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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Valenti, Elizabeth↗
NASA NTRSDate not supplied

Flux Comparison of Master-8 and Ordem 3.1 Modelled Space Debris Population

With ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model(ORDEM) 3.1, the two premier orbital debris engineering models have been officially released. The two models come with significant enhancements and now represent state-of-the-art orbital debris modelling for their respective agencies. Both models provide the community with estimates of the space debris environment from low Earth orbit (LEO) up to at least geostationary altitude. The MASTER population is an event-based simulation of all known events that generate debris and objects that are part of the U.S. Space Surveillance Network (SSN) catalog, which provides coverage of objects with diameters down to approximately 10cm in LEO and 1 m in geosynchronous Earth orbit (GEO). Different models are used to simulate the artificial objects and their orbit evolution over time. These models are called “sources” since they assign an origin to each individual object and consist of fragments, solid rocket motor (SRM) remainders, sodium-potassium(NaK) droplets, paintflakes, ejecta, and multi-layer insulation (MLI) fragments. The objects from each source are characterized by having individual release mechanisms, as well as orbital distributions, material composition, size, and mass distributions. Dedicated radar and telescope observation data is used to calibrate the model for objects larger than 1 cm in LEO and larger than 10 cm in GEO. For calibrating the small-sized objects, below 1 cm, impact data from returned surfaces are analyzed. Because the >1cm object population is dominated by fragments, the fragmentation event database was updated to include new events, as well as re-evaluate past events. Special attention was drawn to re-evaluating theFengyun-1C anti-satellite test from 2007 and Cosmos-Iridium collision event from 2009 since these events shape the fragment population because of their severity. After 2009, the two largest fragmentations in terms of number of tracked debris are the Briz-M explosion in 2012 and the NOAA-16explosion in 2015. In total, there are 261 confirmed fragmentations in the database up to November 2016.The baseline population for ORDEM 3.1 is based on the U.S. SSN catalog, and observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller size regions. These regions are not well-covered by the SSN catalog yet may pose the greatest threat to operational spacecraft. The NASA Standard Satellite Breakup Model is used to generate fragments greater than 1mm from collisions and explosions, and these fragment populations are scaled using ground-based radar data. Specific major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos2251 debris clouds, and unique populations, such as NaK droplets, were re-examined, modelled, and added to the ORDEM environment separately. Optical measurement data is used to model the GEO population down to 10 cm. The debris environment is propagated using NASA’s LEO-to-GEO Environment Debris model, and future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically. The environment from a few millimetres down to 10 𝜇m is modelled using a special degradation model where small particles are generated from intact spacecraft and rocket bodies, then the populations are scaled to fit in situ cratering data from Space Shuttle returned surfaces. Fragments smaller than 10 cm are differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to upper stages and spacecraft. This paper will discuss the MASTER and ORDEM approaches for modelling populations and compare fluxes for specific orbits, including sun-synchronous, ISS-altitude, geosynchronous transfer, and GEO. In the end, a conclusion is drawn towards the importance of having multiple fundamentally different, yet validated, models to estimate the space debris population.

Andre Horstmann↗
DOE OSTI2021

Geant4Reweight: a framework for evaluating and propagating hadronic interaction uncertainties in Geant4

Geant4Reweight is an open-source C++ framework that allows users to weight tracks produced by the Geant4 particle transport Monte Carlo simulation according to hadron interaction cross section variations and estimate uncertainties in Geant4 interaction models by comparing the simulation’s hadron interaction cross section predictions to data. The ability to weight hadron transport as simulated by Geant4 is crucial to the propagation of systematic uncertainties related to secondary hadronic interactions in current and upcoming neutrino oscillation experiments, including MicroBooNE, NOvA, and DUNE, aswell as hadron test beam experiments such as ProtoDUNE. Here, we provide motivation for weighting hadron tracks in Geant4 in the context of systematic uncertainty propagation, a description of Geant4’s transport simulation technique, and a description of our weighting technique and fitting framework in the momentum range 0–10 GeV/c, which is typical for the hadrons produced by neutrino interactions in these experiments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗
DOE OSTI2018

Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions

Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period: (1) bale-delivery scenario with biorefinery uptime varying from 20 to 85%; (2) pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%; and (3) pellet-delivery scenario with depot and biorefinery uptime at 85%. In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.

