SEARCH · Engineering Papers

Results for “Model based development”

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.

SourceResearch connectionFrom yearThrough year

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

At least 667 records · Page 37

All sources NASA NTRS DOE OSTI

NASA NTRS2018

Integrated Real-Time Modeling System for Heliospheric Space Weather Forecasting

The Sun lies at the center of space weather and is the source of its variability. The primary input to coronal and solar wind models is the activity of the magnetic field in the solar photosphere. What is needed is to develop physics-based models for the dynamics of the magnetic field from the deep convection zone of the Sun to the corona with the goal of providing robust near real-time boundary conditions at the base of space weather forecast models. NASA strategic capabilities efforts toward this goal will be summarized during the talk. These have the objective to enable characterizing and predicting the magnetic field structure and flow dynamics of the Sun by assimilating data from helioseismology and magnetic field observations into physics-based realistic magnetohydrodynamics (MHD) simulations. It is argued that an effort in integrating first-principle modeling of solar magnetism and flow dynamics with real-time observational data via advanced data assimilation methods is needed for transformative steps in space weather research and prediction.

Mansour, Nagi N.↗

DOE OSTI2011

Joint inversion of marine seismic AVA and CSEM data using statistical rock-physics models and Markov random fields: Stochastic inversion of AVA and CSEM data

Joint inversion of seismic AVA and CSEM data requires rock-physics relationships to link seismic attributes to electrical properties. Ideally, we can connect them through reservoir parameters (e.g., porosity and water saturation) by developing physical-based models, such as Gassmann’s equations and Archie’s law, using nearby borehole logs. This could be difficult in the exploration stage because information available is typically insufficient for choosing suitable rock-physics models and for subsequently obtaining reliable estimates of the associated parameters. The use of improper rock-physics models and the inaccuracy of the estimates of model parameters may cause misleading inversion results. Conversely, it is easy to derive statistical relationships among seismic and electrical attributes and reservoir parameters from distant borehole logs. In this study, we develop a Bayesian model to jointly invert seismic AVA and CSEM data for reservoir parameter estimation using statistical rock-physics models; the spatial dependence of geophysical and reservoir parameters are carried out by lithotypes through Markov random fields. We apply the developed model to a synthetic case, which simulates a CO{sub 2} monitoring application. We derive statistical rock-physics relations from borehole logs at one location and estimate seismic P- and S-wave velocity ratio, acoustic impedance, density, electrical resistivity, lithotypes, porosity, and water saturation at three different locations by conditioning to seismic AVA and CSEM data. Comparison of the inversion results with their corresponding true values shows that the correlation-based statistical rock-physics models provide significant information for improving the joint inversion results.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Supplying materials needed for grain growth characterizations of nano-grained UO 2

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructure based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2 . The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Synchrotron characterization of nanograined UO 2 grain growth

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2016

Hollow Cathode Assembly Development for the HERMeS Hall Thruster

To support the operation of the HERMeS 12.5 kW Hall Thruster for NASA's Asteroid Redirect Robotic Mission, hollow cathodes using emitters based on barium oxide impregnate and lanthanum hexaboride are being evaluated through wear-testing, performance characterization, plasma modeling, and assessment of system implementation concerns. This paper will present the development approach used to assess the cathode emitter options. A 2,000-hour wear-test of development model barium-oxide-based (BaO) hollow cathode is being performed as part of the development plan. The cathode was operated with an anode that simulates the HERMeS hall thruster operating environment. Cathode discharge performance has been stable with the device accumulating 740 hours at the time of this report. Cathode operation (i.e. discharge voltage and orifice temperature) was repeatable during period variation of discharge current and flow rate. The details of the cathode assembly operation during the wear-test will be presented.

Plasma Sources/Technology↗

DOE OSTI2015

Total Dissolved Gas Prediction and Optimization in RIVERWARE

Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results indicate excellent model performance with coefficient of determination values exceeding 92% for all sites. This approach enables model extension to an increasingly wider array of hydropower plants, i.e., with the proper data input, TDG uptake can be calculated independent of actual physical component design. The TDG model is used as a module in the systematic optimization framework of RiverWare, a river and reservoir modeling tool used by federal agencies, public utility districts, and other dam owners and operators to forecast, schedule, and manage hydropower assets. The integration and testing of the TDG module within RiverWare, led by University of Colorado's Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), will allow users to generate optimum system schedules based on the minimization of TDG. Optimization analysis and added value will be quantified as system wide reductions in TDG achieved while meeting existing hydropower constraints. Future work includes the development of a method to predict downstream reservoir forebay TDG levels as a function of upstream reservoir tailrace TDG values based on river hydrodynamics, hydro operations, and reservoir characteristics. Once implemented, a holistic model that predicts both TDG uptake and transport will give hydropower operators valuable insight into how system-wide environmental effects can be mitigated while simultaneously balancing stakeholder interests.

