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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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Materials with skutterudite structure have been known for a long time. Some of them are semiconductors. A typical skutterudite is CoSb(sub 3) and its thermoelectric properties were partially studied in the 1960's. Recently, it has been discovered that many skutterudite compounds are thermoelectrics with promising future.
Basic information about the computer code STAGS (Structural Analysis of General Shells) is presented to describe to potential users the scope of the code and the solution procedures that are incorporated. Primarily, STAGS is intended for analysis of shell structures, although it has been extended to more complex shell configurations through the inclusion of springs and beam elements. The formulation is based on a variational approach in combination with local two dimensional power series representations of the displacement components. The computer code includes options for analysis of linear or nonlinear static stress, stability, vibrations, and transient response. Material as well as geometric nonlinearities are included. A few examples of applications of the code are presented for further illustration of its scope.
The segregation of solute atoms at grain boundaries (GBs) can strongly impact the structural and functional properties of polycrystals. Yet, due to the limited availability of simulation tools to study polycrystals at the atomistic scale (i.e., interatomic potentials), there is a minimal understanding of the variation of solute segregation tendencies across the very complex space of GB microenvironments and the large range of alloys in which it can occur. Here, we develop an algorithmic framework that can directly learn the full spectrum of segregation energies for a metal solute atom in a metal polycrystal from ab initio methods, bypassing the need for alloy interatomic potentials. This framework offers a pathway to a comprehensive catalog of GB solute segregation with quantum accuracy, for the entire alloy space. As an initial demonstration in this pursuit, we build an extensive GB segregation database for aluminum-based alloys across the periodic table, including dozens of alloys for which there are substantially no prior data.
The aluminosilicate layers of the swelling clay mineral montmorillonite, and the saturated pores they delineate, control the mechanical properties and the transport of solutes in many natural and engineered environments. However, the structural basis of montmorillonite porosity remains poorly characterized due to the difficulty in visualizing hydrated samples in their native state. Here in this paper, we used cryogenic transmission electron microscopy (cryo-TEM) and cryo electron tomography (cryo-ET) to show that stacking defects within minimally altered, fully hydrated montmorillonite particles define multiscale porosity networks. Variations in layer lateral dimensions over tens to thousands of nanometers cause a range of topological and dynamic defects that generate pervasive curvature and introduce previously uncharacterized solute transport pathways. Observations of long-range rotational order between neighboring layers indicate that the layer-layer interactions that govern clay swelling involve three dimensional orienting forces that operate across nanoscale pores. These direct observations of the hierarchical structure of hydrated montmorillonite pore networks with nanoscale resolution reveal potentially general aspects of colloidal interactions in fluid-saturated clay minerals.
The paper outlines the nonlinear dynamic analysis of an isolated three-degree flap-lag-feather wind turbine blade under a gravity field and with shear flow. Lagrangian equations are used to derive the nonlinear equations of motion of blade for arbitrarily large angular deflections. The limit cycle analysis for forced oscillations and the determination of the principal parametric resonance of the blade due to periodic forces from the gravity field and wind shear are performed using the harmonic balance method. Results are obtained first for a two-degree flap-lag blade, then the effect of the third degree of freedom (feather) is studied. The self-excited flutter solutions are obtained for a uniform wind and with gravity forces neglected. The effects of several parameters on the blade stability are examined, including coning angle, structural damping, Lock number, and feather frequency. The limit cycle flutter solution of a typical configuration shows a substantial nonlinear softening spring behavior.
