Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model reduction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Reinforcement learning for online adaptation of model predictive controllers: Application to a selective catalytic reduction unit

Here we present a novel application of reinforcement learning (RL) for online dynamic tuning of model predictive controllers (MPC). Applying a state-action-reward-state-action (SARSA) algorithm for temporal difference learning with a control-specific reward function improves the error tracking performance of a standard MPC formulation. The proposed RL approach is also readily adaptable to other MPCs, or entirely different control approaches. Practical details for the implementation of the RL-MPC algorithm are also presented. The proposed algorithm is applied to a case study of controlling nitrogen oxide (NO x ) emissions in an industrial selective catalytic reduction (SCR) unit, a control problem characterized by significant nonlinearity and time delay. Along with an RL-MPC formulation for NOx control, another MPC is proposed to mitigate ammonia slip and decrease ammonia consumption in the SCR. Results showing the efficacy of the RL-MPC for NO x control through learning and implementation on the nonlinear SCR dynamic model are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Effect of Two Advanced Noise Reduction Technologies on the Aerodynamic Performance of an Ultra High Bypass Ratio Fan

A wind tunnel experiment was conducted in the NASA Glenn Research Center anechoic 9- by 15-Foot Low-Speed Wind Tunnel to investigate two new advanced noise reduction technologies in support of the NASA Fundamental Aeronautics Program Subsonic Fixed Wing Project. The goal of the experiment was to demonstrate the noise reduction potential and effect on fan model performance of the two noise reduction technologies in a scale model Ultra-High Bypass turbofan at simulated takeoff and approach aircraft flight speeds. The two novel noise reduction technologies are called Over-the-Rotor acoustic treatment and Soft Vanes. Both technologies were aimed at modifying the local noise source mechanisms of the fan tip vortex/fan case interaction and the rotor wake-stator interaction. For the Over-the-Rotor acoustic treatment, two noise reduction configurations were investigated. The results showed that the two noise reduction technologies, Over-the-Rotor and Soft Vanes, were able to reduce the noise level of the fan model, but the Over-the-Rotor configurations had a significant negative impact on the fan aerodynamic performance; the loss in fan aerodynamic efficiency was between 2.75 to 8.75 percent, depending on configuration, compared to the conventional solid baseline fan case rubstrip also tested. Performance results with the Soft Vanes showed that there was no measurable change in the corrected fan thrust and a 1.8 percent loss in corrected stator vane thrust, which resulted in a total net thrust loss of approximately 0.5 percent compared with the baseline reference stator vane set.

Hughes, Christoper E.↗
DOE OSTI2019

Investigation of LSM-YSZ Composite Cathode Performance Degradation with a Multistep Charge Transfer Model

The long-term performance degradation of LSM/YSZ composite cathodes is investigated via calibrated multiphysics simulation with a multistep oxygen reduction reaction (ORR) model and structural coarsening data from a phase field study. Multiphysics simulations, including a multistep ORR mechanism, are first developed for better understanding of the limiting processes in solid oxide fuel cells. The multistep ORR mechanism includes two parallel pathways, surface pathway and bulk pathway, which consist of elementary reaction steps. The multiphysics model is simultaneously calibrated with experimental polarization curves and impedance behavior for various air/fuel supply conditions. To our knowledge, this is the first time that a multistep ORR model is calibrated with such datasets. Next, the calibrated simulations are utilized to simulate a 2D half-cell constructed with measured microstructural data and random heterogeneity. Finally, the long-term performance degradation of the half-cell is predicted by the calibrated multiphysics model coupled with structural coarsening trends simulated using a phase field-based coarsening model. Degradation of both polarization curves and impedance behavior is investigated. Thorough analyses, including changes of contributions from different pathways, the resistance components, and overall reaction order, are performed to provide more insights into cathode performance degradation due to grain coarsening phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Global and Regional Radiative Forcing from 20 Reductions in BC, OC and SO4 an HTAP2 Multi-Model Study

