Engineering Papers⌕ Search

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.

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

At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Phase space effects on fast ion distribution function modeling in tokamaks

Integrated simulations of tokamak discharges typically rely on classical physics to model energetic particle (EP) dynamics. However, there are numerous cases in which energetic particles can suffer additional transport that is not classical in nature. Examples include transport by applied 3D magnetic perturbations and, more notably, by plasma instabilities. Focusing on the effects of instabilities, ad-hoc models can empirically reproduce increased transport, but the choice of transport coefficients is usually somehow arbitrary. New approaches based on physics-based reduced models are being developed to address those issues in a simplified way, while retaining a more correct treatment of resonant wave-particle interactions. The kick model implemented in the tokamak transport code TRANSP is an example of such reduced models. It includes modifications of the EP distribution by instabilities in real and velocity space, retaining correlations between transport in energy and space typical of resonant EP transport. The relevance of EP phase space modifications by instabilities is first discussed in terms of predicted fast ion distribution. Results are compared with those from a simple, ad-hoc diffusive model. It is then shown that the phase-space resolved model can also provide additional insight into important issues such as internal consistency of the simulations and mode stability through the analysis of the power exchanged between energetic particles and the instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2006

An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility

Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.

Conway, Sheila R.↗
DOE OSTI2012

Prediction of Total Dissolved Gas Exchange at Hydropower Dams

Total dissolved gas (TDG) supersaturation in waters released at hydropower dams can cause gas bubble trauma in fisheries resulting in physical injuries and eyeball protrusion that can lead to mortality. Elevated TDG pressures in hydropower releases are generally caused by the entrainment of air in spillway releases and the subsequent exchange of atmospheric gasses into solution during passage through the stilling basin. The network of dams throughout the Columbia River Basin (CRB) are managed for irrigation, hydropower production, flood control, navigation, and fish passage that frequently result in both voluntary and involuntary spillway releases. These dam operations are constrained by state and federal water quality standards for TDG saturation which balance the benefits of spillway operations designed for Endangered Species Act (ESA)-listed fisheries versus the degradation to water quality as defined by TDG saturation. In the 1970s, the United States Environmental Protection Agency (USEPA), under the federal Clean Water Act (Section 303(d)), established a criterion not to exceed the TDG saturation level of 110% in order to protect freshwater and marine aquatic life. The states of Washington and Oregon have adopted special water quality standards for TDG saturation in the tailrace and forebays of hydropower facilities on the Columbia and Snake Rivers where spillway operations support fish passage objectives. The physical processes that affect TDG exchange at hydropower facilities have been studied throughout the CRB in site-specific studies and routine water quality monitoring programs. These data have been used to quantify the relationship between project operations, structural properties, and TDG exchange. These data have also been used to develop predictive models of TDG exchange to support real-time TDG management decisions. These empirically based predictive models have been developed for specific projects and account for both the fate of spillway and powerhouse flows in the tailrace channel and resultant exchange in route to the next downstream dam. Currently, there exists a need to summarize the general finding from operational and structural TDG abatement programs conducted throughout the CRB and for the development of a generalized prediction model that pools data collected at multiple projects with similar structural attributes. A generalized TDG exchange model can be tuned to specific projects and coupled with water regulation models to allow the formulation of optimal daily water regulation schedules subject to water quality constraints for TDG supersaturation. A generalized TDG exchange model can also be applied to other hydropower dams that affect TDG pressures in tailraces and can be used to develop alternative operational and structural measures to minimize TDG generation. It is proposed to develop a methodology for predicting TDG levels downstream of hydropower facilities with similar structural properties as a function of a set of variables that affect TDG exchange; such as tailwater depth, spill discharge and pattern, project head, and entrainment of powerhouse releases. TDG data from hydropower facilities located throughout the northwest region of the United States will be used to identify relationships between TDG exchange and relevant dependent variables. Data analysis and regression techniques will be used to develop predictive TDG exchange expressions for various structural categories.

13 HYDRO ENERGY↗
NASA NTRS2012

An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithm must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty, and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transformation. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.

Daigle, Matthew J.↗
NASA NTRS1985

Report of the LSPI/NASA Workshop on Lunar Base Methodology Development

Groundwork was laid for computer models which will assist in the design of a manned lunar base. The models, herein described, will provide the following functions for the successful conclusion of that task: strategic planning; sensitivity analyses; impact analyses; and documentation. Topics addressed include: upper level model description; interrelationship matrix; user community; model features; model descriptions; system implementation; model management; and plans for future action.

