Results for “uncertainty analysis” — Page 20

NASA NTRSDate not supplied

Dragonfly Entry and Descent Flight Mechanics Modeling and Analysis for Mission PDR

Dragonfly is a New Frontiers Program mission led by Johns Hopkins Applied Physics Laboratory (APL) which will deliver a rotorcraft lander to Saturn’s moon, Titan [1]. Relative to previous studies presented, Dragonfly recently passed its mission Preliminary Design Review (PDR) [2]. This study presents the updated design and analysis performed for the Dragonfly mission PDR. The entry vehicle analysis includes the phases of entry and descent prior to cruise stage separation until lander separation. These results discuss the robustness of the overall entry sequence as assessed through a Monte Carlo uncertainty analysis as well as sensitivity analysis.

Modeling↗

DOE OSTI2020

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1991

An introduction to the global positioning system and some geological applications

The fundamental principles of the global positioning system (GPS) are reviewed, with consideration given to geological and geophysical applications and related accuracy requirements. Recent improvements are emphasized which relate to areas such as equipment cost, limitations in the GPS satellite constellation, data analysis, uncertainties in satellite orbits and propagation delays, and problems in resolving carrier phase cycle ambiguities. Earthquake processes and near-fault crustal deformation monitoring have been facilitated by advances in GPS data acquisition and analysis. Horizontal positioning capability has been improved by new satellite constellation, better models, and global tracking networks. New classes of tectonic problems may now be studied through GPS, such as kinematic descriptions of crustal deformation and the measurement of relative plate motion at convergent boundaries. Continued improvements in the GPS are foreseen.

Dixon, T. H.↗

DOE OSTI2026

A Kinetic Model-Driven Techno-Economic Analysis of Plastic Pyrolysis: Linking Process Dynamics to Economic Viability

This study employs a kinetic model integrated into Aspen Plus to predict pyrolysis product distribution under various conditions. A techno-economic assessment calculated the minimum selling price (MSP) of pyrolysis oil under different operating conditions for the baseline capacity of 100 kta, and across eight processing capacities ranging from 30 to 150 kta. The lowest MSP under the baseline capacity is estimated at $\$$420/ton, which is 33% lower than the 2023 average US crude oil price ($\$$74.6/bbl, equivalent to $\$$634/ton based on the density of pyrolysis oil). Under Monte Carlo simulation, accounting for variability in key economic and technical parameters, the mean MSP is estimated at $\$$1137/ton. The economic viability depends on feedstock price remaining below $\$$320/ton, defining the break-even feedstock price threshold. Sensitivity analysis further identifies capital investment and transportation cost as key economic drivers. Capacities beyond 90 kta show limited economies of scale benefits. Reducing product storage time cuts capital costs by 7% but raises operational risk. Uncertainty analysis suggests the economic feasibility of pyrolysis oil is unlikely to compete with crude oil without policy incentives.

petrochemicals↗

DOE OSTI2020

Increasing the SATS Uncertainty Safety Margin

The Surveillance and Test System (SATS) checks the functionality of ATR’s Plant Protection System (PPS). The analogue linearity test checks that the SATS analog and digital conversions are accurate to +/- 61 mVdc. This project analyzes whether this accuracy range can be increased without impacting the uncertainty analysis of the PPS system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Deep learning of parameterized equations with applications to uncertainty quantification

We propose a learning algorithm for discovering unknown parameterized dynamical systems by using observational data of the state variables. Our method is built upon and extends the recent work of discovering unknown dynamical systems, in particular those using deep neural network (DNN). We propose a DNN structure, largely based upon the residual network (ResNet), to not only learn the unknown form of the governing equation but also take into account the random effect embedded in the system, which is generated by the random parameters. Once the DNN model is successfully constructed, it is able to produce system prediction over longer term and for arbitrary parameter values. For uncertainty quantification, it allows us to conduct uncertainty analysis by evaluating solution statistics over the parameter space.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Experimental uncertainty survey and assessment

An uncertainty analysis and assessment of the specific impulse determination during Space Shuttle Main Engine testing is reported. It is concluded that in planning and designing tests and in interpreting the results of tests, the bias and precision components of experimental uncertainty should be considered separately. Recommendations for future research efforts are presented.

Coleman, Hugh W.↗

DOE OSTI2024

Identifying Hydropower Operational Flexibilities in Presence of Streamflow and Net-load Uncertainty (Final Technical report)

In the existing operations, hydropower contributions to future system flexibility are generally modeled while maintaining traditional operating rules and constraints in supporting grid operation, such as the balancing of variable renewable energy production. Moreover, operation of large scale hydropower systems on major rivers has been investigated for decades, utilizing various systems engineering approaches, with the evolving electric grid, as the result of renewable resources integration, compounded by the changing climate (variability of river flows, intensification of hydrologic cycle resulting in more frequent extreme events) affecting water availability, the need for more advanced stochastic modeling and effective uncertainty analysis approaches have become necessary. The research results supported by this funding and presented in this report provide a new look at hydropower operational flexibility enforced by the changes identified above. Understanding how hydropower operates in response to the underlying uncertainties with respect to the system constraints is crucial in identifying its operational flexibility potentials. In this project, the flexibility of the operating hydropower facility is described by capturing uncertainties in both water and power system and formulating the operations as a multistage stochastic optimization problem. The proposed approach supports short- to seasonal-term operations and planning decision horizons.

