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DOE OSTI2013

Theory Aided Design of Active and Durable Nanoscale Cathode Catalysts (Final Report)

One of the greatest technological hurdles to deployment of fuel cells relates to the sluggish activity, low durability and the high cost of the catalysts that are currently employed. For automotive PEM fuel cells to become commercially viable, the Pt-specific power density would need to be reduced to less than 0.2gPt/kW (at cell voltages >0.65 V). This would require the Pt loadings to be less than 0.15 mg Pt /cm 2 MEA within the membrane electrode assembly. This could be achieved by enhancing the catalytic activity at the cathode, thus lowering its overpotential. Various different Pt-alloys have shown 2-4 times enhanced activities over Pt alone but still suffer some of the same durability issues as that of the pure Pt. There is a general loss of active Pt due to dissolution and sintering. While there have been a number of elegant fundamental experimental and theoretical studies on ideal single crystal Pt and Pt alloy surfaces which have helped to elucidate the factors that control the activity, there have been very few fundamental studies focused on the stability, reactivity and durability of well-defined Pt nanoparticles. We carried out ab initio density functional theory together with a novel double reference method that we developed to simulate constant potential electrochemical systems in order to model the electrocatalytic reduction of oxygen over model Pt alloy surfaces and nanoparticles. These simulations were used to probe the factors that control the electrocatalytic activity, guide the potential selection of new materials and test their stability under reaction conditions. Ab initio calculations were used to determine the reaction energies and activation barriers for a comprehensive array of different elementary adsorption, desorption, surface reaction and diffusion steps over Pt and Pt alloys involved in the electroreduction of oxygen as a function of surface coverage, the electrochemical potential and temperature. The calculations were used to simulate the potential dependent adsorption and surface reaction energies along with activation barriers in order to determine the kinetics for different surface structures and structural features (step edge and corner sites) to provide the necessary input for kinetic Monte Carlo simulations to follow the rates of reaction. More coarse-grained simulated annealing methods were used to help establish the lowest energy structures and morphologies for different Pt and Pt-alloy nanoparticles that form. The results from the DFT calculations were used to establish an ab initio-derived kinetic database that was used in both 2D and 3D kinetic Monte Carlo simulations that were used to follow the electrocatalytic performance over different particle sizes, shapes and compositions. The ab initio calculations together with the kinetic Monte Carlo simulations were used to complete the following objectives: 1) Determine the controlling elementary reaction pathways and intrinsic kinetics involved in ORR and their potential dependent behavior; 2) Establish the influence of the extrinsic reaction environment including surface structure, alloy composition and spatial arrangement and the humidity on ORR kinetics; 3) Elucidate the effects of particle size and morphology as well as the atomic structure and composition of nanoparticles of Pt, Pt 3 Co, Pt 3 Ni, Pt 3 Fe and other Pt-alloys on the electrocatalytic activity and reaction selectivity; 5) Construct surface Pourbaix phase diagrams for different Pt and Pt-alloys in order to map out the most stable surface phases for different material compositions and reaction conditions; 6) Elucidate the mechanisms that control dissolution and re-deposition of Pt.

08 HYDROGEN↗

DOE OSTI2018

An Improved Representation of Vegetative Filter Strips in SWAT

Abstract. Vegetative filter strips (VFS) are popular conservation practices installed at the edges of agricultural fields to reduce losses of pollutants from agricultural areas to receiving waterbodies. The recent interest in using VFS areas as multifunctional landscapes necessitates an improved depiction of VFS in simulation models. This study is aimed to enhance the physical representation of VFS in the Soil and Water Assessment Tool (SWAT) to improve the representation of ecohydrologic processes and land management practices in VFS areas. The proposed enhancement enables routing of water, sediment, and nutrients from the source area through the VFS area and makes the infiltrated water and nutrients available for filter crop uptake. The improvements are implemented in SWAT by modifying input files through Matlab scripts and by changing SWAT subroutines to enable routing. The model improvements are tested with three paired watershed studies with and without edge-of-field VFS in central Iowa. The improved model estimated 46% runoff reduction, 91% sediment reduction, 83% total phosphorus reduction, and 54% nitrate reduction with VFS, and these estimates closely matched the measured VFS reductions. The improved model was able to represent increased infiltration, soil moisture, and denitrification in the VFS area, along with accurately capturing crop yields in the source and VFS areas. Overall, the results indicate improved physical representation of VFS in SWAT. Keywords: Conservation measures, Flexible buffer strips, Multifunctional buffers, SWAT model, Vegetative filter strips.

