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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Application of Modular Modeling System to Predict Evaporation, Infiltration, Air Temperature, and Soil Moisture

Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.

Boggs, Johnny↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2023

Automated Progress Monitoring in Modular Construction Factories Using Computer Vision and Building Information Modeling

Modular construction methods have recently gained interest due to the advantages offered in terms of safety, quality, and productivity for projects. In this method, a significant portion of the construction is performed off-site in factories where modular components are built in different workstations, assembled on the production line, and shipped to the site for installation. Due to the labor-intensive nature of tasks, cycle times in modular construction factories are highly variable, which commonly leads to major bottlenecks and delays in construction projects. To remedy this effect, recent methods rely on sensors such as RFID to monitor the production process, which is reportedly expensive, and intrusive to the work process. Recently, computer vision-based methods have been proposed to track the production process in modular construction factories. However, these methods overlook monitoring the assembly process on the production line. Therefore, this paper presents a method to monitor the assembly process by integrating computer vision-based methods with Building Information Modeling (BIM). The proposed method detects the modular units using object segmentation; superimposes the installation area with the corresponding 2D region using BIM, and identifies the installation of the components using image processing techniques. The proposed method has been validated using surveillance videos captured from a modular construction factory in the US. Successful implementation of the proposed method can lead to timely identification of delays during the assembly process and reduce delays in modular integrated construction projects.

building information modeling↗
DOE OSTI2020

Flexible and Modular Simultaneous Modeling of Flow and Reactive Transport in Rivers and Hyporheic Zones

Investigations of coupled multiphysics processes in rivers and hyporheic zones have extensively used numerical models. Most existing models use a sequential, one-way coupling between the surface and subsurface domains. Such one-way coupling potentially introduces error. To overcome this, a fully coupled model, hyporheicFoam, was developed using the open-source computational platform OpenFOAM. It captures the coupled flow and multicomponent reactive transport processes within both surface and subsurface domains and across their interface. The coupling between two domains is implemented by mapping conservative flux boundary conditions at the interface through an iterative algorithm. Reactive transport is enabled by specifying a reaction network. To start, we have implemented reaction kinetics following the double Monod-type model with inhibition. The model capability is illustrated through modeling of both conservative and reactive hyporheic flow and transport through dune bedforms. With the novel coupled model, it is now possible to quantify reactions wherein the reactants and products are constantly exchanging between domains and have feedbacks. hyporheicFoam can simulate large, three-dimensional cases owing to the computational flexibility and power offered by the code structure and parallel design of OpenFOAM.

58 GEOSCIENCES↗
NASA NTRS1994

A Modular, Portable Model of Image Fidelity

There is a persistent need for a trustworthy model of perceptual image fidelity, especially in applications such as image compression and display design. A fidelity model provides a measure of the visual discriminability of two images. Ahumada has previously shown that the existing fidelity models may be categorized according to their inclusion of various canonical properties, such as a contrast sensitivity function, spatial frequency channels, etc. This suggests that research would be aided by the availability of a modular model, in which these components could be easily inserted or removed. A further impediment to research in this area has been that most models are written in low-level languages and are consequently large, non-portable, and difficult to understand, modify, and maintain. We therefore believe research would also be aided by models written in high-level languages. To serve both of these purposes, and to honor our conference host for his lifetime dedication to the problem of image quality. Global brightness and its effect on perceptual image quality. We offer a modular model written in the high-level language Mathematica. We will demonstrate this model and show how it may be modified.

