Results for “Nonlinear projection” — Page 35

NASA NTRS2007

Strain Measurement Using FBG on COPV in Stress Rupture Test

White Sands Test Facility (WSTF) was requested to perform ambient temperature hydrostatic pressurization testing of a Space Transportation System (STS) 40-in. Kevlar Composite Overwrapped Pressure Vessel (COPV). The 40-in. vessel was of the same design and approximate age as the STS Main Propulsion System (MPS) and Orbiter Maneuvering System (OMS) vessels. The NASA Engineering Safety Center (NESC) assembled a team of experts and conducted an assessment that involved a review of national Kevlar COPY data. During the review, the STS COPVs were found to be beyond their original certification of ten years. The team observed that the likelihood of STS COPV Stress rupture, a catastrophic burst before leak failure mode, was greater than previously believed. Consequently, a detailed assessment of remaining stress rupture life became necessary. Prior to STS-114, a certification deviation was written for two flights of OV-103 (Discovery) and OV-104 (Atlantis) per rationale that was based on an extensive review of the Lawrence Livermore National Laboratories, COPV data, and revisions to the STS COPV stress levels. In order to obtain flight rationale to extend the certification deviation through the end of the Program, the Orbiter Project Office has directed an interagency COPV team to conduct further testing and analysis to investigate conservatism in the stress rupture model and evaluate material age degradation. Additional analysis of stress rupture life requires understanding the fiber stresses including stress that occurs due to thru-wall composite compression in COPV components. Data must be obtained at both zero gauge pressure (pre-stress) and at the component operating pressure so that this phenomenon can be properly evaluated. The zero gauge pressure stresses are predominantly a result of the autofrettage process used during vessel manufacture. Determining these pre-stresses and the constitutive behavior of the overwrap at pressure will provide necessary information to better predict the remaining life of the STS COPVs. The primary test objective is obtaining data to verify the hypothesis of a radially oriented thru-thickness stress-riser in the COPV composite whose magnitude is a function of the applied pressure and the load history. The anticipated load dependent response follows from the constitutive behavior of the composite overwrap so data to quantify its nonlinear and time dependent response will be sought. The objective of the Fiber Braggs Gratings (FBGs) were to advance the state-of-the-art by developing techniques using FBG sensors that are capable of assessing stress-rupture degradation in Kevlar COPVs in a health monitoring mode (1). Moreover, they sought to answer questions of how embedded sensors affect overall integrity of the structure. And lastly, they sought to provide an important link in the overall stress rupture study that will help close the loop on the COPV fabrication process. NDE inspection methods will be used from start to finish and FBG will be an integral link within the overall chain.

Banks, Curtis↗

NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗

NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗

NASA NTRS2004

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Williams-Hayes, Peggy S.↗

NASA NTRS1994

Raman-shifting an ArF excimer laser to generate new lines for obtaining optical diagnostic based information in flow fields

The application of tunable excimer lasers in combustion and flow diagnostics is almost routine nowadays. The properties of this laser system that enable density and temperature measurements in supersonic and hypersonic flow fields to be conducted are its high power, high repetition rate, and high spectral brightness. The limitation imposed by this system on these measurements is the paucity of lines in the wavelength region, the vacuum-ultraviolet, where species of interest, such as OH, N2, O2, H2, H2O, CO, NO, etc., are susceptible to electronic excitation to high-lying states. To circumvent this problem one normally resorts to nonlinear optical techniques such as frequency conversion via stimulated Raman scattering (SRS), more commonly known as Raman shifting or Raman mixing, to extend these nonintrusive and nonperturbing techniques to the shorter wavelengths in the VUV region and, for that matter, to longer wavelengths in the infrared region, if the need arises. The theoretical basis of SRS and its application are well documented in the literature. In essence, the Raman shift is a consequence of the inelastic scattering of the incident radiation by the sample. Most of the scattered radiation from the molecules of the sample is unchanged in frequency. However, a small fraction of the incident radiation is changed in frequency. This shift is a result of the fact that some of the incident photons on colliding with the molecules of the sample give up some of their energy and emerge with a lower energy resulting in the lower-frequency Stokes radiation. Other incident photons may increase their energy by colliding with the vibrationally excited molecules of the medium and emerge as higher-frequency antistokes radiation. The generation of the latter is the main objective of this project. The process, however, depends on several factors, including the beam quality of the pump laser, the cross-section of the gaseous medium, the gas pressure, and the ambient temperature of the gas near the focal region. Furthermore, since the Raman shifting process is polarization sensitive, it is necessary to have all of the laser energy in a single polarization. These factors were taken into consideration in the execution of the project. The implementation of the Raman shift was accomplished by focusing the 193 nm output of an ArF excimer laser (Lamda-Physik LPX 150) into a 1-meter long high pressure recirculating Raman cell filled with H2 gas. The laser system was modified in order to improve the mode quality of the pump beam to enhance the Raman shifting. To accomplish this feat, a prism beam expander and grating on the oscillator discharge provided wavelength tuning over the excimer gain profile. Furthermore, a triple-pass configuration, as opposed to unstable resonator optics, was employed in the operation of the amplifier cavity so that when the oscillator output radiation, focused by a 51-cm focal length fused silica lens through a 50 micron pinhole (serving as a spatial filter) and recollimated with a 25-cm focal length lens, was fed into the amplifier, it was injection locked, thereby providing tunable radiation with relatively low divergence. The forward scattered radiation emanating from the impingement of the modified pump beam on the Raman cell was detected using an energy meter after the latter had been separated from it using a dispersing prism.

