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Prediction of forces and heat loads induced by rocket jet plume impingement on Saturn V launch vehicle and launch complex structures
Two novel quaternary oxyarsenides, Eu 8 Zn 2 As 6 O and Eu 14 Zn 5 As 12 O, were synthesized through metal flux reactions, and their crystal structures were established by single-crystal X-ray diffraction methods. Eu 8 Zn 2 As 6 O crystallizes in the orthorhombic space group Pbca, featuring polyanionic ribbons composed of corner-shared triangular [ZnAs 3 ] units, running along the [100] direction. The structure of Eu 14 Zn 5 As 12 O crystallizes in the monoclinic space group P2/m and its anionic substructure can be described as an infinite “ribbonlike” chain comprised of [ZnAs 3 ] trigonal-planar units, although the structural complexity here is greater and also amplified by disorder on multiple crystallographic positions. In both structures, the O 2– anion occupies an octahedral void with six neighboring Eu 2+ cations. Formal electron counting, electronic structure calculations, and transport properties reveal the charge-balanced semiconducting nature of these heteroanionic Zintl phases. High-temperature thermoelectric transport properties measurements on Eu 14 Zn 5 As 12 O reveal relatively high resistivity (ρ 500K = 8 Ω·cm) and Seebeck coefficient values (S 500K = 220 μV K –1 ), along with a low concentration and mobility of holes as the dominant charge-carriers (n 500K = 8.0 × 10 17 cm –3 , μ 500K = 6.4 cm 2 /V s). Magnetic studies indicate the presence of divalent Eu 2+ species in Eu 14 Zn 5 As 12 O and complex magnetic ordering, with two transitions observed at T 1 = 21.6 K and T 2 = 9 K.
The crystal structure and magnetic properties of Cu 0.6 Mn 2.4 Ge 2 have been re-investigated by a combination of extensive magnetic measurements and neutron scattering experiments, aided by electronic structure calculations. The material is found to be a soft ferromagnet with the ordering temperature T C = 316 K. The magnetocaloric effect evaluated from field-dependent magnetization isotherms is equal to 1.2 J/(kg·K) and 2.5 J/(kg·K) under the maximum applied magnetic field of 2 T and 5 T, respectively. The compound crystallizes in the hexagonal space group P6 3 /mmc. A complex structural disorder necessitated testing of several disorder models against the results of non-polarized and polarized neutron scattering experiments and magnetization measurements. Simulations at the density-functional theory level were also performed to identify the most robust solution that properly described the data observed. The final magnetic structure model reveals non-equal magnetic moments on the Mn1 and Mn2 atoms (2.29(9) µ B and 2.7(1) µ B , respectively) and the presence of vacancies and minor Cu substitution defects in both Mn sites. The work demonstrates how the non-polarized and polarized neutron scattering methods can be combined with electronic structure calculations to establish the microscopic structure of magnetic materials with complex crystallographic disorder.
The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.
Sinnerite Cu 6 As 4 S 9 has been identified as a promising material for optoelectronic applications, with potential for other energy-related applications; however, knowledge of the electrical and thermal properties as well as the mechanisms underlying transport in sinnerite is lacking. Here, we present an investigation of the synthesis, structural, thermal and electrical transport properties of stoichiometric and Sn-doped Cu 6 As 4 S 9 . Sinnerite has a triclinic lattice structure, with highly distorted local atomic coordination environments that, in part, results in its complex structure and bonding. Our results and analyses indicate As 4s 2 lone pair-induced distortions and strong lattice anharmonicity that leads to a relatively short phonon mean free path, resulting in intrinsically very low thermal conductivity. The electrical resistivity for both compositions, Cu 6 As 4-x Sn x S 9 (x = 0, 0.2), are relatively high and varies little with temperature, typical of degenerate semiconductors. An increase in mobility and electrical conductivity was obtained by Sn doping in Cu 6 As 3.8 Sn 0.2 S 9 . This work demonstrates an effective route to synthesize bulk sinnerite as well as advances the knowledge of the properties of sinnerite, as this and other ternary chalcogenides continue to be of interest for potential technologically significant applications.