13 HYDRO ENERGY↗

DOE OSTI2018

Rheological Evolution of Ti-Bearing Slag with Different Volume Fractions of TiN

The effect of the volume fraction of TiN (0 to 4.27 vol pct) on the rheological behaviors of Ti-bearing slag, including the viscosity and the constitutive equation, was investigated using a Brookfield rheometer at 1773 K. With the increasing TiN, the viscosity and the shear stress increased substantially, and the slag is converted from Newtonian to non-Newtonian. When the slag samples were dispersed with TiN (1.00 to 4.27 vol pct), the measured viscosities were greater than those estimated by the Einstein–Roscoe equation, and the complex internal structure was suggested to be responsible for the extra enhancement of the viscosity beyond that caused by TiN itself. The viscosity curves of the slag samples containing TiN (1.00 to 4.27 vol pct) were divided into three regions depending on the critical shear rate and the initial shear rate. In the Newtonian region, the apparent volume fraction of TiN was defined and used to develop a semiempirical model based on the Einstein–Roscoe equation to describe the viscosity. In the two non-Newtonian regions, the shear rate, the yield stress, and the viscosity differences between the non-Newtonians regions and the Newtonian regions were applied in developing the viscosity models.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Validation of Photovoltaic Modeling Tool HelioScope Against Measured Data

HelioScope is a cloud-based solar design software developed by Folsom Labs to model arrays based on physical design. Folsom Labs received a grant from the Department of Energy for the National Renewable Energy Laboratory to validate the performance of HelioScope's simulation engine against measured PV system performance. This study builds upon previous validation work by NREL of multiple other PV modeling tools, using the same fixed-tilt systems with available system specifications. HelioScope designs were set up using the same system specifications and concurrent weather data as were used in previous studies. The predicted performance results from the simulations were compared with measured data and to performance predictions by other PV modeling tools.

14 SOLAR ENERGY↗

NASA NTRS1981

A theory of the n-i-p silicon solar cell

A computer model has been developed, based on an analytical theory of the high base resistivity BSF n(+)(pi)p(+) or p(+)(nu)n(+) silicon solar cell. The model makes very few assumptions and accounts for nonuniform optical generation, generation and recombination in the junction space charge region, and bandgap narrowing in the heavily doped regions. The paper presents calculated results based on this model and compares them to available experimental data. Also discussed is radiation damage in high base resistivity n(+)(pi)p(+) space solar cells.

Goradia, C.↗

NASA NTRS2002

Flight Dynamic Model Exchange using XML

The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.

Jackson, E. Bruce↗

DOE OSTI2021

NEAMS TH CRAB

The MOOSE framework is a library designed to make it straightforward for physicists and engineers to model partial differential equations using finite element and finite volume methods. Finite elements have been a part of the framework library since MOOSE's inception over a decade ago. Initial finite volume capability, however, was added only as recently as May of 2020. Since that time, significant work has been conducted to develop fluid modeling capability based on the finite volume method. Much of this work has taken place in MOOSE's navier_stokes module and in the NEAMS program's coarse mesh CFD code Pronghorn. We report here on development in MOOSE and Pronghorn of incompressible, porous incompressible, and weakly compressible finite volume simulation capabilities and their application to modeling of MSR and FHR advanced reactor concepts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Woven ceramic matrix composite surrogate model based on physics-informed recurrent neural network

A recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear constitutive behavior of woven ceramic matrix composites (CMCs) driven by matrix damage at multiple length scales. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the multiscale generalized method of cells (MSGMC) approach coupled with a matrix damage model. This coupling permits simulating the nonlinear behavior of woven CMCs based on constituent response at the micro-, meso-, and macroscales. The multiscale repeating unit cell is loaded under non-monotonic conditions including multiple load / unload cycles and tension / compression. The fiber volume fraction as well as the intra- and intertow void volume fractions are also varied in the generation of training data. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input strain sequence and fiber and void volume fractions, the resulting stress versus strain response while satisfying physical constraints such as positive semi-definiteness of the tangent stiffness matrix and linear elastic unloading. Further, the trained surrogate model effectively matches the stress versus strain response and successfully predicts the tangent modulus throughout the loading regime. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex architectures, nonlinear multiaxial material response, and under non-monotonic loading conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Report on SNL RCBC control options

The attractive performance of the S-CO 2 recompression cycle arises from the thermo-physical properties of carbon dioxide near the critical point. However, to ensure efficient operation of the cycle near the critical point, precise control of the heat removal rate by the Printed Circuit Heat Exchanger (PCHE) upstream of the main compressor is required. Accomplishing this task is not trivial because of the large variations in fluid properties with respect to temperature and pressure near the critical point. The use of a model-based approach for the design of a robust feedback regulator is being investigated to achieve acceptable control of heat removal rate at different operating conditions. A first step in this procedure is the development of a dynamic model of the heat exchanger. In this work, a one-dimensional (1-D) control-oriented model of the PCHE was developed using the General Plant Analyzer and System Simulator (GPASS) code. GPASS is a transient simulation code that supports analysis and control of power conversion cycles based on the S-CO 2 Brayton cycle. This modeling capability was used this fiscal year to analyze experiment data obtained from the heat exchanger in the SNL recompression Brayton cycle. The analysis suggested that the error in the water flowrate measurement was greater than required for achieving precise control of heat removal rate. Accordingly, a new water flowmeter was installed, significantly improving the quality of the measurement. Comparison of heat exchanger measurements in subsequent experiments with code simulations yielded good agreement establishing a reliable basis for the use of the GPASS PCHE model for future development of a model-based feedback controller.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2003