09 BIOMASS FUELS↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗
DOE OSTI2024

GLAD-M35: a joint P and S global tomographic model with uncertainty quantification

We present our third and final generation joint P and S global adjoint tomography (GLAD) model, GLAD-M35, and quantify its uncertainty based on a low-rank approximation of the inverse Hessian. Starting from our second-generation model, GLAD-M25, we added 680 new earthquakes to the database for a total of 2160 events. New P-wave categories are included to compensate for the imbalance between P- and S-wave measurements, and we enhanced the window selection algorithm to include more major-arc phases, providing better constraints on the structure of the deep mantle and more than doubling the number of measurement windows to 40 million. Two stages of a Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton inversion were performed, each comprising five iterations. With this BFGS update history, we determine the model’s standard deviation and resolution length through randomized singular value decomposition.

58 GEOSCIENCES↗
DOE OSTI2020

Validation of (not-historical) large-event near-fault ground-motion simulations for use in civil engineering applications

Ground-motion simulations generated from physics-based wave propagation models are gaining increasing interest in the engineering community for their potential to inform the performance-based design and assessment of infrastructure residing in active seismic areas. A key prerequisite before the ground-motion simulations can be used with confidence for application in engineering domains is their comprehensive and rigorous investigation and validation. This article provides a four-step methodology and acceptance criteria to assess the reliability of simulated ground motions of not historical events, which includes (1) the selection of a population of real records consistent with the simulated scenarios, (2) the comparison of the distribution of Intensity Measures (IMs) from the simulated records, real records, and Ground-Motion Prediction Equations (GMPEs), (3) the comparison of the distribution of simple proxies for building response, and (4) the comparison of the distribution of Engineering Demand Parameters (EDPs) for a realistic model of a structure. Specific focus is laid on near-field ground motions (<10km) from large earthquakes (M w 7), for which the database of real records for potential use in engineering applications is severely limited. The methodology is demonstrated through comparison of (2490) near-field synthetic records with 5 Hz resolution generated from the Pitarka et al (2019) kinematic rupture model with a population of (38) pulse-like near-field real records from multiple events and, when applicable, with NGA-W2 GMPEs. Lastly, the proposed procedure provides an effective method for informing and advancing the science needed to generate realistic ground-motion simulations, and for building confidence in their use in engineering domains.

42 ENGINEERING↗
DOE OSTI2024

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

FISPACT-II: An Advanced Simulation System for Activation, Transmutation and Material Modelling

Fispact-II is a code system and library database for modelling activation-transmutation processes, depletion-burn-up, time dependent inventory and radiation damage source terms caused by nuclear reactions and decays. The Fispact-II code, written in object-style Fortran, follows the evolution of material irradiated by neutrons, alphas, gammas, protons, or deuterons, and provides a wide range of derived radiological output quantities to satisfy most needs for nuclear applications. It can be used with any ENDF-compliant group library data for nuclear reactions, particle-induced and spontaneous fission yields, and radioactive decay (including but not limited to TENDL-2015, ENDF/B-VII.1, JEFF-3.2, JENDL-4.0u, CENDL-3.1 processed into fine-group-structure files, GEFY-5.2 and UKDD-16), as well as resolved and unresolved resonance range probability tables for self-shielding corrections and updated radiological hazard indices. The code has many novel features including: extension of the energy range up to 1 GeV; additional neutron physics including self-shielding effects, temperature dependence, thin and thick target yields; pathway analysis; and sensitivity and uncertainty quantification and propagation using full covariance data. The latest ENDF libraries such as TENDL encompass thousands of target isotopes. Nuclear data libraries for Fispact-II are prepared from these using processing codes PREPRO, NJOY and CALENDF. These data include resonance parameters, cross sections with covariances, probability tables in the resonance ranges, PKA spectra, kerma, dpa, gas and radionuclide production and energy-dependent fission yields, supplemented with all 27 decay types. All such data for the five most important incident particles are provided in evaluated data tables. The Fispact-II simulation software is described in detail in this paper, together with the nuclear data libraries. The Fispact-II system also includes several utility programs for code-use optimisation, visualisation and production of secondary radiological quantities. Included in the paper are summaries of results from the suite of verification and validation reports available with the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock salt are multi-porosity porous media in which pores of different scales may co-exist in the host matrix. When fractures propagate in these multi-porosity materials, these pores may enlarge and coalesce and therefore change the magnitude and the principal directions of the effective permeability tensors. The pore-fluid inside the cracks and the pores of host matrix may interact and exchange fluid mass, but the difference in hydraulic properties of these pores often means that a single homogenized effective permeability tensor field is insufficient to characterize the evolving hydraulic properties of these materials at smaller time scale. Furthermore, the complexity of the hydro-mechanical coupling process and the induced mechanical and hydraulic anisotropy originated from the micro-fracture and plasticity at grain scale also makes it difficult to propose, implement and validate separated macroscopic constitutive laws for numerical simulations. Here this article presents a hybrid data-driven method designed to capture the multiscale hydro-mechanical coupling effect of porous media with pores of various different sizes. At each scale, data-driven models generated from supervised machine learning are hybridized with classical constitutive laws in a directed graph that represents the numerical models. By using sub-scale simulations to generate database to train material models, an offline homogenization procedure is used to replace the up-scaling procedure to generate cohesive laws for localized physical discontinuities at both grain and specimen scales. Through a proper homogenization procedure that preserves spatial length scales, the proposed method enables field-scale simulations to gather insights from meso-scale and grain-scale micro-structural attributes. This method is proven to be much more computationally efficient than the classical DEM–FEM or FEM2 approach while at the same time more robust and flexible than the classical surrogate modeling approach. Due to the usage of bridging-scale technique, the proposed model may provide multiple opportunities to incorporate different types of simulations and experimental data across different length scales for machine learning. Numerical issues will also be discussed.