13 HYDRO ENERGY↗

DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗

DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗

DOE OSTI2024

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton–proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV. Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb –1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

Dragonfly Entry and Descent Flight Mechanics Modeling and Analysis

Dragonfly is a New Frontiers Program mission that will deliver a rotorcraft lander to Saturn’s moon, Titan [1]. The focus of this work is to analyze the trajectory from cruise stage separation until lander separation. This analysis is done by the NASA Langley (LaRC) EDL team using Program to Optimize Trajectories II (POST2)[2]. This poster provides an overview of the current design and the robustness of the overall entry sequence as assessed using a Monte Carlo uncertainty analysis. This mission is led by Johns Hopkins Applied Physics Laboratory (APL), presented here is the design and analysis as of the Dragonfly EDL Assembly Preliminary Design Review (PDR).

Modeling↗

DOE OSTI2024

Monte Carlo Perturbation Analysis of Fuel Temperature Variations in the MCNP Model of the Annular Core Research Reactor

The Annular Core Research Reactor (ACRR) Monte Carlo N-Particle (MCNP) model is used by ACRR reactor operators and experiment designers at Sandia National Laboratories for a variety of computational calculations ranging from reactor kinetics parameter estimates and safety analyses to experimental planning. To understand the dominant source of uncertainty within the MCNP model, perturbations in temperature were applied to individual ACRR MCNP fuel rods. Fuel rod temperatures were randomly sampled from a uniform distribution from operational temperatures to quantify temperature-related uncertainty effects. Stochastic mixing was used to blend the cross sections of the desired temperatures using the MCNP continuous and Thermal Neutron Scattering Treatment [S(α,β)] libraries in ENDF/B-VII.1. Furthermore, this uncertainty analysis produced a 640 row × 640 column correlation and covariance matrix of the neutron energy spectra. Positive covariance was produced around the 1-MeV region and the 0.2-eV region. Correlation was found in the thermal and fast energy regions, but no correlation was observed in the slowing-down energy region because interactions in this region are not dominated by fuel.

ACRR↗

NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗

NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗

DOE OSTI2023

Computational Fluid Dynamics Study of a Cross-Flow Marine Hydrokinetic Turbine and the Combined Influence of Struts and Helical Blades: Preprint

A computational fluid dynamics study was performed for a cross-flow marine hydro-kinetic turbine. The analysis was done in three dimensions and used the unsteady Reynolds averaged Navier-Stokes solver in the commercial code STAR-CCM+. The base turbine configuration is the RivGen® Turbine, designed by the Ocean Renewable Power Company (ORPC). A convergence and uncertainty analysis was performed for both the spatial and temporal discretization; this was done using the base configuration which features support struts and helical foils. The proposed study aims to compare the impact of the struts on both power performance and blade loading for helical and straight blades.

CFD↗

NASA NTRS2016

Landing Gear Noise Prediction and Analysis for Tube-and-Wing and Hybrid-Wing-Body Aircraft

Improvements and extensions to landing gear noise prediction methods are developed. New features include installation effects such as reflection from the aircraft, gear truck angle effect, local flow calculation at the landing gear locations, gear size effect, and directivity for various gear designs. These new features have not only significantly improved the accuracy and robustness of the prediction tools, but also have enabled applications to unconventional aircraft designs and installations. Systematic validations of the improved prediction capability are then presented, including parametric validations in functional trends as well as validations in absolute amplitudes, covering a wide variety of landing gear designs, sizes, and testing conditions. The new method is then applied to selected concept aircraft configurations in the portfolio of the NASA Environmentally Responsible Aviation Project envisioned for the timeframe of 2025. The landing gear noise levels are on the order of 2 to 4 dB higher than previously reported predictions due to increased fidelity in accounting for installation effects and gear design details. With the new method, it is now possible to reveal and assess the unique noise characteristics of landing gear systems for each type of aircraft. To address the inevitable uncertainties in predictions of landing gear noise models for future aircraft, an uncertainty analysis is given, using the method of Monte Carlo simulation. The standard deviation of the uncertainty in predicting the absolute level of landing gear noise is quantified and determined to be 1.4 EPNL dB.

Guo, Yueping↗

DOE OSTI2023

Computational Fluid Dynamics Study of a Cross-Flow Marine Hydrokinetic Turbine and the Combined Influence of Struts and Helical Blades

A computational fluid dynamics study was performed for a cross-flow marine hydrokinetic turbine. The analysis was done in three dimensions and used the unsteady Reynolds-averaged Navier-Stokes solver in the commercial code STAR-CCM+. The base turbine configuration is the RivGen(R) Turbine, designed by the Ocean Renewable Power Company. A convergence and uncertainty analysis was performed for both the spatial and temporal discretization; this was done using the base configuration, which features support struts and helical foils. Both struts and helical blades introduce three-dimensional flow effects, influencing the complex flow phenomenon of dynamic stall. The study compares the relative impact of struts on power performance and blade loading for both helical and straight blades, and found that for this turbine the relative loss in power from struts was lower with helical blades.

CFD↗