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At least 649 records · Page 36

Experiments Developed to Study Microgravity Smoldering Combustion

The overall objective of the Microgravity Smoldering Combustion (MSC) research program is to understand and predict smoldering combustion under normal and microgravity (near-zero-gravity) conditions to help prevent and control smolder-originated fires, in both environments. Smoldering is defined as a nonflaming, self-sustaining, propagating, exothermic surface reaction. If a material is sufficiently permeable, smoldering is not confined to its outer surface, but can propagate as a reaction wave through the interior of the material. The MSC program will accomplish its goals by conducting smolder experiments on the ground and in a space-based laboratory, and developing theoretical models of the process. Space-based experiments are necessary because smoldering is a very slow process and, consequently, its study in a microgravity environment requires extended periods of time that can only be achieved in space. Smoldering can occur in a variety of processes ranging from the smolder of porous insulating materials to underground coal combustion. Many materials can sustain smoldering, including wood, cloth, foams, tobacco, other dry organic materials, and charcoal. The ignition, propagation, transition to flaming, and extinction of the smolder reaction are controlled by complex, thermochemical mechanisms that are not well understood. As with many forms of combustion, gravity affects the availability of the oxidizer and the transport of heat, and therefore, the rate of combustion. The smoldering combustion of porous materials has been studied both experimentally and theoretically, usually in the context of fire safety. Smoldering encompasses a number of fundamental processes, including heat and mass transfer in a porous media; endothermic pyrolysis of combustible material; ignition, propagation, and extinction of heterogeneous exothermic reactions at the solid-gas pore interface; and the onset of gas phase reactions (flaming) from existing surface reactions. Smoldering presents a serious fire risk because the combustion can propagate slowly in a material's interior and go undetected for long periods of time. It typically yields a substantially higher conversion of fuel to toxic compounds than does flaming (though more slowly), and may undergo a sudden transition to flaming.

Vergilii, Franklin↗

Oxidation kinetics for conversion of U 3 O 8 to ε-UO 3 with NO 2

The oxidation kinetics of U 3 O 8 powder to ε-UO 3 in an NO 2 environment was measured by in situ x-ray diffraction (XRD). Experiments were performed at temperatures of 195, 210, 235, and 250°C using a custom designed and fabricated sample isolation stage. Data were refined to quantify phase fractions using a newly proposed structure for the ε-UO 3 polymorph. The kinetics data were modeled using a shrinking core approach. A proposed two-step reaction process is presented based on the developed models.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Tools for Assessing Performance Project: FY2021 Quarter 4 Report

The rotatable building located at Texas Tech’s Reese Technology Center is approximately 14 m wide (width being defined as more normal to the wind than parallel), 9 m long (aligned more with the wind than perpendicular), and 4 m tall. By placing 29 sonic anemometers downwind of the building, see Fig. 1, this facility provided a chance to collect data concerning both the wake velocity deficit distribution in the downstream and crosssteam directions (relative to the mean wind) behind an isolated building. A preliminary comparison between this data and the recently- developed fast-running diffusive wake model, which was developed based on wind tunnel and LES (performed with JOULES) simulations, for the purpose of either validating this model of understanding potential persistent differences between the idealized wind tunnel or LES conditions and those of full-scale real world phenomena. For this preliminary exploration, we utilized the diffusive wake model implemented in the QUIC model.

42 ENGINEERING↗

Icing Branch Current Research Activities in Icing Physics

Current development: A grid block transformation scheme which allows the input of grids in arbitrary reference frames, the use of mirror planes, and grids with relative velocities has been developed. A simple ice crystal and sand particle bouncing scheme has been included. Added an SLD splashing model based on that developed by William Wright for the LEWICE 3.2.2 software. A new area based collection efficiency algorithm will be incorporated which calculates trajectories from inflow block boundaries to outflow block boundaries. This method will be used for calculating and passing collection efficiency data between blade rows for turbo-machinery calculations.

Vargas, Mario↗

On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.

