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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2018

Electron Paramagnetic Resonance Characterization of the Triheme Cytochrome from Geobacter sulfurreducens

Periplasmic cytochrome A (PpcA) is a representative of a broad class of multiheme cytochromes functioning as protein “nanowires” for storage and extracellular transfer of multiple electrons in the δ-proteobacterium Geobacter sulfurreducens. PpcA contains three bis-His coordinated hemes held in a spatial arrangement that is highly conserved among the multiheme cytochromes c 3 and c 7 families, carries low potential hemes, and is notable for having one of the lowest number of amino acids utilized to maintain a characteristic protein fold and site-specific heme function. Low temperature X-band electron paramagnetic resonance (EPR) spectroscopy has been used to characterize the electronic configuration of the Fe(III) and the ligation mode for each heme. The three sets of EPR signals are assigned to individual hemes in the three-dimensional crystal structure. The relative energy levels of the Fe(III) 3d orbitals for individual hemes were estimated from the principal g-values. The observed g-tensor anisotropy was used as a probe of electronic structure of each heme, and differences were determined by specifics of axial ligation. To ensure unambiguous assignment of highly anisotropic low-spin (HALS) signal to individual hemes, EPR analyses of iron atom electronic configurations have been supplemented with investigation of porphyrin macrocycles by one-dimensional 1 H NMR chemical shift patterns for the methyl substituents. In conclusion, within optimized geometry of hemes in PpcA, the magnetic interactions between hemes were found to be minimal, similar to the c 3 family of tetraheme cytochromes.

1H NMR↗
DOE OSTI2021

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed CoN 4 Active Sites

We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)-8-derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X-ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co-OH and Co-O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four-electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal-induced compressive strain of Co-N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two-step (i.e., Co ion doping and adsorption) Co-N-C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Experimental and Computational Mechanistic Studies Guiding the Rational Design of Molecular Electrocatalysts for Production and Oxidation of Hydrogen

Understanding how to control the movement of protons and electrons is crucial to the design of fast, efficient electrocatalysts for hydrogen production and oxidation based on earth-abundant metals. Our work seeks to elucidate fundamental questions about proton movement. We have demonstrated that incorporating a pendant amine functioning as a proton relay in the second coordination sphere of a metal complex helps proton mobility, resulting in faster and more energy efficient catalysts. Proton transfer reactions are often rate limiting, and are influenced by several factors, such as pKa values, steric effects, hydrogen bonding, and solvation/desolvation of the exogenous base and acid employed. The presence of multiple protonation sites introduces branching points along the catalytic cycle, making less productive pathways accessible, or leading to the formation of stable off-cycle species. Using ligands with only one pendant amine mitigates this problem and results in catalysts with high rates for production of H2. For H2 oxidation catalysts, iron complexes with a high H2 binding affinity were developed. However, the improvement of H2 binding enthalpy resulted in a pKa mismatch between the protonated metal center and the protonated pendant amine, and consequently to rate-limiting intramolecular proton movement. Taken altogether, our results demonstrate the necessity of optimizing the entire catalytic cycle, as the optimization of a specific catalytic step can negatively influence another step, and not necessarily lead to better catalytic performance. We discuss a general procedure, based on thermodynamic arguments, which allows the simultaneous minimization of the free energy change of each catalytic step, yielding a nearly flat free energy surface, with no large barriers due to energy mismatches from either high- or low-energy intermediates. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Pacific Northwest National Laboratory is operated by Battelle for DOE.

hydrogen, catalysis, quantum chemistry, proton tra↗
DOE OSTI2021

Mesoporous Fe-doped MgO nanoparticles as a heterogeneous photo-Fenton-like catalyst for degradation of salicylic acid in wastewater

Mesoporous Fe-doped MgO nanoparticles were synthesized using a facile sol-gel method and utilized for photo-Fenton-like degradation of salicylic acid (SA). The MgO surface dissolution facilitated an increase in the pH under the reaction conditions that allowed the Fe-MgO catalyst to be active without detectable iron leaching. Under simulated solar radiation, SA was completely degraded with an initial rate constant of 0.048 min -1 at the optimal reaction conditions of 500 ppm loading of 5% Fe-MgO, 20 mM H 2 O 2 concentration, and 50 ppm SA concentration. The catalyst was stable over 5 reaction cycles. The Fe-MgO catalyst was shown to have a surface area up to 171 m 2 /g and contain hematite (Fe 2 O 3 ) nanoparticles with octahedrally coordinated iron catalytic centers, as inferred from diffuse reflectance UV–vis measurements. Post-reaction catalyst characterization showed that some Fe 2+ was present in the catalyst due to the redox cycle during the chain initiation and propagation steps of the reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2013

White upconversion emission in Y{sub 2}O{sub 3}:Er{sup 3+}–Tm{sup 3+}–Yb{sup 3+}phosphor

Graphical abstract: Schematic energy level diagram of Er{sup 3+}–Yb{sup 3+}–Tm{sup 3+} system upon excitation at 980 nm. Highlights: ► Prepared the Er{sup 3+}–Tm{sup 3+}–Yb{sup 3+} codoped Y{sub 2}O{sub 3} phosphor. ► Excitation of the sample by 980 nm diode laser is studied. ► Explored the possibility of getting white light emission from the synthesized phosphor. ► Colour tunability of the prepared phosphor is studied. ► Temperature sensing behaviour is investigated using FIR studied. - Abstract: Er{sup 3+}–Tm{sup 3+}–Yb{sup 3+} codoped Y{sub 2}O{sub 3} phosphor has been synthesized by optimized combustion synthesis process and its white light upconversion emission property is investigated using cheap 980 nm diode laser excitation. Efficient red, green and blue light emission bands, necessary for attaining white light emission, are observed in the codoped sample. The concentration of each rare earth ion is adjusted to get the required emission. In this phosphor, interestingly, emission colour coordinates are found to almost independent on the excitation power density. The temperature sensing behaviour of the prepared samples has also been studied using fluorescence intensity ratio (FIR) technique.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Local Structure of Proton-Conducting Lanthanum Tungstate La 28-x W 4+x O 54+δ : a Combined Density Functional Theory and Pair Distribution Function Study