Impact-melt glasses, rich in Martian atmospheric gases, contain Martian soil fines (MSF) mixed with other coarse-grained regolith fractions which are produced during impact bombardment on Mars surface. An important characteristic of the MSF fraction is the simultaneous enrichment of felsic component accompanied by the depletion of mafic component relative to the host phase in these glasses. In addition, these glasses yield large sulfur abundances due to the occurrence of secondary mineral phases such as sulfates produced during acid-sulfate weathering of the regolith material near the Martian surface. Sulfurous gases released into atmosphere by volcanoes on Mars are oxidized to H2SO4 which deposit back on the surface of Mars as aerosol particles. Depending on the water availability, sulfuric acids dissolve into solutions which aggressively decompose the Fe-Mg silicates in the Martian regolith. During chemical weathering, structural elements such as Fe, Mg and Ca (among others) are released into the transgressing solutions. These solutions leach away the soluble components of Mg, Ca and Na, leaving behind insoluble iron as Fe3(+) hydroxysulfate mixed with poorly crystalline hydroxide- precipitates under oxidizing conditions. In this study, we focus on the elemental distribution of FeO and SO3 in the glass veins of EET79001, 507 sample, determined by Electron Microprobe and FE SEM measurements at JSC. This glass sample is an aliquot of a bigger glass inclusion ,104 analysed by where large concentrations of Martian atmospheric noble gases are found.
A consistent linearization is provided for the element-dependent corotational formulation, providing the proper first and second variation of the strain energy. As a result, the warping problem that has plagued flat elements has been overcome, with beneficial effects carried over to linear solutions. True Newton quadratic convergence has been restored to the Structural Analysis of General Shells (STAGS) code for conservative loading using the full corotational implementation. Some implications for general finite element analysis are discussed, including what effect the automatic frame invariance provided by this work might have on the development of new, improved elements.
This paper investigates the properties of a one-dimensional fluid model of plasma convection in the equatorial F region ionosphere. The model equations are similar in form to Burgers equation except for additional higher-order spatial derivatives. Like Burgers equation, solution to the model have the form of propagating, shocklike structures. Numerical simulations of the model closely resemble the steepened structures observed by sounding rocket plasma density probes within equatorial spread F. Simulated denstiy power spectra, like the spectra computed from in situ data, seem to possess power law forms with a break at wavelengths of about 100 m. The precise wavenumber of the spectral break is determined by the ambipolar diffusion coefficient. The model predicts that electric field fluctuations perpendicular to the direction of plasma steepening should be proportional to the plasma density fluctuations. Electric field fluctuations parallel to the steepening will be due primarily to the ambipolar field and have a Boltzmann relationship with density (square of the absolute value of delta E) approximately equal to (K(exp 2))(square of the absolute value of (delta n/n)). At wavelengths less than about 300 m, the ambipolar field should be the dominant component of the total field intensity.
The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.
For semidilute polyelectrolyte solutions, it is generally assumed that topological, electrostatic, and hydrodynamic interactions are screened (called triple screening). Despite a large body of research focused on polyelectrolyte solutions, the concept of triple screening has never been rigorously verified. In this work, we test the concept by probing concentration fluctuations in aqueous solutions containing a well-studied polyelectrolyte, sodium poly(styrenesulfonate) (NaPSS) with neutron scattering, theory, and molecular dynamics simulations. Neutron spin–echo (NSE) and small-angle neutron scattering (SANS) data from semidilute solutions of NaPSS are presented at different polymer and salt (NaCl) concentrations. A combined theory for structure (J. Chem. Phys. 105, 5183 (1996)) and dynamics (J. Chem. Phys. 107, 2619 (1997)), which captures effects of hydrodynamic, topological, and electrostatic screening, is used to interpret the experimental results. Here, the theory quantitatively predicts the decay rate obtained from the NSE measurements while capturing the shape and concentration dependencies of the polyelectrolyte peak observed in the SANS spectra. Detailed comparisons of the theory and the experiments reveal that the wavevector-dependent decay rate of concentration fluctuations in semidilute solutions of polyelectrolytes is dictated by the screening of hydrodynamic, topological, and electrostatic interactions. This conclusion is corroborated by coarse-grained molecular dynamics simulations, executed without any hydrodynamic interactions, which fail to capture the correct wavevector dependence of the decay rate. These results highlight that the theories based on the concept of triple screening provide a quantitative framework for predicting a relation between the structure and dynamics of polyelectrolyte solutions.
Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.
The nonequilibrium viscous shock-layer (VSL) solution scheme is revisited to improve its solution accuracy in the stagnation point region and also to minimize and control the errors in the conservation of elemental mass. The stagnation-point solution is improved by using a second-order expansion for the normal velocity and the elemental mass conservation is improved by directly imposing the element conservation equations as solution constraints. These modifications are such that the general structure and computational efficiency of the nonequilibrium VSL scheme is not affected. This revised nonequilibrium VSL scheme is used to study the Mach 20 flow over a 7-deg sphere-cone vehicle under zero and 20-deg angle-of-attack conditons. Comparisons are made with the corresponding predictions of Navier-Stokes and Parabolized Navier-Stokes solution schemes. The results of these tests show that the nonequilibrium blunt-body VSL scheme is indeed an accurate, fast and extremely efficient means for generating the blunt-body flowfield over spherical nosetips at small-to-large angles of attack.
The nonequilibrium viscous shock-layer (VSL) solution scheme is revisited to improve its solution accuracy in the stagnation region and also to minimize and control errors in the conservation of elemental mass. The stagnation-point solution is improved by using a second-order expansion for the normal velocity, and the elemental mass conservation is improved by directly imposing the element conservation equations as solution constraints. These modifications are such that the general structure and computational efficiency of the nonequilibrium VSL scheme is not affected. This revised nonequilibrium VSL scheme is used to study the Mach 20 flow over a 7-deg sphere-cone vehicle under 0- and 20-deg angle-of-attack conditions. Comparisons are made with the corresponding predictions of Navier-Stokes and parabolized Navier-Stokes solution schemes. The results of these tests show that the nonequilibrium blunt-body VSL scheme is indeed an accurate, fast, and extremely efficient means for generating the blunt-body flowfield over spherical nose tips at zero-to-large angles of attack.
A Cartesian, cell-based scheme for solving the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, polygonal 'cut' cells are created. The geometry of the cut cells is computed using polygon-clipping algorithms. The grid is stored in a binary-tree data structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded, with a limited linear reconstruction of the primitive variables used to provide input states to an approximate Riemann solver for computing the fluxes between neighboring cells. A multi-stage time-stepping scheme is used to reach a steady-state solution. Validation of the Euler solver with benchmark numerical and exact solutions is presented. An assessment of the accuracy of the approach is made by uniform and adaptive grid refinements for a steady, transonic, exact solution to the Euler equations. The error of the approach is directly compared to a structured solver formulation. A non smooth flow is also assessed for grid convergence, comparing uniform and adaptively refined results. Several formulations of the viscous terms are assessed analytically, both for accuracy and positivity. The two best formulations are used to compute adaptively refined solutions of the Navier-Stokes equations. These solutions are compared to each other, to experimental results and/or theory for a series of low and moderate Reynolds numbers flow fields. The most suitable viscous discretization is demonstrated for geometrically-complicated internal flows. For flows at high Reynolds numbers, both an altered grid-generation procedure and a different formulation of the viscous terms are shown to be necessary. A hybrid Cartesian/body-fitted grid generation approach is demonstrated. In addition, a grid-generation procedure based on body-aligned cell cutting coupled with a viscous stensil-construction procedure based on quadratic programming is presented.
Structural fault detection and identification remains an area of active research. Solutions to fault detection and identification may be based on subtle changes in the time series history of vibration signals originating from various sensor locations throughout the structure. The purpose of this paper is to document the application of vibration based fault detection methods applied to several structures. Overall, this paper demonstrates the utility of vibration based methods for fault detection in a controlled laboratory setting and limitations of applying the same methods to a similar structure during flight on an experimental subscale aircraft.
The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.
The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.
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