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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Surface reconstruction from scattered data through pruning of unstructured grids

This paper describes an algorithm for reconstructing a surface from a randomly digitized object. Scan data (treated as a cloud of points) is first tesselated out to its convex hull using Delaunay triangulation. The line-of-sight between each surface point and the scanning device is traversed, and any tetrahedra which are pierced by it are removed. The remaining tetrahedra form an approximate solid model of the scanned object. Due to the inherently limited resolution of any scan, this algorithm requires two additional procedures to produce a smooth, polyhedral surface: one process removes long, narrow tetrahedra which span indentations in the surface between digitized points; the other smooths sharp edges. The results for a moderately resolved sample body and a highly resolved aircraft are displayed.

Maksymiuk, C. M.↗
NASA NTRS2018

LAVA Simulations for the 3rd AIAA CFD High Lift Prediction Workshop with Body Fitted Grids

In response to the 3rd AIAA CFD High Lift Prediction Workshop, the workshop cases were analyzed using Reynolds-averaged Navier-Stokes flow solvers within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework. For the workshop cases the advantages and limitations of both overset-structured an unstructured polyhedral meshes were assessed. The workshop included 3 cases: a 2D airfoil validation case, a mesh convergence study using the High Lift Common Research Model, and a nacelle/pylon integration study using the JAXA (Japan Aerospace Exploration Agency) Standard Model. The 2D airfoil case from the workshop is used to verify the implementation of the Spalart-Allmaras turbulence model along with some of its variants within the solver. The High Lift Common Research Model case is used to assess solver performance and accuracy at varying mesh resolutions, as well as identify the minimum mesh fidelity required for LAVA on this class of problem. The JAXA Standard Model case is used to assess the solver's sensitivity to the turbulence model and to compare the structured and unstructured mesh paradigms. These workshop cases have helped establish best practices for high lift flow configurations for the LAVA solver.

LAVA↗
DOE OSTI2016

Effect of inter-species selective interactions on the thermodynamics and nucleation free-energy barriers of a tessellating polyhedral compound

The phase behavior and the homogeneous nucleation of an equimolar mixture of octahedra and cuboctahedra are studied using thermodynamic integration, Gibbs-Duhem integration, and umbrella sampling simulations. The components of this mixture are modeled as polybead objects of equal edge lengths so that they can assemble into a space-filling compound with the CsCl crystal structure. Taking as reference the hard-core system where the compound crystal does not spontaneously nucleate, we quantified the effect of inter-species selective interactions on facilitating the disorder-to-order transition. Facet selective and facet non-selective inter-species attractions were considered, and while the former was expectedly more favorable toward the target tessellating structure, the latter was found to be similarly effective in nucleating the crystal compound. Ranges for the strength of attractions and degree of supersaturation were identified where the nucleation free-energy barrier was small enough to foretell a fast process but large enough to prevent spinodal fluctuations that can trap the system in dense metastable states lacking long-range order. At those favorable conditions, the tendency toward the local orientational order favored by packing entropy is amplified and found to play a key role seeding nuclei with the CsCl structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗
NASA NTRS1990

Positional estimation techniques for an autonomous mobile robot

Techniques for positional estimation of a mobile robot navigation in an indoor environment are described. A comprehensive review of the various positional estimation techniques studied in the literature is first presented. The techniques are divided into four different types and each of them is discussed briefly. Two different kinds of environments are considered for positional estimation; mountainous natural terrain and an urban, man-made environment with polyhedral buildings. In both cases, the robot is assumed to be equipped with single visual camera that can be panned and tilted and also a 3-D description (world model) of the environment is given. Such a description could be obtained from a stereo pair of aerial images or from the architectural plans of the buildings. Techniques for positional estimation using the camera input and the world model are presented.

Nandhakumar, N.↗
DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1991

Operator-coached machine vision for space telerobotics

A prototype system for interactive object modeling has been developed and tested. The goal of this effort has been to create a system which would demonstrate the feasibility of high interactive operator-coached machine vision in a realistic task environment, and to provide a testbed for experimentation with various modes of operator interaction. The purpose for such a system is to use human perception where machine vision is difficult, i.e., to segment the scene into objects and to designate their features, and to use machine vision to overcome limitations of human perception, i.e., for accurate measurement of object geometry. The system captures and displays video images from a number of cameras, allows the operator to designate a polyhedral object one edge at a time by moving a 3-D cursor within these images, performs a least-squares fit of the designated edges to edge data detected with a modified Sobel operator, and combines the edges thus detected to form a wire-frame object model that matches the Sobel data.