Lanthanum tungstate (La 28–x W 4+x O 54+δ ) is a good proton conductor and exhibits a complex fluorite-type structure. To gain further understanding of the short-range order in the structure we correlate the optimized configurations obtained by density functional theory (DFT) with the experimental atomic pair distribution function analysis (PDF) of time-of-flight neutron and synchrotron X-ray data, collected at room temperature. The local atomic arrangements cannot be described by means of any average symmetric structure. Tungsten forms WO 6 octahedra in alternating directions, La1 is mainly 8-fold coordinated in relatively symmetric cubes, and La2 is coordinated with 6 or 7 oxygens in heavily distorted cubes. Both DFT and PDF confirm that the excess tungsten (x) is incorporated in La2 (1/4, 1/4, 1/4) sites in the La 27 W 5 O 55.5 composition. This additional tungsten can be considered as a donor self-dopant in the material and has implications to the conducting properties and the defect structure.

Kalland, Liv-Elisif↗
DOE OSTI2022

Materials research and development needs to enable efficient and electrified buildings

Because of the complexity of modern buildings—with many interconnected materials, components, and systems—fully electrifying buildings will require targeted R&D and efficient coordination across those material, component, and system levels. Because buildings that consume the smallest amount of energy are easier to electrify, energy efficiency is a crucial step toward fully electrified buildings. Materials advances will play an important role in both reducing the energy intensity of buildings and electrifying their remaining energy use. Materials are currently being explored, discovered, synthesized, evaluated, optimized, and implemented across many building components, including solid-state lighting; dynamic windows and opaque envelopes; cold climate heat pumps; thermal energy storage; heating, ventilating, and air conditioning (HVAC); refrigeration; non-vapor compression HVAC; and more. In this article, we review the current state-of-the-art of materials for various buildings end uses and discuss R&D challenges and opportunities for both efficiency and electrification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Selective binding of choline by a phosphate-coordination-based triple helicate featuring an aromatic box

In nature, proteins have evolved sophisticated cavities tailored for capturing target guests selectively among competitors of similar size, shape, and charge. The fundamental principles guiding the molecular recognition, such as self-assembly and complementarity, have inspired the development of biomimetic receptors. In the current work, we report a self-assembled triple anion helicate (host 2) featuring a cavity resembling that of the choline-binding protein ChoX, as revealed by crystal and density functional theory (DFT)-optimized structures, which binds choline in a unique dual-site-binding mode. Here, this similarity in structure leads to a similarly high selectivity of host 2 for choline over its derivatives, as demonstrated by the NMR and fluorescence competition experiments. Furthermore, host 2 is able to act as a fluorescence displacement sensor for discriminating choline, acetylcholine, l-carnitine, and glycine betaine effectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Palm: Easing the Burden of Analytical Performance Modeling

Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexity (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.

annotation languages↗
DOE OSTI2021

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗
NASA NTRS2010

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Nguyen, Nhan T.↗
NASA NTRS2009

Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

Nguyen, Nhan T.↗
NASA NTRS2019

Methods of Performing Large Scale, Multidimensional Parametric Studies for Space Launch System Mission Analysis

Optimizing a large number of trajectories over a wide range of parameters is a difficult and computationally intensive, particularly when the parametric space has a large number of dimensions. Solving parametric studies like these require good initial conditions for each optimization case, which results in a significant amount of manual interaction and human judgment and can be time consuming. The Space Launch System (SLS) uses POST2 (Program to Optimize Simulated Trajectories II) to simulate different ascent trajectories and perform mission analysis. SLS mission analysis currently uses two types of large scale, multidimensional parameter spaces. The qualifying factor between these spaces is the grid density, which determines the set of applicable solution methodologies. One type has a relatively low number of dimensions (2-3), but a large number of grid coordinates (2000- 4000), whereas the second type has a relatively low number of grid coordinates (150-350), but a higher number of dimensions (7-10).

Stein, W. B.↗
DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗
NASA NTRS1994

Stereo imaging based particle velocimeter

Three dimensional coordinates of an object are determined from it's two dimensional images for a class of points on the object. Two dimensional images are first filtered by a Laplacian of Gaussian (LOG) filter in order to detect a set of feature points on the object. The feature points on the left and the right images are then matched using a Hopfield type optimization network. The performance index of the Hopfield network contains both local and global properties of the images. Parallel computing in stereo matching can be achieved by the proposed methodology.

Batur, Celal↗
NASA NTRS2002

First Principle Predictions of Isotopic Shifts in H2O

We compute isotope independent first and second order corrections to the Born-Oppenheimer approximation for water and use them to predict isotopic shifts. For the diagonal correction, we use icMRCI wavefunctions and derivatives with respect to mass dependent, internal coordinates to generate the mass independent correction functions. For the non-adiabatic correction, we use scaled SCF/CIS wave functions and a generalization of the Handy method to obtain mass independent correction functions. We find that including the non-adiabatic correction gives significantly improved results compared to just including the diagonal correction when the Born-Oppenheimer potential energy surface is optimized for H2O-16. The agreement with experimental results for deuterium and tritium containing isotopes is nearly as good as our best empirical correction, however, the present correction is expected to be more reliable for higher, uncharacterized levels.

Schwenke, David W.↗
DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant: Preprint

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