Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model code”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Advancing Theory and Modeling Efforts in Heliophysics

Heliophysics theory and modeling build understanding from fundamental principles to motivate, interpret, and predict observations. Together with observational analysis, they constitute a comprehensive scientific program in heliophysics. As observations and data analysis become increasingly detailed, it is critical that theory and modeling develop more quantitative predictions and iterate with observations. Advanced theory and modeling can inspire and greatly improve the design of new instruments and increase their chance of success. In addition, in order to build physicsbased space weather forecast models, it is important to keep developing and testing new theories, and maintaining constant communications with theory and modeling. Maintaining a sustainable effort in theory and modeling is critically important to heliophysics. We recommend that all funding agencies join forces and consider expanding current and creating new theory and modeling programs–especially, 1. NASA should restore the HTMS program to its original support level to meet the critical needs of heliophysics science; 2. a Strategic Research Model program needs to be created to support model development for next-generation basic research codes; 3. new programs must be created for addressing mission-critical theory and modeling needs; and 4. enhanced programs are urgently required for training the next generation of theorists and modelers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Measurement and Modeling of Electron Temperature in Laboratory Photoionized Plasmas Relevant to Astrophysics

The electron temperature of photoionized plasmas characterizes the thermalization of photoelectrons, impacts the charge-state distribution, emissivity, and opacity through atomic recombination processes, and is needed to perform detailed comparisons with theory predictions. We discuss temperature measurements in laboratory photoionized plasmas and a comparison with model calculations done with several theory approximations and codes. These include a radiation-hydrodynamics simulation and two nonequilibrium heating and ionization models that tracked the evolution of the internal energy of the electrons. Furthermore, for the same physics model and X-ray flux time history, calculations were performed assuming steady-state or time-dependent conditions. The time history of steady-state results correlates with that of the X-ray flux, while that of the time-dependent cases does not, and it is qualitatively and quantitatively different from the steady-state case. Steady-state results significantly overestimated temperature measurements, while time-dependent results produced better approximations, which suggests the importance of transient effects in the experiment and also the need for time-resolved measurements.

Laboratory astrophysics↗
DOE OSTI2024

Coupled model for liquid lithium plasma facing components

Numerical analysis provides the design choice and operating window of liquid metal Plasma Facing Components (PFC) concepts. Coupled analysis of boundary plasma together with the surrounding boundary structures is required. Here, to achieve this goal, PPPL is developing a comprehensive multi-physics model for modeling of PFCs in fusion devices. The model includes the fluid-kinetic code SOLPS-ITER and the flow and heat transfer code CFX from ANSYS. SOLPS-ITER was augmented with a liquid metal boundary condition algorithm, allowing direct two-way coupling of the plasma analysis with the two-dimensional analytical slab flow model which includes heat convection in the liquid metal PFC. The target heat flux resulting from this coupled analysis is used as a boundary condition for detailed 3D Computational Fluid Dynamics (CFD) Magneto Hydro Dynamics (MHD) and heat transfer analysis. A new formulation of MHD equations is introduced in the numerical procedure ensuring current conservation of the discretized equations. Results of the 3D analysis are used for final validation of the coupled model. A PFC design where a porous wall is used to stabilize the liquid metal surface, while MHD drive is used to push the liquid metal flow inside the PFC, will be investigated in the regimes where vapor shielding is created for enhanced volumetric plasma heat dissipation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Reionization effective likelihood from Planck 2018 data

We release relike (reionization effective likelihood), a fast and accurate effective likelihood code based on the latest Planck 2018 data that allows one to constrain any model for reionization between 6 < z < 30 using five constraints from the CMB reionization principal components (PC). We tested the code on two example models which showed excellent agreement with sampling the exact Planck likelihoods using either a simple Gaussian PC likelihood or its full kernel density estimate. This code enables a fast and consistent means for combining Planck constraints with other reionization data sets, such as kinetic Sunyaev-Zeldovich effects, line-intensity mapping, luminosity function, star formation history, quasar spectra, etc., where the redshift dependence of the ionization history is important. Since the PC technique tests any reionization history in the given range, we also derive model-independent constraints for the total Thomson optical depth τ PC = $0.0619$$^{+0.0056}_{–0.0068}$ and its 15 ≤ z ≤ 30 high redshift component τ PC (15,30) < 0.020 (95% C.L.). Furthermore, the upper limits on the high-redshift optical depth is a factor of ~3 larger than those reported in the Planck 2018 cosmological parameter paper using the FlexKnot method and we validate our results with a direct analysis of a two-step model which permits this small high-z component.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Implementation of a Drift-Flux Model in SAM for Modeling of Passively Transported GAS in Molten Salt Reactors