In the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) exercise, a range of global atmospheric general circulation and chemical transport models performed coordinated perturbation experiments with 20% reductions in emissions of anthropogenic aerosols, or aerosol precursors, in a number of source regions. Here, we compare the resulting changes in the atmospheric load and vertically resolved profiles of black carbon (BC), organic aerosols (OA) and sulfate (SO4/ from 10 models that include treatment of aerosols. We use a set of temporally, horizontally and vertically resolved profiles of aerosol forcing efficiency (AFE) to estimate the impact of emission changes in six major source regions on global radiative forcing (RF) pertaining to the direct aerosol effect, finding values between. 51.9 and 210.8mW/sq m/Tg for BC, between -2.4 and -17.9mW/sq m/Tg for OA and between -3.6 and -10.3W/sq m/Tg for SO4. In most cases, the local influence dominates, but results show that mitigations in south and east Asia have substantial impacts on the radiative budget in all investigated receptor regions, especially for BC. In Russia and the Middle East, more than 80 % of the forcing for BC and OA is due to extra-regional emission reductions. Similarly, for North America, BC emissions control in east Asia is found to be more important than domestic mitigations, which is consistent with previous findings. Comparing fully resolved RF calculations to RF estimates based on vertically averaged AFE profiles allows us to quantify the importance of vertical resolution to RF estimates. We find that locally in the source regions, a 20% emission reduction strengthens the radiative forcing associated with SO4 by 25% when including the vertical dimension, as the AFE for SO4 is strongest near the surface. Conversely, the local RF from BC weakens by 37% since BC AFE is low close to the ground. The fraction of BC direct effect forcing attributable to intercontinental transport, on the other hand, is enhanced by one-third when accounting for the vertical aspect, because long-range transport primarily leads to aerosol changes at high altitudes, where the BC AFE is strong. While the surface temperature response may vary with the altitude of aerosol change, the analysis in the present study is not extended to estimates of temperature or precipitation changes.

profiles of aerosol forcing efficiency (AFE)↗
DOE OSTI2026

Multi-Scale Modeling and Prototype Development for Electrochemical CO2 Reduction (CRADA Final Report)

In this CRADA project, Lawrence Livermore National Laboratory, Stanford University, SLAC National Laboratory, and TotalEnergies collaboratively executed a multidisciplinary investigation of electrochemical reduction of CO2 to produce sustainable fuels and chemicals. Overall, the project led to an increased understanding of the fundamental processes involved in CO2 electrolysis, from the atomistic scale to the full electrolyzer device scale, ultimately leading to design guidelines for CO2 electrolyzers that will help in their future commercialization. As the model systems, Ag- and Cu-based catalysts were investigated in various forms depending on the electrochemical platform that was utilized to study the activity, selectivity, and durability towards electrochemical CO2 reduction. By employing experimental, theoretical, and computational techniques, the project team experimentally validated multi-physics models, evaluated the experimental levers that lead to increased electrolyzer reaction selectivity and energy efficiency, and used computational optimization to design higher performance electrodes. The learnings of this project were extensively documented in publicly available peer-reviewed journal publications and conference presentations, which serve as a foundation for further work to build from.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Open‐source photovoltaic model pipeline validation against well‐characterized system data

Abstract All freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.

14 SOLAR ENERGY↗
DOE OSTI2019

Modeling anaerobic soil organic carbon decomposition in Arctic polygon tundra: insights into soil geochemical influences on carbon mineralization

Abstract. Rapid warming of Arctic ecosystems exposes soil organic matter (SOM) to accelerated microbial decomposition, potentially leading to increased emissions of carbon dioxide ( CO 2 ) and methane ( CH 4 ) that have a positive feedback on global warming. Current estimates of the magnitude and form of carbon emissions from Earth system models include significant uncertainties, partially due to the oversimplified representation of geochemical constraints on microbial decomposition. Here, we coupled modeling principles developed in different disciplines, including a thermodynamically based microbial growth model for methanogenesis and iron reduction, a pool-based model to represent upstream carbon transformations, and a humic ion-binding model for dynamic pH simulation to build a more versatile carbon decomposition model framework that can be applied to soils under varying redox conditions. This new model framework was parameterized and validated using synthesized anaerobic incubation data from permafrost-affected soils along a gradient of fine-scale thermal and hydrological variabilities across Arctic polygonal tundra. The model accurately simulated anaerobic CO 2 production and its temperature sensitivity using data on labile carbon pools and fermentation rates as model constraints. CH 4 production is strongly influenced by water content, pH, methanogen biomass, and presence of competing electron acceptors, resulting in high variability in its temperature sensitivity. This work provides new insights into the interactions of SOM pools, temperature increase, soil geochemical feedbacks, and resulting CO 2 and CH 4 production. The proposed anaerobic carbon decomposition framework presented here builds a mechanistic link between soil geochemistry and carbon mineralization, making it applicable over a wide range of soils under different environmental settings.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

An Observation‐Driven Approach to Improve Vegetation Phenology in a Global Land Surface Model