Bon, Bruce↗
DOE OSTI2017

The arbitrary order mimetic finite difference method for a diffusion equation with a non-symmetric diffusion tensor

Here, we present the arbitrary order mimetic finite difference (MFD) discretization for the diffusion equation with non-symmetric tensorial diffusion coefficient in a mixed formulation on general polygonal meshes. The diffusion tensor is assumed to be positive definite. The asymmetry of the diffusion tensor requires changes to the standard MFD construction. We also present new approach for the construction that guarantees positive definiteness of the non-symmetric mass matrix in the space of discrete velocities. The numerically observed convergence rate for the scalar quantity matches the predicted one in the case of the lowest order mimetic scheme. For higher orders schemes, we observed super-convergence by one order for the scalar variable which is consistent with the previously published result for a symmetric diffusion tensor. The new scheme was also tested on a time-dependent problem modeling the Hall effect in the resistive magnetohydrodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Vertex protein PduN tunes encapsulated pathway performance by dictating bacterial metabolosome morphology

Engineering subcellular organization in microbes shows great promise in addressing bottlenecks in metabolic engineering efforts; however, rules guiding selection of an organization strategy or platform are lacking. Here, we study compartment morphology as a factor in mediating encapsulated pathway performance. Using the 1,2-propanediol utilization microcompartment (Pdu MCP) system from Salmonella enterica serovar Typhimurium LT2, we find that we can shift the morphology of this protein nanoreactor from polyhedral to tubular by removing vertex protein PduN. Analysis of the metabolic function between these Pdu microtubes (MTs) shows that they provide a diffusional barrier capable of shielding the cytosol from a toxic pathway intermediate, similar to native MCPs. However, kinetic modeling suggests that the different surface area to volume ratios of MCP and MT structures alters encapsulated pathway performance. Finally, we report a microscopy-based assay that permits rapid assessment of Pdu MT formation to enable future engineering efforts on these structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Combined Machine Learning and High-Energy X-ray Diffraction Approach to Understanding Liquid and Amorphous Metal Oxides

Determining the structure-property relations of liquid and amorphous metal oxides is challenging, due to their variable short-range order and polyhedral connectivity. To predict chemically realistic structures, we have developed a Machine Learned, Gaussian Approximation Potential (GAP) for HfO 2 , with a focus on enhanced sampling of the training database and accurate density functional theory calculations. By using training datasets for the GAP model at the level of Density Functional Theory-Strongly Constrained and Appropriately Normed (DFT-SCAN) level of theory, our results show that the topology of both the low viscosity liquid and the amorphous form are dominated by edge-shared chains and small corner-shared rings of polyhedra. This topology is shown to be consistent with the structure of other liquid and amorphous transition metal oxides of variable ion size, such as TiO 2 and ZrO 2 . Current limitations of the ML-GAP modeling method for obtaining glass structures and future perspectives are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Algorithmic construction of SSA-compatible extreme rays of the subadditivity cone and the N = 6 solution

We compute the set of all extreme rays of the 6-party subadditivity cone that are compatible with strong subadditivity. In total, we identify 208 new (genuine 6-party) orbits, 52 of which violate at least one known holographic entropy inequality. For the remaining 156 orbits, which do not violate any such inequalities, we construct holographic graph models for 150 of them. For the final 6 orbits, it remains an open question whether they are holographic. Consistent with the strong form of the conjecture in [1], 148 of these graph models are trees. However, 2 of the graphs contain a “bulk cycle”, leaving open the question of whether equivalent models with tree topology exist, or if these extreme rays are counterexamples to the conjecture. The paper includes a detailed description of the algorithm used for the computation, which is presented in a general framework and can be applied to any situation involving a polyhedral cone defined by a set of linear inequalities and a partial order among them to find extreme rays corresponding to down-sets in this poset.

AdS-CFT correspondence↗
DOE OSTI2024

Multi-Factor-Coupled, Ahead-of-Time Aggregation of Power Flexibility Under Forecast Uncertainty

The increasing penetration of distributed energy resources (DERs) is significantly reshaping the role of distribution systems under active energy management. To aggregate the active-reactive power flexibility of DERs dispersed at the feeder and provide capacity support to the transmission system, it is essential to efficiently identify feasible substation power injection trajectories. This paper introduces a novel ahead-of-time flexibility characterization method to address it. First, a polyhedral non-feeder-level power flexibility region (PFR) is constructed, accounting for various time-dependent, power-coupled, and forecast error uncertainties. Then, a polyhedral feeder-level PFR is analytically derived through a coordinate transformation, which can reveal the uncertainty propagation path, i.e., how uncertainty applies to the feeder-level PFR. To facilitate the high-level application, a tractable chance-constrained Chebyshev centering optimization model is further developed to find a ball-shaped inner approximation of the feeder-level PFR. Finally, the proposed method is validated on a modified IEEE 123-bus test system. Here, both theoretical and experimental results show that, with appropriate robustness parameter settings, the proposed method can make the approximated PFR less conservative with abundant robustness against forecast error uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Predicting initial dissolution rates using structural features from molecular dynamics simulations