42 ENGINEERING↗
DOE OSTI2016

Thermal Diffusivity Measurement of Irradiated SiC-SiC Composite Material

Silicon Carbide fiber and matrix composite (SiC-SiC) is being considered as a fuel cladding candidate because of its high melting point, low susceptibility to corrosion, good thermal and mechanical shock resistance, and low degradation of mechanical properties under irradiation. The thermal properties of SiC-SiC composite depend heavily on the fabrication process, thus cannot be simply referenced from available database. Similarly, the influence of irradiation on SiC-SiC composite thermal properties needs to be measured to provide general trends of property degradation. For ion irradiated samples, the damaged layer is only a few to a few tens of micrometers. It is impossible to directly measure the bulk property change of a SiC-SiC composite because of the thin, damaged layer. This paper focuses on a methodology that is based on microscale measurement of fiber and matrix properties to determine the overall bulk property change due to ion irradiation. Laser-based photothermal reflectance technique is one of the ideal methods to measure local thermal conductivity and diffusivity with high spatial resolution. The main principle of this technique is to heat the solid sample using an intensity-modulated laser, and scan the sample with a constant intensity continuous-wave (CW) laser to detect the phase lag of the thermal wave propagation. On bulk, isotropic material, if the heating laser intensity is modulated as a sine wave, thermal diffusivity of the sample can be derived from the phase lag, scan distance and modulation frequency in a straight forward manner. By using more specific analytical models, thermal conductivity and diffusivity in complicated cases, such as layered structure materials, composite materials, and/or anisotropic materials, are measurable as well. In this work, a new measurement approach of SiC-SiC composite thermal diffusivity is presented. Due to the micrometer spatial resolution of the photothermal reflectance technique, the measurements are performed locally on fibers along both radial and axial directions, and on the matrix. The influence of Silicon ion irradiation (75 MeV, 10 dpa) is then examined by comparing the experimental results of samples before and after irradiation. (authors)