An empirical model calibration approach is presented that aims to approximate missing biosphere processes in a global land surface model without the need for substantial model structural changes. The strategy is implemented here using the NASA Catchment‐CN land surface model and Moderate Resolution Imaging Spectroradiometer (MODIS) observations of the fraction of absorbed photosynthetically active radiation (FPAR). Existing plant functional types (PFTs) of the Catchment‐CN model are divided into three subtypes, based on the bias between the model‐simulated and MODIS‐observed FPAR. Separate sets of vegetation parameters for each subtype are then calibrated at a small number of grid cells with homogeneous, single‐PFT land cover, using MODIS FPAR reference observations from 2003 to 2009. The effectiveness of the empirical approach at improving the realism of modeled vegetation dynamics is investigated with two global model simulations for the period 2010–2016, one using the newly calibrated parameter values and the other using the original values. Globally, the calibrated parameters reduce the root mean square error (RMSE) of the modeled FPAR with respect to MODIS by 0.029 (∼10%) on average. In some regions, substantially larger RMSE reductions are achieved. RMSE reductions are primarily driven by model bias reductions, with neutral effects on the temporal correlation skill. While the empirical approach is suitable for achieving consistent model improvements, it is shown to be sensitive to the characteristics of the model error, specifically a dominance of the bias component in the case of Catchment‐CN. Ultimately, more fundamental model structural changes may be required to achieve better improvements.

J. Kolassa↗
DOE OSTI2021

Development, Implementation, and Verification of Partially-Ionized Collisional Multifluid Plasma Models in Drekar

We consider the development of multifluid models for partially ionized multispecies plasmas. The models are composed of a standard set of five-moment fluid equations for each species plus a description of electromagnetics. The most general model considered utilizes a full set of fluid equations for each charge state of each atomic species, plus a set of fluid equations for electrons. The fluid equations are coupled through source terms describing electromagnetic coupling, ionization, recombination, charge exchange, and elastic scattering collisions in the low-density coronal limit. The form of each of these source terms is described in detail, and references for required rate coefficients are identified for a diverse range of atomic species. Initial efforts have been made to extend these models to incorporate some higher-density collisional effects, including ionization potential depression and three- body recombination. Some reductions of the general multifluid model are considered. First, a reduced multifluid model is derived which averages over all of the charge states (including neutrals) of each atomic species in the general multifluid model. The resulting model maintains full consistency with the general multifluid model from which it is derived by leveraging a quasi-steady-state collisional ionization equilibrium assumption to recover the ionization fractions required to make use of the general collision models. Further reductions are briefly considered to derive certain components of a single-fluid magnetohydrodynamics (MHD) model. In this case, a generalized Ohm's law is obtained, and the standard MHD resistivity is expressed in terms of the collisional models used in the general multifluid model. A number of numerical considerations required to obtain robust implementations of these multifluid models are discussed. First, an algebraic flux correction (AFC) stabilization approach for a continuous Galerkin finite element discretization of the multifluid system is described in which the characteristic speeds used in the stabilization of the fluid systems are synchronized across all species in the model. It is demonstrated that this synchronization is crucial in order to obtain a robust discretization of the multifluid system. Additionally, several different formulations are considered for describing the electromagnetics portion of the multifluid system using nodal continuous Galerkin finite element discretizations. The formulations considered include a parabolic divergence cleaning method and an implicit projection method for the traditional curl formulation of Maxwell's equations, a purely- hyperbolic potential-based formulation of Maxwell's equations, and a mixed hyperbolic-elliptic potential-based formulation of Maxwell's equations. Some advantages and disadvantages of each formulation are explored to compare solution robustness and the ease of use of each formulation. Numerical results are presented to demonstrate the accuracy and robustness of various components of our implementation. Analytic solutions for a spatially homogeneous damped plasma oscillation are derived in order to verify the implementation of the source terms for electromagnetic coupling and elastic collisions between fluid species. Ionization balance as a function of electron temperature is evaluated for several atomic species of interest by comparing to steady-state calculations using various sets of ionization and recombination rate coefficients. Several test problems in one and two spatial dimensions are used to demonstrate the accuracy and robustness of the discretization and stabilization approach for the fluid components of the multifluid system. This includes standard test problems for electrostatic and electromagnetic shock tubes in the two-fluid and ideal shock-MHD limits, a cylindrical diocotron instability, and the GEM challenge magnetic reconnection problem. A one-dimensional simplified prototype of an argon gas puff configuration as deployed on Sandia's Z-machine is used as a demonstration to exercise the full range of capabilities associated with the general multifluid model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

The role of carbonaceous aerosols on short-term variations of precipitation over North Africa