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is further developing the Multiphysics Object Oriented Simulation Environment (MOOSE) system thermal hydraulics (T/H) code, System Analysis Module (SAM), to include modeling of molten salt reactor (MSR) designs. MSR designs in which the fuel is dissolved in the salt coolant poses unique modeling and simulation (M&S) challenges because fission products—some of which will be noncondensable gasses—travel with the coolant, thus allowing for deposition and interaction throughout the entire system flow loop. This behavior must be modeled to successfully understand MSR system behavior during normal and off-normal operation events. In past work, SAM has been extended to include a passive species transport capability for modeling of MSR fission products that travel with the salt coolant. This work extends the model to include a drift-flux model to capture the tendency of the gas phase to move at a different velocity than the bulk liquid. Additional constitutive models have also been added for calculation of gas volume fraction, bubble radius, and interfacial area, which will be important for calculation of species phase migration in future coupling activities. Testing has been performed to ensure that the new model agrees with expected values for several simple models, but additional future work will be required to test the model for more complex geometries that will be needed for full-scale MSR simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Initial development of viscoplastic constitutive model of Alloy 800H in support of the use of inelastic analysis methods for ASME Section III, Division 5, Class A applications

This report describes the development of a preliminary inelastic constitutive model for the thermomechanical behavior of Alloy 800H. The objective is to develop a model suitable for incorporating into Nonmandatory Appendix Z to Section III, Division 5 of the ASME Boiler & Pressure Vessel Code, which provides guidance and reference constitutive models for the ASME design by inelastic analysis rules for Class A components. The report describes the process of collecting experimental data, developing a mathematical form for the model, and training the model against the test data. The initial version of the model captures most of the relevant material deformation mechanisms, including dynamic strain aging effects. However, further development of the model form will be required to develop a final model suitable for ASME use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Broad Grid of 2D Kilonova Emission Models

Depending upon the properties of their compact remnants and the physics included in the models, simulations of neutron star mergers can produce a broad range of ejecta properties. The characteristics of this ejecta, in turn, define the kilonova emission. To explore the effect of ejecta properties, we present a grid of 2-component 2D axisymmetric kilonova simulations that vary mass, velocity, morphology, and composition. The masses and velocities of each component vary, respectively, from 0.001 to 0.1 M ⊙ and 0.05 to 0.3c, covering much of the range of results from the neutron star merger literature. The set of 900 models is constrained to have a toroidal low electron fraction (Y e ) ejecta with a robust r-process composition and either a spherical or lobed high-Y e ejecta with two possible compositions. We simulate these models with the Monte Carlo radiative transfer code SuperNu using a full suite of lanthanide and 4th row element opacities. We examine the trends of these models with parameter variation, show how it can be used with statistical tools, and compare the model light curves and spectra to those of AT2017gfo, the electromagnetic counterpart of GW170817.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Keras2c: A library for converting Keras neural networks to real-time compatible C

With the growth of machine learning models and neural networks in measurement and control systems comes the need to deploy these models in a way that is compatible with existing systems. Existing options for deploying neural networks either introduce very high latency, require expensive and time consuming work to integrate into existing code bases, or only support a very limited subset of model types. We have therefore developed a new method called Keras2c, which is a simple library for converting Keras/TensorFlow neural network models into real-time compatible C code. It supports a wide range of Keras layers and model types including multidimensional convolutions, recurrent layers, multi-input/output models, and shared layers. Keras2c re-implements the core components of Keras/TensorFlow required for predictive forward passes through neural networks in pure C, relying only on standard library functions considered safe for real-time use. The core functionality consists of ~ 1500 lines of code, making it lightweight and easy to integrate into existing codebases. Keras2c has been successfully tested in experiments and is currently in use on the plasma control system at the DIII-D National Fusion Facility at General Atomics in San Diego.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90° to 110°, corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching (-4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Astroparticle Physics and High-Energy Cosmic Pheno↗
DOE OSTI2021

MACCS (MELCOR Accident Consequence Code System) User Guide

The MELCOR Accident Consequence Code System (MACCS) is used by Nuclear Regulatory Commission (NRC) and various national and international organizations for probabilistic consequence analysis of nuclear power accidents. This User Guide is intended to assist analysts in understanding the MACCS/WinMACCS model and to provide information regarding the code. This user guide version describes MACCS Version 3.10.0. Features that have been added to MACCS in subsequent versions are described in separate documentation. This User Guide provides a brief description of the model history, explains how to set up and execute a problem, and informs the user of the definition of various input parameters and any constraints placed on those parameters. This report is part of a series of reports documenting MACCS. Other reports include the MACCS Theory Manual, MACCS Verification Report, Technical Bases for Consequence Analyses Using MACCS, as well as documentation for preprocessor codes including SecPop, MelMACCS, and COMIDA2. PAPERWORK REDUCTION ACT STATEMENT The NUREG does not contain information collection requirements and, therefore, is not subject to the requirements of the Paperwork Reduction Act of 1995 (44 USC 3501, et seq.). PUBLIC PROTECTION NOTIFICATION The NRC may not conduct or sponsor, and a person is not required to respond to, a request for information or an information collection requirement unless the requesting document displays a currently valid OMB control number. ACKNOWLEDGEMENTS Contributions to this User Guide were received from NRC and Sandia National Laboratories (SNL) project managers, technical experts, and code authors dedicated to the production of a valuable resource for the MACCS user community. Instructions and guidance included herein were developed over many years and include advancements in the code that provide users the ability to develop complex consequence modeling scenarios. WinMACCS and many of the early MACCS developments were due to vision of an earlier Project Manager, Jocelyn Mitchell. Jonathan Barr and AJ Nosek also contributed to the development of this report. The current NRC Project Manager, Salman Haq, provided the leadership to ensure this document was completed. Several other NRC and Sandia staff provided insights supporting development of the MACCS code and of this document.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