36 MATERIALS SCIENCE↗
NASA NTRS2022

22” ADP Fan Rig Liners Design Report

A liner design study was conducted as part of a cooperative effort between five (5) government/industry teams that together seek to demonstrate the technology for designing and manufacturing acoustic liners that are twenty five percent (25%) more efficient than 1992 technology liners. The study emphasized teaming collaboration. The improved liners were designed by Pratt & Whitney and Boeing Airplane Company and built by Rohr Inc, and will be tested in the NASA/P& W 22-inch ADP fan rig at NASA Lewis Research Center's 9' x 15' wind tunnel. Design guidelines and decisions were made collectively during monthly design review telecons and at the formal final design review. The tools that were used to design the new improved liners were not new, but the process that was developed as part of this study that led into the evaluation and selection of the final and best liner designs is new. Until now, the liner design process as practiced by different industry teams varied greatly. Some procedures were based on empirical liner attenuation databases which could not adequately account for engine-to-engine hardwall fan noise spectral differences, while others were entirely theoretical. And regardless of which method one chose, the major difficulty was still the lack of understanding and knowledge of the actual hardwall fan source noise modal structure and farfield SPL spectra. The NASA-led effort to attempt actual measurements of the fan source noise modal structure by means of the rotating microphone array is expected to contribute significantly to the understanding of the nature of the fan tone noise modes, but the application to broadband noise is still a long way off. The new design process included consideration of the measured fan tone modes, but for the majority of the spectra a separate, systematic process was used. It is a common practice in the engine/nacelle industry that acoustic liners for new products are designed before actual measured hardwall engine far-field noise spectra are available. Target noise spectra are normally derived from existing engine noise databases with some adjustments to absolute SPLs and frequencies. This practice has been acceptable as long as the new engine was a derivative of the base engine. However, in the case of the ADP, the transition from a current engine base is too - great, and the adjustments could not adequately account for the quantum changes in SPL spectral differences. Examples were the 1992 single degree of freedom (SDOF) inlet and aft liners (designed by P&W) that would be used as the baseline liners against which the new improved liners' efficien¬cies would -be measured. As will be shown, these baseline liners have been found to be deeper than the desire optimum depths. The new liner design process begins with the selection of the target hard wall fan noise spectra. These spectra were obtained by scaling up (5.91 scale factor) the measured hardwall fan spectral data from the 22” ADP fan rig. Next, the modal energy contents for each 1/3-octave band center frequency of these hardwall fan noise spectra are estimated. (Within each 1/3-octave band center frequency, the model energy distribution approximation is for both tone and broadband noise). For the inlet noise, P&W uses a derivative of the NASA Lewis (Ed Rice's) method of classifying; and grouping propagating modes by their cutoff ratios. The next step is to assign energy level to each group of modes having the same cutoff ratio. In Ed Rice's model, the modes were grouped according to ten (10) cutoff ratio intervals with center values located at 1.026, 1.085, 1.155, 1.24, 1.35, 1.49, 1.69, 2.0, and 4.47 (with equal number of modes in each interval). The modes were assumed to have equal energy. P&W’s model expands the cutoff ratio-mode grouping into two hundred (200) smaller cutoff ratio intervals with center values located f1".'m 1.003 to 11.5 in 199 increasing incremental intervals. Next, P&W's model uses a "2-parameter" normal distribution as a template to assign energy levels to these 200 pre-determined cutoff ratio values (for each 1/3-octave band center frequency). In the past, P&W had conducted an extensive study to determine what "2-parameter" values are appropriate for fullscale inlet liners, and had developed a set of twenty-four (24) "2-pararneter" values (i.e. one for each 1/3-octave frequency band) that when used in Ed Rice's Inlet Attenuation Prediction Method produced predicted liner attenuations that closely matched measured liner attenuations from several P&W's engines. In the absence of actual measured tone and broadband modal data from the 22" ADP rig, the process will use P&W's proprietary set of "2-parameter" values for this liner design study. For the aft noise, Boeing uses a modal energy approximation that the "transport energy" of each propagating mode is equal. This approximation is almost the same as the equal energy per mode approximation, except for modes that are near cutoff. Boeing's model forces these modes to have lower energy levels. Both P&W and Boeing agreed that the "transport energy" approximation should work well for the ADP aft fan noise which appears to be dominated by broadband noise. The design process then proceeds to calculate the optimum liner impedances for each frequency in both the inlet and the aft. These optimum impedances represent the target impedances that the designed liners should have. Liners with impedances matching the optimum impedances at all frequencies are "ideal" liners. These ideal liners are theoretically the best liners. Unfortunately, it has been showed that it is impossible to design and build such ideal liners. The next best liners are ones that have impedances matching the optimum impedances over some frequency range (not all frequencies as for the ideal). This is accomplished by the use of "frequency weightings". Several of P&W's and Boeing's existing computer decks were used for optimizing and matching the designed liner impedances to the target optimum values (with the various frequency weightings specified). The optimization produces liner candidates with predicted liner impedances and descriptions of their physical liner characteristics. These candidate liner impedances are then used to predict their spectral attenuation characteristics which are then used together with the target hardwall fan noise spectra to determine the resulting treated noise spectra and PNLT values. Further optimization around the selected candidate designs yield final designs that are best in PNLT attenuations. Use of the optimization decks allowed a large number of liner candidates to be screened in a relatively short period of time. This design process is systematic and is efficient. The new inlet SDOF liner design obtained from the improved process was predicted to be 34% more effective (per unit area) than the 1992 baseline inlet liner. This inlet liner design is a 112 rayl wovenwiremesh facesheet over a 0.312-inch deep honeycomb core. The new aft SDOF liner design was predicted to be 52% more efficient than the aft baseline liner. The new aft SDOF liner is "segmented" with a shallower liner on the core cowl (inner duct wall) and a deeper liner on the fan cowl (outer duct wall). The shallower liner is a 70.6 rayl woven-wiremesh facesheet over a 0.141-inch deep honeycomb core. The deeper liner is a 68 rayl woven-wiremesh facesheet over a 0.309-inch deep honeycomb core. All liner dimensions are for the 22-inch model-scale ADP fan rig liners. The selected advanced liners are "segmented" double-layer (DDOF) liners for the inlet and aft locations. Also, for the inlet, a bulk liner with ceramic foam for wider broadband noise absorption was also selected. Triple-layer liner designs were not considered since the model scaled liners ( 1/5. 91) were dimensionally too small to be built correctly, and irrin earlier concept study, Boeing found a triple-layer to have only very small benefits over a double-layer. The inlet DDOF liner was predicted to be 83% more effective than the baseline. The inlet DDOF design is a 78 rayl facesheet over a 0.080 top cavity depth, a 68 rayl septum and a 0.227-inch bottom cavity depth. The inlet bulk liner is a 60 rayl facesheet over a 0.33-inch deep honeycomb filled with high temperature (HTP) ceramic foam with a density of 4.8 lb/cu.ft and a flow resistivity of 167 rayl/cm. The inlet bulk liner was predicted to be 83% more effective than the baseline liner. The aft DDOF liners are segmented with a shallower liner on the core cowl and a deeper liner on the fan cowl. The shallow DDOF liner is a 49.8 rayl facesheet over a 0.093-inch top cavity depth, a septum of 88.2 rayls over a 0.181-inch bottom cavity depth. The deep DDOF liner is a 12.9 rayl facesheet over a 0.140-inch top cavity depth, a septum of 53.1 ray ls over a 0.258-inch botom cavity depth. The segmented aft DDOF liners were predicted to be 86% more efficient than the baseline liner.