Northern Africa has been subject to extensive droughts in the late 20th century, which are frequently linked to changes in the Sea Surface Temperature (SST) in both the Atlantic and Indian Oceans. However, climate models forced by observed Sea Surface Temperatures have been unable to reproduce the magnitude of rainfall reduction over the last several decades. In this study, we propose that aerosol indirect effects (AIE) may be an important feedback mechanism to contribute this recent reduction. The climate model used here has a fully predictive aerosol life cycle. Results are presented for a set of sensitivity experiments designed to distinguish the role of aerosol direct/semi-­direct and indirect effects on regional precipitation. Changes in cloud lifetime due to the presence of carbonaceous aerosols are proposed as a key mechanism to explain the reduced rainfall over the tropical and North Africa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impact of methane and black carbon mitigation on forcing and temperature: a multi-model scenario analysis

The relatively short atmospheric lifetimes of methane (CH 4 ) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH 4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Coupling of electroelastic dynamics and direct contact ultrasonic drying formulation for annular piezoelectric bimorph transducers

A newly developed technique for drying clothes without thermal energy has been developed through the utilization of ultrasonic vibrations from piezoelectric transducers. The novel technique incorporates the actuation of a thin stainless steel disk in contact with wet fabric via annular piezoelectric rings, where water in the liquid form is atomized, transported through microchannels in the disk, and ejected as a mist. In such a system, resonance matching between the actuation portion of the transducer and the portion contacting fabric must be realized, with theoretical results from the developed electromechanical model showing a reduction in energy consumption by 50% when resonance matching is achieved. The electrically coupled distributed parameter model for an annular bimorph piezoelectric transducer is developed for optimization of ultrasonic drying technology. The thickness mode vibrations are shown to dominate the behavior of the system, where the analytically developed model can be optimized to increase the output acceleration of the transducer, thus increasing drying performance. Here, the electromechanical equation developed will be connected to the drying rates of fabrics in contact with said vibrations, where the novelty of the coupled equations and its description of the physics of ultrasonic drying will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling.

The recent growth in multifidelity uncertainty quantification has given rise to a large set of variance reduction techniques that leverage information from model ensembles to provide variance reduction for estimates of the statistics of a high-fidelity model. In this paper we provide two contributions: (1) we utilize an ensemble estimator to account for uncertainties in the optimal weights of approximate control variate (ACV) approaches and derive lower bounds on the number of samples required to guarantee variance reduction; and (2) we extend an existing multifidelity importance sampling (MFIS) scheme to leverage control variates. Our approach directly addresses a limitation of many multifidelity sampling strategies that require the usage of pilot samples to estimate covariances. As such we make significant progress towards both increasing the practicality of approximate control variates—for instance, by accounting for the effect of pilot samples—and using multifidelity approaches more effectively for estimating low-probability events. The numerical results indicate our hybrid MFIS-ACV estimator achieves up to 50% improvement in variance reduction over the existing state-of-the-art MFIS estimator, which had already shown an outstanding convergence rate compared to the Monte Carlo method, on several problems of computational mechanics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

DC Modeling of 4H-SiC JFET Gate Length Reduction at 500°C

The development of robust, high-performance integrated circuits (ICs) will enable numerous potential NASA missions of current interest, including long-duration robotic missions exploring the 460 °C surface of Venus. Currently, NASA is looking towards SiC-based devices to provide such a solution. However, the current NASA silicon carbide (SiC) JFET device with a channel length of 6μm (for recently fabricated Gen. 11 ICs) limits on mission relevant circuit capabilities [1]. In this study, we combined experiments with simulations to explore two straightforward fabrication strategies to reduce the SiC JFET channel length while maintaining turn-off behavior (Fig. 1a) needed to realize 500 °C circuit operation. The first fabrication strategy uses a shallow self-align nitrogen implant (Figure 1b) along the device's top surface but not below the gate combined with a high-dose phosphorous implant directly below the source and drain contacts. For the second fabrication strategy (Figure 1c), the high-dose phosphorous implants extended from below the contacts all the way up to the gate edges. Simulations guided gate length reductions without significant degradation in the turn-off performance. In total 12 SiC JFET variants implementing using the different fabrication strategies, gate lengths, and n-channel epilayer thickness were implemented in our simulation framework implemented in COMSOL. Since the COMSOL database does not have the material properties for 4H-SiC, these parameters were taken from the literature and implemented in COMSOL. The empirical models [2] for incomplete ionization, Auger recombination, low field mobility, and Shockley-Read-Hall recombination were implemented to account for material-specific device behavior.