Agriculture↗

NASA NTRS1984

The SIMRAND methodology - Simulation of Research and Development Projects

In research and development projects, a commonly occurring management decision is concerned with the optimum allocation of resources to achieve the project goals. Because of resource constraints, management has to make a decision regarding the set of proposed systems or tasks which should be undertaken. SIMRAND (Simulation of Research and Development Projects) is a methodology which was developed for aiding management in this decision. Attention is given to a problem description, aspects of model formulation, the reduction phase of the model solution, the simulation phase, and the evaluation phase. The implementation of the considered approach is illustrated with the aid of an example which involves a simplified network of the type used to determine the price of silicon solar cells.

Miles, R. F., Jr.↗

NASA NTRS2020

Progressive Failure Analysis Correlation with Notched Composite Laminate Test Data

Testing of small and intermediate laminate panels with notches was performed and Progressive Failure Analyses (PFA) models were developed for aid in test planning and for correlation with the test data. Two progressive damage failure models were included in the study: the commercially available Abaqus built-in damage model and COmplete STress Reduction (COSTR) damage model developed at NASA Langley Research Center (LaRC). The finite elements models used for the analysis were developed using shell elements. The pre-test PFA results obtained from the two damage models were compared to test data. Then a post-test PFA with updated material properties based on additional available material property data was executed with the COSTR damage model and compared to the test data. The panels tested in compression all exhibited less scatter in the failure load with self-similar failure behavior. The panels tested in tension exhibited more scatter in the failure load with a failure mode that included delamination of plies. However, a self-similar crack path was also observed as the overall failure mode for all panels tested. When comparing test data to the pre-test analysis results, both damage models with shell element models were considered adequate for predicting the behavior and failure load of both the small and intermediate panels when tested in compression. However, for the tension load cases, larger differences were observed between the test and analysis results. When comparing test data to the post-test analysis performed using the COSTR damage model, better correlation was observed. However, large discrepancies were still observed for the tension load cases. Consequently, a higher fidelity finite element model including solid elements for sub-laminates and the modeling of cohesive layers between sub-laminate layers is recommended for tension loading of notched composite laminates.

Damage Model,Progressive Failure Analysis,Open Hol↗

NASA NTRS1974

Digital computer modeling of the process of reduction of redundancy in multichannel telemetry information by the method of adaptive discretization with associative sorting

Digital computer modeling of the process of adaptive discretization with associative sorting of actual multichannel telemetry information is discussed. The main task in modeling is production of initial data for determination of dependences describing the operation of the on-board information compression device. Conclusions are presented including the shortcomings of telemetric information used in modeling.

Tolmadzheva, T. A.↗

DOE OSTI2023

Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computationally expensive. This work proposes a context-aware multi-fidelity Monte Carlo method that optimally balances the costs of training low-fidelity models with the costs of Monte Carlo sampling. It generalizes the previously developed context-aware bi-fidelity Monte Carlo method to hierarchies of multiple models and to more general types of low-fidelity models. When training low-fidelity models, the proposed approach takes into account the context in which the learned low-fidelity models will be used, namely for variance reduction in Monte Carlo estimation, which allows it to find optimal trade-offs between training and sampling to minimize upper bounds of the mean-squared errors of the estimators for given computational budgets. This is in stark contrast to traditional surrogate modeling and model reduction techniques that construct low-fidelity models with the primary goal of approximating well the high-fidelity model outputs and typically ignore the context in which the learned models will be used in upstream tasks. Further, the proposed context-aware multi-fidelity Monte Carlo method applies to hierarchies of a wide range of types of low-fidelity models such as sparse-grid and deep-network models. Numerical experiments with the gyrokinetic simulation code Gene show speedups of up to two orders of magnitude compared to standard estimators when quantifying uncertainties in small-scale fluctuations in confined plasma in fusion reactors. This corresponds to a runtime reduction from 72 days to four hours on one node of the Lonestar6 supercomputer at the Texas Advanced Computing Center.