Nozette, Stewart↗
DOE OSTI2025

Gas-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the pebble-bed high-temperature gas-cooled reactor (PB-HTGR) reference plant models for the United States Nuclear Regulatory Commission. These models serve as the foundation for the future development of detailed design evaluation models based on license applications. The reference plant models have been developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, which is the code suite proposed for non-light-water reactor systems safety analysis. It incorporates various simulation tools developed by the Nuclear Energy Advanced Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of the work that was performed was to assess BlueCRAB’s level of readiness for modeling a PB-HTGR. To do so, we first developed numerical models in BlueCRAB that include the key physics for this technology to ensure an adequate level of fidelity for modeling PB-HTGR core performance and for performing multiphysics simulations for equilibrium core conditions and different accident scenarios. Then we simulated transient scenarios, including depressurized and pressurized loss of forced cooling accidents, over-cooling, and control rod withdrawal events with delayed and prompt supercritical reactivity insertions. The analysis in this report includes comparisons of the 2D thermal fluid porous media models in Pronghorn and SAM, and comparisons of coupled SAM/Griffin/SAM and coupled Pronghorn/Griffin for depressurized and pressurized loss of forced cooling, over-cooling, and control rod withdrawal events. In addition, we compare 3D, 2D, and 0D/PKE neutronic models for the two control rod withdrawal scenarios with coupled Pronghorn/Griffin. The comparisons show that the BlueCRAB models lead to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields, such as neutron flux, power, temperature, density, pressure, and velocity, are within the expected ranges, and their distributions can be explained by the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. This work further highlights the need for flexible tools with various levels of fidelity to cover the breadth and depth of needs that may arise in future technical evaluations of the PB-HTGR. We believe that the BlueCRAB capabilities will be a significant asset for confirmatory analyses in order to resolve important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Large Scale DD Simulation Results for Crystal Plasticity Parameters in Fe-Cr And Fe-Ni Systems

The development of viable nuclear energy source depends on ensuring structural materials integrity. Structural materials in nuclear reactors will operate in harsh radiation conditions coupled with high level hydrogen and helium production, as well as formation of high density of point defects and defect clusters, and thus will experience severe degradation of mechanical properties. Therefore, the main objective of this work is to develop a capability that predicts aging behavior and in-service lifetime of nuclear reactor components and, thus provide an instrumental tool for tailoring materials design and development for application in future nuclear reactor technologies. Towards this end goal, the long term effort is to develop a physically based multiscale modeling hierarchy, validated and verified, to address outstanding questions regarding the effects of irradiation on materials microstructure and mechanical properties during extended service in the fission and fusion environments. The focus of the current investigation is on modern steels for use in nuclear reactors including high strength ferritic-martensitic steels (Fe-Cr-Ni alloys). The effort is to develop a predicative capability for the influence of irradiation on mechanical behavior. Irradiation hardening is related to structural information crossing different length scales, such as composition, dislocation, and crystal orientation distribution. To predict effective hardening, the influence factors along different length scales should be considered. Therefore, a hierarchical upscaling methodology is implemented in this work in which relevant information is passed between models at three scales, namely, from molecular dynamics to dislocation dynamics to dislocation-based crystal plasticity. The molecular dynamics (MD) was used to predict the dislocation mobility in body centered cubic (bcc) Fe and its Ni and Cr alloys. The results are then passed on to dislocation dynamics to predict the critical resolved shear stress (CRSS) from the evolution of local dislocation and defects. In this report the focus is on the results obtained from large scale dislocation dynamics simulations. The effect of defect density, materials structure was investigated, and evolution laws are obtained. These results will form the bases for the development of evolution and hardening laws for a dislocation-based crystal plasticity framework. The hierarchical upscaling method being developed in this project can provide a guidance tool to evaluate performance of structural materials for next-generation nuclear reactors. Combined with other tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the models developed will have more impact in improving the reliability of current reactors and affordability of new reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Development of neural network convection parameterizations for climate and NWP models using Cloud Resolving Model simulations

A novel approach based on the neural network (NN) technique is formulated and used for development of a NN ensemble stochastic convection parameterization for climate models. This fast parameterization is built based on data from Cloud Resolving Model (CRM) simulations initialized with and driven by the TOGA-COARE data available for the 4-month winter season from November 1992 to February 1993. CRM simulated data were averaged and projected onto the GCM space of atmospheric states to implicitly define a stochastic convection parameterization. This parameterization is emulated using an ensemble of neural networks (NNs). The developed NNs are trained and tested. The inherent uncertainty of the stochastic convection parameterization derived following this approach is estimated. The newly developed NN convection parameterization has been tested in a diagnostic mode of NCAR CAM. It produced reasonable and promising climate simulations for the TOGA-COARE winter. This paper is devoted to discussion of the concept, methodology, initial results,and the major challenges of development of NN convection parameterizations for climate and numerical weather prediction (NWR) models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Development and assessment of a physics-based simulation model to investigate residential PM 2.5 infiltration across the US housing stock