4H-SiC JFET↗
DOE OSTI2017

Chemotherapy Response Assessment by FDG-PET-CT in Early-stage Classical Hodgkin Lymphoma: Moving Beyond the Five-Point Deauville Score

Purpose: In early-stage classical Hodgkin lymphoma, fluorodeoxyglucose positron emission tomography (PET)-computed tomography (CT) scans are performed routinely after chemotherapy, and the 5-point Deauville score is used to report the disease response. We hypothesized that other PET-CT parameters, considered in combination with Deauville score, would improve risk stratification. Methods and Materials: Patients treated for stage I to II Hodgkin lymphoma from 2003 to 2013, who were aged ≥18 years and had analyzable PET-CT scans performed before and after chemotherapy, were eligible. The soft tissue volume (STV), maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis were recorded from the PET-CT scans before and after chemotherapy. Reductions were defined as 1 − (final PET-CT value)/(corresponding initial PET-CT value). The primary endpoint was freedom from progression (FFP). Results: For 202 patients treated with chemotherapy with or without radiation therapy, the 5-year FFP was 89% (95% confidence interval 85%-93%). All PET-CT parameters were strongly associated with the Deauville score (P<.001) and FFP (P<.0001) on univariate analysis. The Deauville score was highly predictive of FFP (C-index 0.89) but was less discriminating in the Deauville 1 to 4 subset (C-index 0.67). Therefore, we aimed to identify PET-CT parameters that would improve risk stratification for this subgroup (n=187). STV reduction was predictive of outcome (C-index 0.71) and was dichotomized with an optimal cutoff of 0.65 (65% reduction in STV). A model incorporating the Deauville score and STV reduction predicted FFP more accurately than either measurement alone in the Deauville 1 to 4 subset (C-index 0.83). The improvement in predictive accuracy of this composite measure compared with the Deauville score alone met statistical significance (P=.045). Conclusions: The relative reduction in tumor size is an independent predictor of outcome. Combined with the Deauville score, it might improve risk stratification and contribute to response-adapted individualization of therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1978

Significance of radiation models in investigating the flow phenomena around a Jovian entry body

Formulation is presented to demonstrate the significance of a simplified radiation model in investigating the flow-phenomena in the viscous radiating shock layer of a Jovian entry body. For this, a nongray absorption model for hydrogen-helium gas is developed which consists of 30 steps over the spectral range of 0-20 eV. By employing this model results were obtained for temperature, pressure, density, and radiative flux in the shock layer and along the body surface. These are compared with results of two sophisticated radiative transport models available in the literature. Use of the present radiation model results in significant reduction in computational time. Results of this model are found to be in general agreement with results of other models. It is concluded that use of the present model is justified in investigating the flow phenomena around a Jovian entry body because it is relatively simple, computationally fast, and yields fairly accurate results.

Tiwari, S. N.↗
NASA NTRS2006

Computational Analysis of a Chevron Nozzle Uniquely Tailored for Propulsion Airframe Aeroacoustics

A computational flow field and predicted jet noise source analysis is presented for asymmetrical fan chevrons on a modern separate flow nozzle at take off conditions. The propulsion airframe aeroacoustic asymmetric fan nozzle is designed with an azimuthally varying chevron pattern with longer chevrons close to the pylon. A baseline round nozzle without chevrons and a reference nozzle with azimuthally uniform chevrons are also studied. The intent of the asymmetric fan chevron nozzle was to improve the noise reduction potential by creating a favorable propulsion airframe aeroacoustic interaction effect between the pylon and chevron nozzle. This favorable interaction and improved noise reduction was observed in model scale tests and flight test data and has been reported in other studies. The goal of this study was to identify the fundamental flow and noise source mechanisms. The flow simulation uses the asymptotically steady, compressible Reynolds averaged Navier-Stokes equations on a structured grid. Flow computations are performed using the parallel, multi-block, structured grid code PAB3D. Local noise sources were mapped and integrated computationally using the Jet3D code based upon the Lighthill Acoustic Analogy with anisotropic Reynolds stress modeling. In this study, trends of noise reduction were correctly predicted. Jet3D was also utilized to produce noise source maps that were then correlated to local flow features. The flow studies show that asymmetry of the longer fan chevrons near the pylon work to reduce the strength of the secondary flow induced by the pylon itself, such that the asymmetric merging of the fan and core shear layers is significantly delayed. The effect is to reduce the peak turbulence kinetic energy and shift it downstream, reducing overall noise production. This combined flow and noise prediction approach has yielded considerable understanding of the physics of a fan chevron nozzle designed to include propulsion airframe aeroacoustic interaction effects.

Massey, Steven J.↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