Most metals adopt simple structures such as body-centered cubic (BCC), face-centered cubic (FCC), and hexagonal close-packed (HCP) structures in specific groupings across the periodic table, and many undergo transitions to surprisingly complex structures on compression, not expected from conventional free-electron-based theories of metals. First-principles calculations have been able to reproduce many observed structures and transitions, but a unified, predictive theory that underlies this behavior is not yet in hand. Discovered by analyzing the electronic properties of metals in various lattices over a broad range of sizes and geometries, a remarkably simple theory shows that the stability of metal structures is governed by electrons occupying local interstitial orbitals and their strong chemical interactions. The theory provides a basis for understanding and predicting structures in solid compounds and alloys over a broad range of conditions.
A study was conducted to investigate and prove the correlation between the NASTRAN predicted stresses and those measured on an actual structure. NASTRAN is a general purpose digital computer program for the analysis of large complex structures. A real airframe, which had logged several thousand hours flying time, was obtained, instrumented, and loaded to obtain the measured strains.
The results of numerical experiments designed to illustrate how the minimum weight design, accuracy, and cost can be influenced by: (1) refinement of the finite element analysis model and associated load path problems, and (2) refinement of the design variable linking model are examined. The numerical experiments range from simple structures where the modelling decisions are relatively obvious and less costly to the more complex structures where such decisions are less obvious and more costly. All numerical experiments used employ the dual formulation in ACCESS-3 computer program. Guidelines are suggested for creating analysis and design models that predict a minimum weight structure with greater accuracy and less cost. These guidelines can be useful in an interactive optimization environment and in the design of heuristic rules for the development of knowledge-based expert optimization systems.
An investigation of the microstructure of a Pacific stratocumulus capped boundary layer is presented. A complex structure of three branches, identified using conserved variable diagrams, is found to correspond well to a conceptual model for the unstable, radiatively cooled cloud topped boundary layer. A simple conditional sampling method was used to identify saturation point pairs for ascending and descending branches of the internal boundary layer circulation. Results indicate a primary circulation scale of 5 km and provide a reasonable cloud top entrainment rate of 1 cm/s.
This report covers the period of the grant from January 1991 until its expiration in June 1992. Together with an Interim Report (Ref. 9), it summarizes the research conducted under NASA Grant NAG9-357 on the topic 'Application of Lanczos Vectors to Control Design of Flexible Structures.' The research concerns various ways to obtain reduced-order mathematical models of complex structures for use in dynamics analysis and in the design of control systems for these structures. This report summarizes the research.
Since 1986, remote sensing images derived from satellite and aircraft-borne sensor data have been used to study the stratigraphy and sedimentology of the vertebrate-bearing Wind River and Wagon Bed formations in the Wind River Basin (Wyoming). Landsat 5 TM and aircraft Thermal Infrared Multispectral Scanner data were combined with conventional geologic analyses. The remote sensing data have contributed significantly to: (1) geologic mapping at the formation, member, and bed levels; (2) stratigraphic correlation; (3) reconstruction of ancient depositional environments; and (4) identification of structural complexity. This information is critical to vertebrate paleontology in providing the stratigraphic, sedimentologic, and structural framework required for evolutionary and paleoecologic studies. Of primary importance is the ability to map at minimal cost the geology of large areas (20,000 sq km or greater) at a high level of precision. Remote sensing data can be especially useful in geologically and paleontologically unexplored or poorly understood regions.
Composite Overwrapped Pressure Vessels (COPVs) are commonly used in spacecraft for containment of pressurized gases and fluids, incorporating strength and weight savings. The energy stored is capable of extensive spacecraft damage and personal injury in the event of sudden failure. These apparently simple structures, composed of a metallic media impermeable liner and fiber/resin composite overwrap are really complex structures with numerous material and structural phenomena interacting during pressurized use which requires multiple, interrelated monitoring methodologies to monitor and understand subtle changes critical to safe use. Testing of COPVs at NASA Johnson Space Center White Sands T est Facility (WSTF) has employed multiple in-situ, real-time nondestructive evaluation (NDE) methodologies as well as pre- and post-test comparative techniques to monitor changes in material and structural parameters during advanced pressurized testing. The use of NDE methodologies and their relationship to monitoring changes is discussed based on testing of real-world spacecraft COPVs. Lessons learned are used to present recommendations for use in testing, as well as a discussion of potential applications to vessel health monitoring in future applications.