42 ENGINEERING↗

DOE OSTI2025

Attractive Noncovalent Interactions versus Steric Confinement in Asymmetric Supramolecular Catalysis

The remarkable catalytic performance of enzymes stems from their ability to engage in precise noncovalent interactions (NCIs) within a sterically confined space. Supramolecular catalysis seeks to emulate and understand these strategies through the rational design of simple and controlled catalyst microenvironments. While both steric confinement and attractive interactions have been invoked as key to host activity, their relative contribution to rate enhancement and selectivity, as well as potential trade-offs, remains an outstanding question. Here, we address this question by systematically comparing two metal–organic supramolecular catalysts, which differ in the strength of their attractive noncovalent interactions and in their cavity volume. Our findings reveal that the catalyst with the larger cavity, and with stronger available NCIs, exhibits both significant rate acceleration (100-fold) and enhanced enantioselectivity (84% vs 14% ee) in a model ketone reduction compared to its smaller analogue. Mechanistic analysis, binding competition experiments, and computational modeling indicate that these differences predominantly stem from stabilizing noncovalent interactions in the larger catalyst, a result that challenges existing steric-based models of supramolecular stereoinduction. Understanding the governing factors of asymmetric induction and rate acceleration in supramolecular hosts will undoubtedly inform future catalyst design.

Catalysts↗

DOE OSTI2020

Dynamic Phasor Modeling of Various Multipulse Rectifiers and a VSI Fed by 18-Pulse Asymmetrical Autotransformer Rectifier Unit for Fast Transient Analysis

To study the fast modelling of dynamic characteristics caused by power electronic switching, the dynamic phasor (DP) theory based on the time-varying Fourier decomposition and frequency shifting is firstly applied to the modelling of various multipulse rectifiers. The DP model for symmetrical 12-pulse phase-shifting reactor rectifier unit (PSR-RU) is derived with model order reduction, relations between ac and dc terminals, and Taylor series expansion. The DP model of asymmetrical 18-pulse autotransformer rectifier unit (AT-RU) is proposed based on the switching functions expressed in the DP domain. Meanwhile, the DP model of voltage source inverter (VSI) fed by asymmetrical 18-pulse AT-RU is built with the harmonic state-space (HSS) equations. Under both balanced and unbalanced conditions, the good calculation accuracy and rapid simulation speed of the developed DP models are validated by the detailed time-domain (TD) simulation.

42 ENGINEERING↗

NASA NTRS1989

Steady state cooling flow models with gas loss for normal elliptical galaxies

A grid of cooling flow models for the hot gas in normal elliptical galaxies is calculated, including the loss of gas due to inhomogeneous cooling. The loss process is modeled as a distributed sink for the gas with the rate of loss being proportional to the local cooling rate. The cooling flow models with gas loss have smaller sonic radii, smaller inflow rates in their central regions, lower densities, and higher temperatures than homogeneous models. The reduction in the amount of hot gas flowing into the center of the models brings the models into much better agreement with the observed X-ray surface brightness profiles of elliptical galaxies. However, there is a large dispersion in the observed X-ray luminosities of ellipticals, and this cannot be explained by variations in the efficiency of gas loss. The gas-loss models have X-ray surface brightness profiles which are much less centrally peaked than the no-gas-loss models.

Sarazin, Craig L.↗

NASA NTRSDate not supplied

Forced Displacement Technique for Measuring Blunt Body Aerodynamics in a Magnetic Suspension Wind Tunnel

The Old Dominion University/NASA Langley 6-Inch Magnetic Suspension Wind Tunnel has developed the ability to levitate blunt bodies which can oscillate freely about the yaw axis. This allows for the measurement of static and dynamic stability coefficients without sting interference. The magneic suspension controller introduces other translational forces which affect the vehicle dynamics complicating data reduction. Exciting model oscillations in a reliable way has also been a challenge. A new test method has been developed that produces capsule oscillations from forced oscillatory translational motion at the resonant yaw oscillatory frequency of the capsule. After oscillations are excited, the translational forcing motion is suspended to record free oscillation behavior as well. A data reduction method whereby a linear model of the translational and oscillatory motion is used to fit to the measured data and solve for aerodynamic coefficients has also been developed. The work presented shows that the new data reduction

blunt body↗

NASA NTRSDate not supplied

Forced Displacement Technique for Measuring Blunt Body Aerodynamics in a Magnetic Suspension Wind Tunnel

blunt body↗

NASA NTRS1983

Assessment of current state of the art in modeling techniques and analysis methods for large space structures

Advances in continuum modeling, progress in reduction methods, and analysis and modeling needs for large space structures are covered with specific attention given to repetitive lattice trusses. As far as continuum modeling is concerned, an effective and verified analysis capability exists for linear thermoelastic stress, birfurcation buckling, and free vibration problems of repetitive lattices. However, application of continuum modeling to nonlinear analysis needs more development. Reduction methods are very effective for bifurcation buckling and static (steady-state) nonlinear analysis. However, more work is needed to realize their full potential for nonlinear dynamic and time-dependent problems. As far as analysis and modeling needs are concerned, three areas are identified: loads determination, modeling and nonclassical behavior characteristics, and computational algorithms. The impact of new advances in computer hardware, software, integrated analysis, CAD/CAM stems, and materials technology is also discussed.