Koker, Edmond B.↗

NASA NTRS1994

An initial investigation into methods of computing transonic aerodynamic sensitivity coefficients

The primary accomplishments of the project are as follows: (1) Using the transonic small perturbation equation as a flowfield model, the project demonstrated that the quasi-analytical method could be used to obtain aerodynamic sensitivity coefficients for airfoils at subsonic, transonic, and supersonic conditions for design variables such as Mach number, airfoil thickness, maximum camber, angle of attack, and location of maximum camber. It was established that the quasi-analytical approach was an accurate method for obtaining aerodynamic sensitivity derivatives for airfoils at transonic conditions and usually more efficient than the finite difference approach. (2) The usage of symbolic manipulation software to determine the appropriate expressions and computer coding associated with the quasi-analytical method for sensitivity derivatives was investigated. Using the three dimensional fully conservative full potential flowfield model, it was determined that symbolic manipulation along with a chain rule approach was extremely useful in developing a combined flowfield and quasi-analytical sensitivity derivative code capable of considering a large number of realistic design variables. (3) Using the three dimensional fully conservative full potential flowfield model, the quasi-analytical method was applied to swept wings (i.e. three dimensional) at transonic flow conditions. (4) The incremental iterative technique has been applied to the three dimensional transonic nonlinear small perturbation flowfield formulation, an equivalent plate deflection model, and the associated aerodynamic and structural discipline sensitivity equations; and coupled aeroelastic results for an aspect ratio three wing in transonic flow have been obtained.

Carlson, Leland A.↗

NASA NTRS2011

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

Hanson, Curt↗

NASA NTRSDate not supplied

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

PLIF↗

NASA NTRSDate not supplied

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

PLIF↗

NASA NTRS2017

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments, conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules, which are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flow field carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.

Drozda, Tomasz G.↗

DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗

DOE OSTI2026

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗

DOE OSTI2024

Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction

Burning plasma performance, transport, and the effect of hydrogen isotope (H, D, D-T fuel mix) on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73), were used to predict profiles of T i , T e , and n e while including the effects of alpha heating, auxiliary power (NBI + ECH), collisional energy exchange, and radiation losses inside of $r/a$ = 0.9. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals ($P_\textrm{fusion} = 500$ MW at Q = 10) for the baseline scenario and exhibit energy confinement that is within 1σ of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential resonant magnetic perturbation (RMP) effects on performance with a minimal number of gyrokinetic profile iterations required (3–6). These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that $Q \gt$ 17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in IBS conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.

gyrokinetics↗

NASA NTRS2004

Monitoring space shuttle air quality using the Jet Propulsion Laboratory electronic nose

A miniature electronic nose (ENose) has been designed and built at the Jet Propulsion Laboratory (JPL), Pasadena, CA, and was designed to detect, identify, and quantify ten common contaminants and relative humidity changes. The sensing array includes 32 sensing films made from polymer carbon-black composites. Event identification and quantification were done using the Levenberg-Marquart nonlinear least squares method. After successful ground training, this ENose was used in a demonstration experiment aboard STS-95 (October-November, 1998), in which the ENose was operated continuously for six days and recorded the sensors' response to the air in the mid-deck. Air samples were collected daily and analyzed independently after the flight. Changes in shuttle-cabin humidity were detected and quantified by the JPL ENose; neither the ENose nor the air samples detected any of the contaminants on the target list. The device is microgravity insensitive.

manned↗

DOE OSTI2025

Technical Report on Subsurface Monitoring of the Brady Hot Spring Geothermal Site, Nevada, based upon Full Waveform Inversion