Predicting chemical durability of glass materials is important for various applications from daily life such as drink glass and kitchen ware to advanced technologies such as nuclear waste disposal and biomedicine. In this work, we explored prediction of initial dissolution rate through structural features from molecular dynamics (MD) simulations for a wide range of glass compositions (total 28) including borosilicate and aluminosilicate glasses, ZrO 2 -containing and V 2 O 5 -containing boroaluminosilicate glasses. The initial dissolution rates (r 0 ) measured experimentally at 90 °C with varying solution conditions were correlated with structural features (e.g., polyhedral linkages and non-bridging oxygen species) obtained from MD simulations, either from this study or from literature. Since hydrolysis of the glass network through breaking of the network former linkages (e.g., Si-O-Si, Si-O-Al, etc.) is a critical step of network glass dissolution, the statistics of these linkages obtained from MD were correlated to r0 through linear regression, where the coefficient of determination (R 2 ) and root mean square error are found to be 0.949 and 0.681, respectively. This model was compared and discussed with existing models developed by various approaches including machine learning, the kinetic rate equation, topological constraint theory, and other descriptors from MD simulations. The discussion provides insights on future model improvements to predict glass dissolution. In addition, the impact of V 2 O 5 on the glass dissolution was examined in detail, implicating that the impact is not the same across all glass compositions and test conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Temperature-dependent Structural and Spectroscopic Studies of (Bi 1– x Fe x )FeO 3

We report on temperature-dependent structural and spectroscopic features of (Bi 1–x Fe x )FeO 3 perovskite for x = 0.15 and 0.25. Samples were synthesized by heating quantum crystalline precursors obtained by the polyol method. Crystal structures of each composition were obtained from in-house X-ray, synchrotron X-ray, and time-of-flight neutron powder diffraction data Rietveld refinements. Partial replacement of the Bi site by the Fe 3+ cation significantly changes the crystal physicochemical properties, such as thermal expansion, polyhedral distortion, Debye temperature, and vibrational and magnetic properties. Whereas BiFeO 3 is multiferroic, both Bi 0.85 Fe 0.15 FeO 3 and Bi 0.75 Fe 0.25 FeO 3 are found to be superparamagnetic, as observed by temperature-dependent Mössbauer and SQUID measurements. Lattice thermal expansion was modeled using the Debye–Einstein-anharmonicity approach. Debye temperatures obtained from the mean-squared atomic displacement parameter and lattice thermal expansion are compared. Furthermore, temperature dependence of selective Raman modes is also analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

DDA Computations of Porous Aggregates with Forsterite Crystals: Effects of Crystal Shape and Crystal Mass Fraction

Porous aggregate grains are commonly found in cometary dust samples and are needed to model cometary IR spectral energy distributions (SEDs). Models for thermal emissions from comets require two forms of silicates: amorphous and crystalline. The dominant crystal resonances observed in comet SEDs are from Forsterite (Mg2SiO4). The mass fractions that are crystalline span a large range from 0.0 < or = fcrystal < or = 0.74. Radial transport models that predict the enrichment of the outer disk (>25 AU at 1E6 yr) by inner disk materials (crystals) are challenged to yield the highend-range of cometary crystal mass fractions. However, in current thermal models, Forsterite crystals are not incorporated into larger aggregate grains but instead only are considered as discrete crystals. A complicating factor is that Forsterite crystals with rectangular shapes better fit the observed spectral resonances in wavelength (11.0-11.15 microns, 16, 19, 23.5, 27, and 33 microns), feature asymmetry and relative height (Lindley et al. 2013) than spherically or elliptically shaped crystals. We present DDA-DDSCAT computations of IR absorptivities (Qabs) of 3 micron-radii porous aggregates with 0.13 < or = fcrystal < or = 0.35 and with polyhedral-shaped Forsterite crystals. We can produce crystal resonances with similar appearance to the observed resonances of comet Hale- Bopp. Also, a lower mass fraction of crystals in aggregates can produce the same spectral contrast as a higher mass fraction of discrete crystals; the 11micron and 23 micron crystalline resonances appear amplified when crystals are incorporated into aggregates composed otherwise of spherically shaped amorphous Fe-Mg olivines and pyroxenes. We show that the optical properties of a porous aggregate is not linear combination of its monomers, so aggregates need to be computed. We discuss the consequence of lowering comet crystal mass fractions by modeling IR SEDs with aggregates with crystals, and the implications for radial transport models of our protoplanetary disk.