Prather, Maurice↗

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗

Multi-Variable Model-Based Parameter Estimation Model for Antenna Radiation Pattern Prediction

A new procedure is presented to develop multi-variable model-based parameter estimation (MBPE) model to predict far field intensity of antenna. By performing MBPE model development procedure on a single variable at a time, the present method requires solution of smaller size matrices. The utility of the present method is demonstrated by determining far field intensity due to a dipole antenna over a frequency range of 100-1000 MHz and elevation angle range of 0-90 degrees.

Deshpande, Manohar D.↗

Predictive LES Modeling and Validation of High-Pressure Turbulent Flames and Flashback in Hydrogen-enriched Gas Turbines

The overall objective of this project is to make advances in large-eddy simulation modeling of swirl-flame flashback at elevated pressure, where the reactants can be premixed or stratified, and composed of methane enriched with hydrogen. The modeling effort was conducted with a companion experimental validation effort that focused on high-speed measurements of flashback in a model swirl-flame combustor. The modeling effort focused on the development of manifold-based combustion model for flashback simulations. The main complexity in this configuration comes from the flames’ propagation through a stratified fuel-air mixture along with heat loss near the walls. For this purpose, a non-adiabatic flamelet model was developed and tested using canonical flow configurations. Further, extensive validation in premixed configurations is used to establish the model’s accuracy in capturing heat loss and flame propagation. Finally, the model was tested using the UT flame flashback experiment, and was shown to accurately capture the flame flashback process. The end products from this work are a) a full validated flameout-based approach for modeling flame flashback; b) a complete implementation of the model in the open source OpenFOAM framework, which has been made available to both industry and academia; c) an extensive suite of validation studies performed using the OpenFOAM solver. In addition, new techniques for flame modeling, subfilter modeling of scalars, and simulation of low Mach number flows were developed and tested. In the experimental validation effort, flashback was studied in a premixed and stratified swirl flame by using high-speed imaging diagnostics. Fuels tested included CH 4 enriched with H 2 , with H 2 enrichment up to 84% by volume. These flashback experiments are conducted at pressures ranging from 1 to 5 atm. A swirler-based fuel-injection system was used to create the fuel-air stratification in the radial direction. For the high-pressure measurements, an optically accessible elevated pressure chamber was used. The spatial distribution of the equivalence ratio under non-reacting conditions was characterized using planar laser-induced fluorescence with acetone as the fuel tracer. It was observed that fuel-air pockets were distributed across the mixing tube width, although in an average sense, the fuel-air mixture was radially stratified. The global behavior of upstream flame propagation was investigated for different levels of hydrogen-enrichment. For stratified hydrogen-rich flashback, the propagation path of the flame changed from the inner wall to outer wall, which was induced by the faster chemistry of stoichiometric mixtures that are frequently present near the outer wall. This behavior of hydrogen-rich flashback persists even at elevated pressures up to 5 atm, although the propagation of the flame occurs as a wide flame tongue as opposed to the acute-tipped flame structures present in the atmospheric cases. The end product of the experimental effort is greatly improved knowledge of flashback physics and a unique database that can be used for model validation.

08 HYDROGEN↗

Model Based Engineering for Software Assurance

NASA's successful development of next generation space vehicles, habitats, and robotic systems will require reliable hardware and software systems. The aim of this initiative is to develop modeling methodology and tools to support Model-Based Systems Engineering (MBSE) for software assurance and reliability analysis. This effort expands the Unified Modeling Language (UML) software design models to include fault data for the extraction of Failure Modes and Effects Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) for software. We explored different modeling approaches to integrate the UML software design models with the Systems Modeling Language (SysML) system models to generate an integrated model and reliability tools that take into account software and hardware interfaces.The benefits of this concept directly affect the safety community with quick turnarounds to produce software assurance and reliability analysis artifacts and the ability to visualize failure effects, both hardware and software. The result is enhanced system design integrity and early identification of system risks. This initiative will enable software assurance activities early in the system design lifecycle, facilitating the discovery of design weaknesses and enhancing the capability to produce safe, hazard-free systems

Wang, Lui↗

Icing Simulation

A grid block transformation scheme which allows the input of grids in arbitrary reference frames, the use of mirror planes, and grids with relative velocities has been developed. A simple ice crystal and sand particle bouncing scheme has been included.. Added an SLD splashing model based on that developed by William Wright for the LEWICE 3.2.2 software. A new area based collection efficiency algorithm will be incorporated which calculates trajectories from inflow block boundaries to outflow block boundaries. This method will be used for calculating and passing collection efficiency data between blade rows for turbo-machinery calculations.

