelerates the elementary reconnection events, thereby enhancing the global reconnection rate. The reconnection establishes flux tubes along each tearing layer. Slow-mode shocks gradually form along the outer boundaries of these tubes, further accelerating the magnetic energy conversion. Such a positive-feedback system is absent in two-dimensional simulations, 3D reconnection without a guide field, and reconnection under a single perturbation mode. We refer to our model as the “shock-evoking positive-feedback” model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