turbofan acoustic treatment↗
NASA NTRS2024

Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗
DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗
NASA NTRS2022

Aerosol Models from the AERONET Database: Application to Surface Reflectance Validation Satellite Data

Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. In this paper, we propose and implement a framework for developing an aerosol model using their microphysical properties. Such microphysical properties as the size distribution, the complex refractive index, and the percentage of sphericity are derived from the global AERosol RObotic NETwork (AERONET). These measurements, however, are typically retrieved when almucantar measurement procedures are performed (i.e., early mornings and late afternoons with clear sky) and might not have a temporal correspondence to a satellite overpass time, so a valid validation of satellite-derived products cannot be carried out. To address this problem of temporal inconsistency of satellite and ground-based measurements, we developed an approach to retrieve these microphysical properties (and the corresponding aerosol model) using the optical thickness at 440 nm, τ440, and the Ångström coefficient between 440 and 870 nm, α440–870. Such aerosol models were developed for 851 AERONET sites within the last 28 years. Obtained results suggest that empirically microphysical properties can be retrieved with uncertainties of up to 23 %. An exception is the imaginary part of the refractive index ni, for which the derived uncertainties reach up to 38 %. These specific parametric models of aerosol can be used for the studies when retrieval of microphysical properties is required as well as validation of satellite-derived products over land. Specifically, we demonstrate the usefulness of the aerosol models to validate surface reflectance records over land derived from optical remote sensing sensors. We then quantify the propagation of uncertainties in the surface reflectance due to uncertainties with the aerosol model retrieval that is used as a reference from radiative transfer simulations. Results indicate that individual aerosol microphysical properties can impact uncertainties in surface reflectance retrievals between 3.5 × 10(exp -5) to 1 × 10(exp -3) (in reflectance units). The overall impact of microphysical properties combined yields an overall uncertainty in surface reflectance <0.004 (in reflectance units). That corresponds, for example, to 1 to 3 % of the retrieved surface reflectance in the red spectral band (620–670 nm) by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. These uncertainty values are well below the specification (0.005 + 0.05ρ; ρ is the retrieved surface reflectance) used for the MODIS atmospheric correction.