Modern finite element methods (FEM's) enable the precise modeling of mass and stiffness properties in what were in the past overwhelmingly large and complex structures. These models allow the accurate determination of natural frequencies and mode shapes. However, adequate methods for modeling highly damped and high frequency dependent structures did not exist until recently. The most commonly used method, Modal Strain Energy, does not correctly predict complex mode shapes since it is based on the assumption that the mode shapes of a structure are real. Recently, many techniques have been developed which allow the modeling of frequency dependent damping properties of materials in a finite element compatible form. Two of these methods, the Golla-Hughes-McTavish method and the Lesieutre-Mingori method, model the frequency dependent effects by adding coordinates to the existing system thus maintaining the linearity of the model. The third model, proposed by Bagley and Torvik, is based on the Fractional Calculus method and requires fewer empirical parameters to model the frequency dependence at the expense of linearity of the governing equations. This work examines the Modal Strain Energy, Golla-Hughes-McTavish and Bagley and Torvik models and compares them to determine the plausibility of using them for modeling viscoelastic damping in large structures.
Designing crystalline solids in which intrinsic extremely low lattice thermal conductivity mainly arises from its unique bonding nature rather than structure complexity and/or atomic disorder could promote thermal energy manipulation and utilization for applications ranging from thermoelectric energy conversion to thermal barrier coatings. Here, we report an extremely low lattice thermal conductivity of ~0.34 W m-1 K-1 at 300 K in the new complex sulfosalt MnPb16Sb14S38. We attribute the ultra-low lattice thermal conductivity to a synergistic combination of scattering mechanisms involving (1) strong bond anharmonicity in various structural building units, owing to the presence of stereoactive lone-electron-pair (LEP) micelles, and (2) phonon scattering at the interfaces between building units of increasing size and complexity. Remarkably, low-temperature heat capacity measurement revealed a Cp value of 0.206 J g-1 K-1 at T > 300 K, which is 22% lower than the Dulong-Petit value (0.274 J g-1 K-1). Further analysis of the Cp data and sound velocity (ν = 1834 m/s) measurement yielded Debye temperature values of 161 K and 187 K, respectively. Here, the resulting Grüneisen parameter, γ = 1.65, further supports strong bond anharmonicity as the dominant mechanism responsible for the observed extremely low lattice thermal conductivity.
A computational strategy is presented for the nonlinear static and postbuckling analyses of large complex structures on massively parallel computers. The strategy is designed for distributed-memory, message-passing parallel computer systems. The key elements of the proposed strategy are: (1) a multiple-parameter reduced basis technique; (2) a nested dissection (or multilevel substructuring) ordering scheme; (3) parallel assembly of global matrices; and (4) a parallel sparse equation solver. The effectiveness of the strategy is assessed by applying it to thermo-mechanical postbuckling analyses of stiffened composite panels with cutouts, and nonlinear large-deflection analyses of HSCT models on Intel Paragon XP/S computers. The numerical studies presented demonstrate the advantages of nested dissection-based solvers over traditional skyline-based solvers on distributed memory machines.
Abstract Predicting the structure of multi‐protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage predefined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any precomputed physics‐inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end‐to‐end learning from molecular structures containing tens of thousands of atoms: a point‐based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems.
Research on natural laminar flow, laminar flow control by suction, and turbulent drag reduction is discussed. Preliminary results suggest that a significant amount of natural laminar flow can be achieved on small, straight wing airplanes. On larger, swept wing aircraft, laminar flow control by distributed suction is expected to result in significant fuel savings. The area over which laminar flow control is applied depends on tradeoffs involving structural complexity, maintenance, and cost. Several methods of reducing turbulent skin friction by altering the turbulence structure itself have shown promise in exploratory testing. The status of these technologies and the benefits of applying them to future aircraft are reviewed.
Current NASA research points toward exciting opportunities for large reductions in viscous drag. Research is underway on natural laminar flow, laminar flow control by suction, and turbulent drag reduction. Preliminary results suggest that a significant amount of natural laminar flow can be achieved on small, straight-wing airplanes. On larger, swept-wing aircraft, laminar flow control by distributed suction is expected to result in significant fuel savings. The area over which laminar flow control is applied depends on tradeoffs involving structural complexity, maintenance, and cost. Several methods of reducing turbulent skin friction by altering the turbulence structure itself have shown promise in exploratory testing. This paper reviews the status of these technologies and indicates the benefits of applying them to future aircraft.