Noor, A. K.↗

DOE OSTI2014

Theoretical foundation for measuring the groundwater age distribution.

In this study, we use PFLOTRAN, a highly scalable, parallel, flow and reactive transport code to simulate the concentrations of 3H, 3He, CFC-11, CFC-12, CFC-113, SF6, 39Ar, 81Kr, 4He and themean groundwater age in heterogeneous fields on grids with an excess of 10 million nodes. We utilize this computational platform to simulate the concentration of multiple tracers in high-resolution, heterogeneous 2-D and 3-D domains, and calculate tracer-derived ages. Tracer-derived ages show systematic biases toward younger ages when the groundwater age distribution contains water older than the maximum tracer age. The deviation of the tracer-derived age distribution from the true groundwater age distribution increases with increasing heterogeneity of the system. However, the effect of heterogeneity is diminished as the mean travel time gets closer the tracer age limit. Age distributions in 3-D domains differ significantly from 2-D domains. 3D simulations show decreased mean age, and less variance in age distribution for identical heterogeneity statistics. High-performance computing allows for investigation of tracer and groundwater age systematics in high-resolution domains, providing a platform for understanding and utilizing environmental tracer and groundwater age information in heterogeneous 3-D systems. Groundwater environmental tracers can provide important constraints for the calibration of groundwater flow models. Direct simulation of environmental tracer concentrations in models has the additional advantage of avoiding assumptions associated with using calculated groundwater age values. This study quantifies model uncertainty reduction resulting from the addition of environmental tracer concentration data. The analysis uses a synthetic heterogeneous aquifer and the calibration of a flow and transport model using the pilot point method. Results indicate a significant reduction in the uncertainty in permeability with the addition of environmental tracer data, relative to the use of hydraulic measurements alone. Anthropogenic tracers and their decay products, such as CFC11, 3H, and 3He, provide significant constraint oninput permeability values in the model. Tracer data for 39Ar provide even more complete information on the heterogeneity of permeability and variability in the flow system than the anthropogenic tracers, leading to greater parameter uncertainty reduction.

Gardner, William Payton↗

DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗

DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗

DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Acoustic Performance of Novel Fan Noise Reduction Technologies for a High Bypass Model Turbofan at Simulated Flights Conditions

Two novel fan noise reduction technologies, over the rotor acoustic treatment and soft stator vane technologies, were tested in an ultra-high bypass ratio turbofan model in the NASA Glenn Research Center s 9- by 15-Foot Low-Speed Wind Tunnel. The performance of these technologies was compared to that of the baseline fan configuration, which did not have these technologies. Sideline acoustic data and hot film flow data were acquired and are used to determine the effectiveness of the various treatments. The material used for the over the rotor treatment was foam metal and two different types were used. The soft stator vanes had several internal cavities tuned to target certain frequencies. In order to accommodate the cavities it was necessary to use a cut-on stator to demonstrate the soft vane concept.

Elliott, David M.↗

DOE OSTI2020

Global kinetic modeling of NH 3 -SCR with two sites of NH 3 storage on Cu-SSZ-13

A comprehensive selective catalytic reduction (SCR) model is developed to detail the global kinetic reactions in the catalyst which is involved in two type of sites for high- and low-temperature NH 3 adsorption/desorption, as well as a low temperature H 2 O storage. The model accounts for the formation of ammonium nitrate in fast SCR and the decomposition formation of ammonium nitrate in the absence of NO, and addresses N 2 O relative to NO and NO 2 reactions with NH 3 . The model has been validated against commercial Cu-SSZ-13 measurements of NH 3 inventory, NH 3 oxidation, NO oxidation, standard SCR, fast SCR and NO 2 SCR at both comprehensive steady-state and transient conditions. In addition, the application of the SCR model for emissions control over a transient drive cycle at cold start was demonstrated based on diesel oxidation catalyst (DOC) and SCR aftertreatment system for a passenger car. In conclusion, the results show that the SCR model can provide the detailed emissions estimations for steady-state and transient conditions, can assist with understanding the impact of the SCR reaction mechanism, and can assist with the design and optimization of SCR catalysts to develop innovative technologies for co-optimization of engine fuel economy and emissions control technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