Abilities to accurately characterize the subsurface in a geothermal setting is key to assess and support production. An important element of geothermal reservoir monitoring is also the ability to investigate fluid transport within fracture network. This report focuses on improving subsurface imaging and monitoring in geothermal settings using full waveform inversion based on the adjoint method and time-lapse imaging. To assess our method, we rely on a dense seismic dataset collected in 2016 at the Brady Hot Springs geothermal site in Nevada for the DOE-funded project Poroelastic Tomography by Adjoint Inverse Modeling of Data from Seismology, Geodesy, and Hydrology. This dataset captures subsurface changes across four stages of geothermal power plant operations, which involve varying rates of fluid injection and extraction. Two velocity models were previously derived from this dataset using different methods: one based on travel times and another on sweep interferometry. Our first step is to refine these models using adjoint tomography, which has been applied successfully at global and regional-scales but is less common at the reservoir-scale. Two approaches are then explored for time-lapse analysis: directly comparing refined tomographic models from different stages or backpropagating waveform differences relative to a baseline tomographic model. The main take away is that both approaches highlight similar reservoir behaviors, but the latter approach is more computationally effective in capturing small-scale changes in subsurface properties. For this work, we leverage the use of Salvus (www.mondaic.com), an end-to-end seismic imaging solution, relying on the spectral element method to compute forward and adjoint simulations, and developed by Mondaic Ltd. It includes integrated workflow management that handles waveform and metadata, launches simulations, computes waveform misfits and adjoint sources, and iterates for model updates by nonlinear optimization.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies

Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs) or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we present a road map of how dynamic vegetation demographic models (VDMs) can be used to investigate hypotheses surrounding ecosystem responses to one type of UCE: unprecedented droughts. As a result of nonlinear ecosystem responses to UCEs that are qualitatively different from responses to milder extremes, we consider both biomass loss and recovery rates over time by reporting a time-integrated carbon loss as a result of UCE, relative to the absence of drought. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites using well-tested models (ED2 and LPJ-GUESS). The severity and patterns of biomass losses differed substantially between models. For example, biomass loss could be sensitive to either drought duration or drought intensity depending on the model approach. This is due to the models having different, but also plausible, representations of processes and interactions, highlighting the complicated variability of UCE impacts that still need to be narrowed down in models. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight the consequences of differences in process formulations and uncertainties in models, most notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. We provide a summary of the current state and role of many model processes that give way to different underlying hypotheses of plant responses to UCEs, reflecting knowledge gaps which in future studies could be tested with targeted field experiments and an iterative modeling–experimental conceptual framework.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A reduced-order shifted boundary method for parametrized incompressible Navier–Stokes equations

Here, we investigate a projection-based reduced order model of the steady incompressible Navier–Stokes equations for moderate Reynolds numbers. In particular, we construct an “embedded” reduced basis space, by applying proper orthogonal decomposition to the Shifted Boundary Method, a high-fidelity embedded method recently developed. We focus on the geometrical parametrization through level-set geometries, using a fixed Cartesian background geometry and the associated mesh. This approach avoids both remeshing and the development of a reference domain formulation, as typically done in fitted mesh finite element formulations. Two-dimensional computational examples for one and three parameter dimensions are presented to validate the convergence and the efficacy of the proposed approach.

"embedded" basis↗

DOE OSTI2023

Towards understanding the robust strengthening of ENSO and more frequent extreme El Niño events in CMIP6 global warming simulations

The El Niño Southern Oscillation (ENSO) has profound impacts on weather patterns across the globe, yet there is no consensus on its response to global warming. Several modelling studies find a stronger ENSO in global warming scenarios, while other studies suggest ENSO weakening. Using a broad range of models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and four types of warming experiments, here we show that the majority of the models predict a stronger ENSO by century-end in Shared Social Pathway (SSP) experiments, and in idealized 1pctCO 2 and abrupt 4xCO 2 experiments. Several models, however, do predict no change or ENSO weakening, especially in the idealized experiments. Critically, the strongest forcing (abrupt-4xCO 2 ) does not induce the strongest ENSO response, while differences between the models are much greater than those between warming scenarios. For the long-term response (over 1000 years) the models disagree even on the sign of change. Furthermore, changes in ENSO sea surface temperature (SST) variability are only modestly correlated with the tropical Pacific mean state change. The highest correlation for ENSO SST amplitude is found with the mean zonal SST gradient in the SSP5-8.5 experiment (R = –0.58). In contrast, changes in ENSO rainfall variability correlate well with changes in the mean state, as well as with changes in ENSO SST variability. When evaluating the Bjerknes Stability Index for a subset of models, we find that it is not a reliable predictor of ENSO strengthening, as this index tends to predict greater stability with warming. We argue that the enhanced ENSO stability is offset by increases in atmospheric noise or/and potential nonlinear effects. However, a robust inter-model mechanism that can explain a stronger ENSO simulated with global warming is still lacking. Therefore, caution should be exercised when considering ENSO changes based on a single model or warming scenario.

54 ENVIRONMENTAL SCIENCES↗