Jean-Claude Roger↗
DOE OSTI2018

High-resolution time-resolved experiments on mixing and entrainment of buoyant jets in stratified environments

Fluid jets interacting with a stratified layer play an important role in the safety of several reactor designs. In the containment of nuclear power plants, fluid jets dominate the transport and mixing of gaseous species and consequent hydrogen distribution in case of a severe accident. The mixing phenomena in the containment are driven by buoyant high-momentum injections (jets) and low momentum injection plumes. Mixing near the postulated break is initially dominated by high flow velocities. Plumes with moderate flow velocities are instead relevant in the break compartment during the long-term pressurization phase, or in any of the apertures between two connected compartments if the mass flows are sufficiently high and the density differences between efflux and ambient are sufficiently low. Phenomena of interest include free plumes (as produced by the efflux from the break compartment in a larger room or directly from a break flow), wall plumes (such those produced by low mass flows through inter-compartment apertures), and propagating stratification fronts in the ambient (for any stably stratified conditions). These phenomena have been highly ranked about nuclear reactor design, especially regarding of safety protocols. During a Pressurized Thermal Shock (PTS) scenario, the interaction between the cold ECCS injection plume and the stratified fluid present in the cold (or hot) leg is important in order to determine the temperature at the time-dependent temperature at the inlet of the reactor pressure vessel (RPV) and the potential to cause a thermal shock on the RPV wall. In sodium-cooled fast reactors (SFRs), core channels are typically hydro-dynamically isolated so that there exists a considerable temperature variation at the exit of adjacent fuel assemblies. All the above phenomena are characterized by the interaction of buoyant jets with the stratified flow. In stratified layers baroclinic forces create significant redistribution of turbulent kinetic energy and scales, which leads to anisotropy. This important physical phenomenon is highly three dimensional and is challenging to capture even with high-fidelity CFD simulations, due in part to lack of sufficiently resolved validation data. Furthermore, the experimental data available in the open literature do not feature the level of fidelity needed for an extensive validation of turbulence models in lower order CFD. To shed new lights into the crucial phenomena object of the present research project, it was proposed to conduct coordinated experiments and simulations at the University of Michigan and the George Washington University. The project has resulted in an experimental database of high-resolution time-resolved measurements of jets in uniform and stratified environments. The novel experimental data will be used to validate computational fluid dynamic (CFD) codes, including both Large Eddy Simulations (LES) and unsteady Reynolds-averaged Navier-Stokes equations (URANS) methodologies. In the Experimental and Multiphase flow (ECMF) laboratory at Univerisity of Michigan, we built two experimental facilities to investigate also the effect of scaling. The first facility, DESTROJER (DEnsity Stratified Turbulent ROund free Jet ExpeRiment), featuring a contoured jet nozzle with a diameter of D=12.7mm and a 1m×1m×1m cubic tank, which is made of acrylic glass for optical access. The ratio between the tank width and the nozzle diameter is equal to 78, which ensures that there is no direct interaction between the jet and the side walls. A second, modular experimental facility, features three different tank sizes of size 10×10×30, 20×20×30, 30×30×30 cm3 respectively (all tanks have the same height of 30 cm), and a jet diameter of 2mm. For the modular facility, tank-to-nozzle ratio of 50, 100, and 150 are obtained respectively. Experiments with different-density jet impactions and sharp interface with a density difference of 3.16% In the Laboratory at George Washington University, complementary experiments have been carried out at a facility featuring the same dimensions as DESTROYER. Experiments with different jet diameters have been carried out as well. High-resolution time-resolved measurements have been performed at all facilities using high-speed particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF). In this way, simultaneous measurements of velocity and density fields have been carried out. At the University of Michigan, wire-mesh sensors have been designed and built to gather high-resolution, time-dependent data of the stratified front in the tank. These measurements are important to provide accurate initial conditions for the CFD simulations. An important outcome of the project has been the development of novel techniques to achieve refractive index matching (RIM) of acqueous solutions with high density differences. RIM is crucial if optical techniques such as PIV are used to measure velocity fields. Previous to this project, experiments up to 3% density difference had been reported in the literature. With the methodology developed in this project, we have been able to push the envelop to density differences up to 9%. The experiments have been used to validate Reynolds Averaged Navier-Stokes (RANS) turbulence models and Large Eddy Simulations (LES) models. Both NEK5000 and the commercial CFD code STAR-CCM+ have been used. The experimental data will be made available to the community through the NE-KAMS databasehave been successfully conducted in the scaled facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