An advanced model-based diagnosis engine

We have developed a new and powerful diagnosis engine that overcomes the limitations of the existing systematic methods of general diagnosis through a two-fold approach. First, we propose a novel and compact reconstruction of the General Diagnosis Engine, one of the most fundamental approaches to model-based diagnoses. We then present a novel algorithmic approach for calculation of minimal diagnosis set.

model-based diagnosis hitting set problem integer ↗

NASA NTRS1993

Heat pipe cooled heat rejection subsystem modelling for nuclear electric propulsion

NASA LeRC is currently developing a FORTRAN based computer model of a complete nuclear electric propulsion (NEP) vehicle that can be used for piloted and cargo missions to the Moon or Mars. Proposed designs feature either a Brayton or a K-Rankine power conversion cycle to drive a turbine coupled with rotary alternators. Both ion and magnetoplasmodynamic (MPD) thrusters will be considered in the model. In support of the NEP model, Rocketdyne is developing power conversion, heat rejection, and power management and distribution (PMAD) subroutines. The subroutines will be incorporated into the NEP vehicle model which will be written by NASA LeRC. The purpose is to document the heat pipe cooled heat rejection subsystem model and its supporting subroutines. The heat pipe cooled heat rejection subsystem model is designed to provide estimate of the mass and performance of the equipment used to reject heat from Brayton and Rankine cycle power conversion systems. The subroutine models the ductwork and heat pipe cooled manifold for a gas cooled Brayton; the heat sink heat exchanger, liquid loop piping, expansion compensator, pump and manifold for a liquid loop cooled Brayton; and a shear flow condenser for a K-Rankine system. In each case, the final heat rejection is made by way of a heat pipe radiator. The radiator is sized to reject the amount of heat necessary.

Moriarty, Michael P.↗

NASA NTRS2013

Systems Engineering Interfaces: A Model Based Approach

Currently: Ops Rev developed and maintains a framework that includes interface-specific language, patterns, and Viewpoints. Ops Rev implements the framework to design MOS 2.0 and its 5 Mission Services. Implementation de-couples interfaces and instances of interaction Future: A Mission MOSE implements the approach and uses the model based artifacts for reviews. The framework extends further into the ground data layers and provides a unified methodology.

Advanced Multi-Mission Operations System (AMMOS)↗

DOE OSTI2022

A guideline to document occupant behavior models for advanced building controls

The availability of computational power, and a wealth of data from sensors have boosted the development of model-based predictive control for smart and effective control of advanced buildings in the last decade. More recently occupant-behavior models have been developed for including people in the building control loops. However, while important objectives of scientific research are reproducibility and replicability of results, not all information is available from published documents. Therefore, the aim of this paper is to propose a guideline for a thorough and standardized occupant-behavior model documentation. For that purpose, the literature screening for the existing occupant behavior models in building control was conducted, and the occupant behavior modeling processes were studied to extract practices and gaps for each of the following phases: problem statement, data collection, and preprocessing, model development, model evaluation, and model implementation. Here, the literature screening pointed out that the current state-of-the-art on model documentation shows little unification, which poses a particular burden for the model application and replication in field studies. In addition to the standardized model documentation, this work presented a model-evaluation schema that enabled benchmarking of different models in field settings as well as the recommendations on how OB models are integrated with the building system.

Building control↗

DOE OSTI2022

On the mechanism of marine fouling-prevention performance of oil-containing silicone elastomers

For many decades, silicone elastomers with oil incorporated have served as fouling-release coating for marine applications. In a comprehensive study involving a series of laboratory-based marine fouling assays and extensive global field studies of up to 2-year duration, we compare polydimethylsiloxane (PDMS) coatings of the same composition loaded with oil via two different methods. One method used a traditional, one-pot pre-cure oil addition approach (o-PDMS) and another method used a newer post-cure infusion approach (i-PDMS). The latter displays a substantial improvement in biofouling prevention performance that exceeds established commercial silicone-based fouling-release coating standards. We interpret the differences in performance between one-pot and infused PDMS by developing a mechanistic model based on the Flory–Rehner theory of swollen polymer networks. Using this model, we propose that the chemical potential of the incorporated oil is a key consideration for the design of future fouling-release coatings, as the improved performance is driven by the formation and stabilization of an anti-adhesion oil overlayer on the polymer surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