An international review of occupant-related aspects of building energy codes and standards

In light of recent research, it is evident that occupants are playing an increasingly important role in building energy performance. Furthermore, despite the important role of building energy codes and standards in design, the occupant-related aspects are typically simple and have not kept up with the leading research. This paper reviews 23 regions’ building energy codes and standards by first comparing their quantitative aspects and then analyzing their mandated rules and approaches. While the present paper focuses on offices, general recommendations are applicable to other building types as well. The review revealed a wide range of occupant-related values, approaches, and attitudes. For example, code-specified occupant density varies by nearly a factor of three between different codes. This underlines the need for development of advancement in occupant behavior modeling approaches for future occupant-centric building performance codes and standards. Moreover, occupants are often referred to only implicitly; underlying expectations about energy-saving occupant behavior from building occupants varies greatly; and, only a few codes address occupant feedback and system usability. Based on the findings of the review, a set of initial recommendations for future building energy codes is proposed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

viral_fam_classifier

This code applies publicly available Hidden Markov Model (HMM) profiles to publicly available reference genomes of viruses. It parses the output of these searches to determine bitscore cut-offs for viral taxonomic lineages that may be represented by each HMM. Subsequently, the code will allow the user to classify novel viral sequences using these bitscore cut-offs. This code is a work-in-progress.

Kantor, Rose [Lawrence Livermore National Laborato↗
DOE OSTI2020

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

MELCOR 2.2 Benchmarks of Peach Bottom NUREG/CR 7155 Uncertainty Analysis

The U.S. Nuclear Regulatory Commission (NRC) performed a first-of-a-kind uncertainty analysis (UA) of the accident progression, radiological releases, and offsite consequences for the State-of- the-Art Reactor Consequence Analyses (SOARCA) of an unmitigated long-term station blackout (LTSBO) severe accident scenario at the Peach Bottom Atomic Power Station. The objective of the UA was to evaluate the robustness of the SOARCA deterministic "best estimate results and conclusions documented in NUREG-1935, and to develop insight into the overall sensitivity of the SOARCA results to uncertainty in key modeling inputs. The study was completed in 2015 and documented in NUREG/CR-7155. Since 2015, two other SOARCA UAs were completed for two pressurized water reactor (PWR) plants. The PWR UAs incrementally updated the approach and methodology, including using the latest release of the MELCOR 2.2 computer code. There were also advances made in the state-of-the-art modeling related to NRC efforts using the Peach Bottom model in NUREG-2206, which provided the technical basis for the containment protection and release reduction rulemaking for boiling water reactors with Mark I and Mark II containments. This report documents the input model changes from the NUREG/CR-7155 study and performs a small number of reference calculations to assess the changes of the new computer code and the model input updates. The objective of the work is to verify whether the updated Peach Bottom MELCOR model and updated version of MELCOR support the conclusions formed in the Peach Bottom SOARCA UA by performing these representative calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Integrated Tiger Series (ITS) Code Validation and Uncertainty Quantification for Electron Number Albedo in Various Materials

In the 1970’s and 1980’s, researchers at Sandia National Laboratories produced electron albedo data for a range of materials. Since that time, the electron albedo data has been used for a wide variety of purposes including the validation of Monte Carlo electron transport codes. This report was compiled to examine the electron albedo experiment results in the context of Integrated Tiger Series (ITS) validation. The report presents tables and figures that could provide insight into the underlying model form uncertainty present in the ITS code. Additionally, the report provides data on potential means to reduce these model form errors by highlighting potential refinements in the cross-section generation process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Validation and application of a multiphase CFD model for hydrodynamics, temperature field and RTD simulation in a pilot-scale biomass pyrolysis vapor phase upgrading reactor

Accurate prediction of transport phenomena is critical for VPU reactor design, optimization, and scale-up. The current study focused on the validation and application of a multiphase CFD model within an open-source code MFiX for hydrodynamics, temperature field, and residence time distribution (RTD) simulation in a non-reacting circulating fluidized bed riser for biomass pyrolysis vapor phase upgrading (VPU). First, an Eulerian-Eulerian approach three-dimensional CFD model was employed to simulate the pilot-scale VPU riser on the supercomputer Joule. Excellent quantitative agreement between experimental and simulated results was achieved for pressure drops and temperature field in a range of operating conditions. Then the validated multiphase CFD model was applied to predict gas and solid residence time distributions (RTDs) since prediction and analysis of RTD is an important tool to study the complex multiphase flow behavior and mixing inside chemical reactors. The predictions show that solid mean residence time is 3.5 times the gas residence time; the solid RTD is more sensitive to the process gas flow rate than the solids circulation rate.

09 BIOMASS FUELS↗