Watson, Andrew B.↗
DOE OSTI2020

Modular Growth and Nucleation Formulations in Modular Plasticity Models

Recent investigations like the second and third Sandia Fracture Challenges have characterized and demonstrated the performance of a variety of failure techniques and models. These surveys have considered a wide breadth of models encapsulating both general failure criteria as well as those focusing on pore nucleation and growth. Extensive reviews exist on both topics. The former category generally consists of classic models like the Johnson-Cook or Wilkins criteria. These models were recently added to modular plasticity models in the Library of Advanced Materials for Engineering (LAME) as criteria for use with element death capabilities. The latter category was not treated in that effort. There exists a large class of failure models based on predicting the evolution of pores and failure associated with such microstructures. While the exact mechanisms and corresponding impact on the macroscale behavior remain an active area of research, a large suite of formulations have been proposed combining different features of both pore nucleation and subsequent growth. The most famous of these are based on the popular Gurson model of pore growth derived via micromechanical analysis assuming a plastically incompressible matrix. Numerous other models exist for both growth and nucleation and the Cocks-Ashby growth and Horstemeyer-Gokhale nucleation models have been used successfully in recent Sandia Fracture Challenges. This specific combination is colloquially referred to as the "BCJ-failure model as it has been frequently used with the Bammann-Chisea-Johnson plasticity model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Overview of Elastic Orthotropic Fiber Reinforced Polymer Modular Damage Model for Library of Advanced Materials for Engineering (LAMÉ)

This memo includes the documentation sections for the Library of Advanced Materials for Engineering (LAMÉ) manual for a fiber reinforced polymer composite damage model (Elastic_Orthotropic_FRP_Modular_Damage) in advance of the next Sierra/SM and LAMÉ release consistent with the transition of the model from development to a production capability. This new model capability provides both a set of physically based orthotropic damage criteria as well as orthotropic material softening for woven fiber reinforced polymer composite materials. The documentation sections include short sections on theory, implementation, verification, and user guidance to prescribe the model in a Sierra/SM input file.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Leptonic sum rules from flavour models with modular symmetries

Sum rules in the lepton sector provide an extremely valuable tool to classify flavour models in terms of relations between neutrino masses and mixing parameters testable in a plethora of experiments. In this manuscript we identify new leptonic sum rules arising in models with modular symmetries with residual symmetries. These models simultaneously present neutrino mass sum rules, involving masses and Majorana phases, and mixing sum rules, connecting the mixing angles and the Dirac CP-violating phase. The simultaneous appearance of both types of sum rules leads to some non-trivial interplay, for instance, the allowed absolute neutrino mass scale exhibits a dependence on the Dirac CP-violating phase. We derive analytical expressions for these novel sum rules and present their allowed parameter ranges as well as their predictions at upcoming neutrino experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1991

Continuous system modeling

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Cellier, Francois E.↗
NASA NTRS1999

HSCT Ref-H Transonic Flap Data Base: Wind-Tunnel Test and Comparison with Theory

In cooperation with personnel from the Boeing ANP Laboratory and NASA Langley, a performance test was conducted using the Reference-H 1.675% model ("NASA Modular Model") without nacelles at the NASA Langley 16-Ft Transonic Tunnel. The main objective of the test was to determine the drag reduction achievable with leading-edge and trailing-edge flaps deflected along the outboard wing span at transonic Mach numbers (M = 0.9 to 1.2) for purpose of preliminary design and for comparison with computational predictions. The obtained drag data with flap deflections for Mach numbers of 1.07 to 1.20 are unique for the Reference H wing. Four leading-edge and two trailing-edge flap deflection angles were tested at a mean-wing chord-Reynolds number of about 5.7 million. An outboard-wing leading-edge flap deflection of 81 provides a 4.5 percent drag reduction at M = 1.2 A = 0.2), and much larger values at lower Mach numbers with larger flap deflections. The present results for the baseline (no flaps deflected) compare reasonably well with previous Boeing and NASA Ref-H tunnel tests, including high-Reynolds number NTF results. Viscous CFD simulations using the OVERFLOW thin-layer N.S. method properly predict the observed trend in drag reduction at M = 1.2 as function of leading-edge flap deflection. Modified linear theory properly predicts the flap effects on drag at subsonic conditions (Aero2S code), and properly predicts the absolute drag for the 40 and 80 leading-edge deflection at M = 1.2 (A389 code).