Crystal Shape and Crystal Mass Fraction↗
DOE OSTI2017

Rates and mechanisms of uranyl oxyhydroxide mineral dissolution

Uranyl oxyhydroxide minerals are important weathering products in uranium-contaminated surface and subsurface environments that regulate dissolved uranium concentrations. However, dissolution rates for this class of minerals and associated dissolution mechanisms have not been previously reported for circumneutral pH conditions, particularly for the case of flow through porous media. In this paper, the dissolution rates of K- and Na-compreignacite (K 2 (UO 2 ) 6 O 4 (OH) 6 ·8H 2 O and Na 2 (UO 2 ) 6 O 4 (OH) 6 ·8H 2 O respectively) were measured using flow-through columns reacted with two simulated background porewater (BPW) solutions of low and high dissolved total carbonate content (ca. 0.2 and 2.8 mmol L -1 ). Column materials were characterized before and after reaction with electron microscopy, bulk chemistry, and EXAFS to identify structural and chemical changes during dissolution and to obtain insight into molecular-scale processes. The reactive transport code CrunchFlow was used to calculate overall dissolution rates while accounting for fluid transport and changes in mineral volume and reactive surface area and results were compared to steady-state dissolution rate calculations. In low carbonate BPW systems, interlayer K and Na were initially leached from both minerals, and in Na-compreignacite, K and minor divalent cations from the input solution were incorporated into the mineral structure. Results of characterization analyses suggested that after reaction both K- and Na-compreignacite resembled a disordered K-compreignacite with altered surfaces. A 10-fold increase in dissolved carbonate concentration and corresponding increase in pH (from 6.65 to 8.40) resulted in a net removal of 58-87% of total uranium mass from the columns, compared to <1% net loss in low carbonate BPW systems. Steady-state release of dissolved uranium was not observed with high carbonate solutions and post-reaction characterizations indicated a lack of development of leached or altered surfaces. Dissolution rates (normalized to specific surface area) were about 2.5-3 orders-of-magnitude faster in high versus low carbonate BPW systems, with Na-compreignacite dissolving more rapidly than K-compreignacite under both BPW conditions, possibly due to greater ion exchange (1.57·10 -10 vs. 1.28·10 -13 mol m -2 s -1 [log R = -9.81 and -12.89] and 5.79·10 -10 vs. 3.71·10 -13 mol m -2 s -1 [log R = -9.24 and -12.43] for K- and Na-compreignacite respectively). Experimental and spectroscopic results suggest that the dissolution rate is controlled by bond breaking of a uranyl group and detachment from polyhedral layers of the mineral structure. With higher dissolved carbonate concentrations, this rate-determining step is accelerated by the formation of Ca-uranyl carbonate complexes (dominant species under these conditions), which resulted in an increase of the dissolution rates. Optimization of both dissolution rate and mineral volume fraction in the reactive transport model to account for uranium mass removal during dissolution more accurately reproduced effluent data in high carbonate systems, and resulted in faster overall rates compared with a steady-state dissolution assumption. Finally, this study highlights the importance of coupling reaction and transport processes during the quantification of mineral dissolution rates to accurately predict the fate of contaminants such as uranium in porous geomedia.

58 GEOSCIENCES↗
DOE OSTI2023

How does your gyroid grow? A mesoatomic perspective on supramolecular, soft matter network crystals

We propose and describe a framework to understand the structure of supramolecular network crystals formed in soft matter in terms of mesoatomic building blocks, collective groupings of amphiphilic molecules that play a role analogous to atomic or molecular subunits of hard matter crystals. While the concept of mesoatoms is intuitive and widely invoked in crystalline arrangements of spherelike or cylinderlike (micellelike) domains, analogous notions of natural and physically meaningful building blocks of triply periodic network (TPN) crystals, like the double-gyroid or double-diamond structures are obscured by the complex, bicontinuous domain shapes and intercatenated topologies of the double networks. Focusing on the specific example of diblock copolymer melts, we propose generic rules for decomposing TPN crystals into a unique set of mesoatomic building blocks. Based on physically motivated principles, the combination of symmetries and topologies of these structures point to mesoatomic elements associated with the nodal connections, leading to mesoatomic volumes that are nonconvex and bound by smoothly curved faces, unlike the more familiar Voronoi polyhedral shapes associated with spherelike and cylinderlike mesoatoms. We analyze the shapes of these mesoatoms, their internal structure, and importantly, their local packing with neighbor mesoatomic units. Importantly, we hypothesize that mesoatoms are kinetically favored intermediate structures whose local shapes and packing template network crystal assembly on long time scales. We propose and study a minimal energetic model of mesoatom assembly for three different cubic double-network crystals, based on local shape packing, which predicts a detailed picture for kinetics of intercatenation and surface growth. Based on these analyses, we discuss several possible extensions and elaborations of the mesoatomic description of supramolecular soft matter network crystals, most notably the implications of mesoatomic malleability, a feature that distinguishes soft matter from hard matter crystals. We describe experimental observations of malleable mesoatomic units in the precursor sponge phase as well as in ordered cubic networks and suggest possibilities for observing mesoatoms in primordial, precrystalline states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