The Lawrence Berkeley National Laboratory Population Impact Assessment Modeling Framework (PIAMF) was expanded here to enable determination of indoor PM 2.5 concentrations and exposures in a set of 50,000 homes representing the US housing stock. A mass-balance model is used to calculate time-dependent pollutant concentrations within each home. The model includes size- and species-dependent removal mechanisms. The particle model was applied to the housing samples of the Relationship of Indoor, Outdoor, and Personal Air (RIOPA) and The Detroit Exposure and Aerosol Research Study (DEARS) studies to compare model- and measurement-based estimates of indoor PM 2.5 of outdoor origin. Model-derived distributions of infiltration factors (ratio of indoor PM 2.5 of outdoor origin to outdoor PM 2.5 ) are compared to measurement-based distributions obtained in studies conducted in 11 US cities.

42 ENGINEERING↗
DOE OSTI2019

Simultaneous Dependence of the Earthquake-Size Distribution on Faulting Style and Depth

We analyze two high-quality Southern Californian earthquake catalogues, one with focal mechanisms, to statistically model and test for dependencies of the earthquake-size distribution, the b values, on both faulting style and depth. In our null hypothesis, b is assumed constant. We then develop and calibrate one model based only on faulting style, another based only on depth dependence and two models that assume a simultaneous dependence on both parameters. We develop a new maximum-likelihood estimator corrected for the degrees of freedom to assess models' performances. Our results show that all models significantly reject the null hypothesis. The best performing is the one that simultaneously takes account of depth and faulting style. Our results suggest that differential stress variations in the Earth's crust systematically influence b values and that this variability should be considered for contemporary seismic hazard studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Experimental Performance of a Nonlinear Control Strategy to Regulate Temperature of a High-Temperature Solar Reactor

Abstract Despite the significant potential of solar thermochemical process technology for storing solar energy as solid-state solar fuel, several challenges have made its industrial application difficult. It is important to note that solar energy has a transient nature that causes instability and reduces process efficiency. Therefore, it is crucial to implement a robust control system to regulate the process temperature and tackle the shortage of incoming solar energy during cloudy weather. In our previous works, different model-based control strategies were developed namely a proportional integral derivative controller (PID) with gain scheduling and adaptive model predictive control (MPC). These methods were tested numerically to regulate the temperature inside a high-temperature tubular solar reactor. In this work, the proposed control strategies were experimentally tested under various operation conditions. The controllers were challenged to track different setpoints (500 °C, 1000 °C, and 1450 °C) with different amounts of gas/particle flowrates. Additionally, the flow controller was tested to regulate the reactor temperature under a cloudy weather scenario. The ultimate goal was to produce 5 kg of reduced solar fuel magnesium manganese oxide (MgMn2O4) successfully, and the controllers were able to track the required process temperature and reject disturbances despite the system's strong nonlinearity. The experimental results showed a maximum error in the temperature setpoint of less than 0.5% (6 °C), and the MPC controller demonstrated superior performance in reducing the control effort and rejecting disturbances.

Energy & Fuels↗
DOE OSTI2017

Modeling of Aircraft Measurements of Ice Crystal Concentration in the Arctic and a Parameterization for Mixed-Phase Cloud

Abstract In this study, two parameterizations of ice nucleation rate on dust particles are used in a parcel model to simulate aircraft measurements of ice crystal number concentration Ni in the Arctic. The parcel model has detailed microphysics for droplet and ice nucleation, growth, and evaporation with prescribed vertical air velocities. Three dynamic regimes are considered, including large-scale ascent, cloud-top generating cells, and their combination. With observed meteorological conditions and aerosol concentrations, the parcel model predicts the number concentrations of size-resolved ice crystals, which may be compared to aircraft measurements. Model results show rapid changes with height/time in relative humidity, Ni, and thermodynamic phase partitioning, which is not resolved in current climate and weather forecasting models. Parameterizations for ice number and nucleation rate in mixed-phase stratus clouds are thus developed based on the parcel model results to represent the time-integrated effect of some microphysical processes in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The development of yield-based sooting tendency measurements and modeling to enable advanced combustion fuels

This project produced clear evidence that biofuels can reduce particulate emissions from road vehicles compared with petroleum-derived fuels. It also produced fundamental knowledge that can be used to select fuel compositions and engine designs that will maximize this benefit. This information has been disseminated through more than 20 peer-reviewed publications, more than 30 conference presentations, and 5 freely available internet databases and web tools. This project also provided educational opportunities to 17 students at the high school, undergraduate, and graduate levels.

09 BIOMASS FUELS↗