Bidwell, Colin↗

Automatic Code Generation for Instrument Flight Software

Automatic code generation can be used to convert software state diagrams into executable code, enabling a model- based approach to software design and development. The primary benefits of this process are reduced development time and continuous consistency between the system design (statechart) and its implementation. We used model-based design and code generation to produce software for the Electra UHF radios that is functionally equivalent to software that will be used by the Mars Reconnaissance Orbiter (MRO) and the Mars Science Laboratory to communicate with each other. The resulting software passed all of the relevant MRO flight software tests, and the project provides a useful case study for future work in model-based software development for flight software systems.

state charts↗

Development of Algebraic and Topological-Based Structured Packing Model

Poster being presented at the 2024 annual AICHE meeting held from October 27-31, 2024. The poster focuses on developing an algebraic and topological model for designing structured packing for a CO2 absorption tower. The model can be optimized to determine an optimal packing structure.

Summits, Stephen↗

Novel linear analysis for a gyrotron oscillator based on a spectral approach

With the aim of gaining a better physical insight into linear regimes in gyrotrons, a new linear model was developed. This model is based on a spectral approach for solving the self-consistent system of equations describing the wave-particle interaction in the cavity of a gyrotron oscillator. Taking into account the wall-losses self-consistently and including the main system inhomogeneities in the cavity geometry and in the magnetic field, the model is appropriate to consider real system parameters. The main advantage of the spectral approach, compared with a time-dependent approach, is the possibility to describe all of the stable and unstable modes, respectively, with negative and positive growth rates. This permits to reveal the existence of a new set of eigenmodes, in addition to the usual eigenmodes issued from cold-cavity modes. The proposed model can be used for studying other instabilities such as, for instance, backward waves potentially excited in gyrotron beam tunnels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncertainty analysis of PIV measurements in bubbly flows considering sampling and bubble effects with ray optics modeling

In this report, a modeling-based approach is developed to investigate the external sources of uncertainty in particle image velocimetry (PIV) measurements for two-phase bubbly flows. Primarily relied on ray optics modeling, this study focuses on the uncertainty in PIV measurements due to bubble-induced light distortion. In addition, the uncertainty due to sampling is also considered through synthetic PIV images generated from Monte Carlo sampling. Based on a PIV-planar laser induced florescence (PLIF) measurement system, three case studies are performed and discussed, considering respectively the sampling effect, bubble effect, and the combination of these two effects. These case studies confirm the validity of the ray optics modeling in obtaining accurate particle images through a benchmark test. Furthermore, it is also found that the bubble effect could significantly influence the particle images. On the other hand, the result of the case study with synthetic PIV images indicates that the bubble effect on particle images can be minimized by removing “outliers” in the obtained velocity vector field through a multi-pass post-processing procedure. However, the uncertainty of the velocity measurements will still increase.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗

Multi-modal Approach to Modeling Creep Deformation in Nickel-base Superalloy

This study developed the multi-modal modeling approaches to elucidate the physical and overall mechanical properties of two complex alloy systems of Ni-based Superalloys, namely Haynes 282 and Inconel 740. The overall strategies employed systematically in different scales of modeling are based on the common structural framework of the multi phases that made up the Ni-based Superalloys, namely the matrix phase of the Gamma ($\gamma$) phase which is embedded with ordered Gamma prime ($\gamma$’) precipitates and decorated with the dispersions of mostly carbide precipitates. With this in mind, we had set up the modeling platforms to incorporate a wide range of scales, starting from electronic structures to the continuum level via the crystal plasticity model.

20 FOSSIL-FUELED POWER PLANTS↗

Integrated Real-Time Modeling System for Heliospheric Space Weather Forecasting

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

Mansour, Nagi N.↗