Vijgen, Paul M.↗
DOE OSTI2024

Design Basis Model for Hosting Small Modular Reactors

An aggressive transition from fossil fuels to other types of energy implies the need to construct a large number of nuclear power plants in the near future. However, the real and perceived risks of nuclear energy remain a significant impediment to this transition. This paper describes a comprehensive work process that combines the rigor of model-based systems engineering (MBSE) with 1) the Idaho National Laboratory's (INL) decades of experience with small reactors and with 2) modern project delivery processes. The objective is to reduce the risk of building new facilities or converting existing facilities to nuclear power generation.

42 ENGINEERING↗
DOE OSTI2020

Modular RivGen LCOE Content Model

The Modular RivGen LCOE Content Model contains estimates of levelized cost of energy (LCOE) for three array configurations operating in a theoretical river environment. The LCOE is distinguished by the CapEx, OpEx, and annual energy production and capture for each river environment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

System-Level Integration of Modular Language Models for Real-Time Risk Assessment in Third-Party Risk Management Systems

Large enterprises typically rely on dedicated teams to govern and implement security measures throughout their supply chains, ensuring compliance with enterprise security procedures. There is a significant reliance on Third-Party Risk Management (TPRM) platforms, which often require complete, highly structured information from potential vendors. The review and compliance assurance processes are time- and labor intensive, often requiring several rounds of review between the supply chain security risk management teams, business users, and potential vendors, leading to delays in the supply chain processing and consumer experience. Significant challenges in the risk management paradigm include handling unstructured data in various formats and providing real-time feedback to users to reduce the required review time. This paper presents a novel solution to these challenges. A modular multi-step system architecture is proposed using advances in language processing, specifically for unstructured responses and provides real-time feedback (i.e., 3 seconds) so that users can improve their responses before the TPSRM team review. This novel system architecture will increase information accuracy and significantly reduce time and labor during the review process.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Modular hybrid modeling to increase efficiency, explore structural uncertainty, and allow multidimensional complexity scaling in land surface models

Land surface models (LSMs) are indispensable tools for predicting hydrologic extremes, as well as a particularly uncertain component of Earth system models that has stubbornly resisted the convergence in projections over several successive generations of model intercomparisons. This uncertainty in LSMs is poorly quantified and poorly attributed to specific processes, which has hampered efforts to focus research in reducing uncertainty. This has resulted from sparse sampling of the possible uncertainty space—which is high-dimensional and has contributions from parametric, structural, initial, and boundary condition uncertainties—as an artifact of CMIP-type ensembles of opportunity and limitations inherent in observational benchmarks. A new approach is needed to understand and reduce this uncertainty, based around individual LSMs that can represent the breadth of assumptions represented in current CMIP-type efforts, while at the same time exploring that uncertainty in a systematic way, confronting multiple types of observations, and where justified, replacing process representations with ML-driven emulators. We propose an approach of modular hybrid modeling to address these challenges.

58 GEOSCIENCES↗
DOE OSTI2025

Modeling Small Modular Reactors in GCAM

This study uses the Global Change Analysis Model (GCAM) to examine the critical role and future of nuclear energy in the global energy system, with a focus on the United States. We also analyzed the U.S. government’s new strategic vision for the nuclear energy sector.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1988

An integrated and modular digital modeling approach for the space station electrical power system development

An electrical power system for the Space Station was designed, developed and built. This system provides for electrical power generation, conditioning, storage, and distribution. The initial configuration uses photovoltaic power generation. The power system control is based on a hierarchical architecture to support the requirements of automation. In the preliminary design and technology development phase of the program, various modeling techniques and software tools were evaluated for the purpose of meeting the Space Station power system modeling requirements. Rocketdyne and LeRC jointly selected the EASY5 simulation software, developed by Boeing Computer Services, as a system level modeling tool. The application of the selected analytical modeling approach to represent the entire power system is described. Typical results of model predictions are also summarized. The equipment modeled includes solar arrays, dc to ac converters, resonant inverters, battery storage system, alternator, transmission line, switch gear, and system level microprocessor controls. During the advanced development phase of this program, several models were developed using this approach.

Gombos, Frank J.↗