More Efficient Structural Design by Optimality Criteria
Computer algorithm aids in selection of active constraints on structural design via optimality-criterion method-- highly useful way of ensuring lightweight, low-cost structures.
Levy, R.↗
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Results for “Structural Optimization”
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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Multinuclear Solid-State NMR and NMR Crystallography of Solid Forms of Creatine and Creatinine
Creatine is a performance-enhancing supplement with two widely available commercial solid forms, namely, creatine monohydrate (creatine·H 2 O) and creatine HCl, the latter of which does not have a reported crystal structure. Moreover, commercial formulations of creatine may contain creatinine, an undesired impurity phase resulting from the self-cyclization of creatine during manufacturing. Therefore, reliable methods for characterizing the different solid forms of creatine and detecting the presence of creatinine are essential. Herein, we address these challenges using 13 C, 15 N, and 35 Cl solid-state NMR (SSNMR) spectroscopy to obtain distinct spectral fingerprints for creatine·H 2 O and creatine HCl, along with creatinine and creatinine HCl. The acquisition of these SSNMR spectra offers a robust approach for both the rapid characterization of each solid form and the detection of the impurity phases. Additionally, quadrupolar NMR crystallography-guided crystal structure prediction (QNMRX-CSP) was applied for the de novo crystal structure determination of creatine HCl, which was validated by the subsequently determined single-crystal X-ray diffraction (SCXRD) structure. Finally, to investigate the relationship between NMR parameters and structural features, 13 C and 15 N chemical shifts and 35 Cl electric field gradient (EFG) tensors were computed from geometry-optimized structures of the four solid forms by using dispersion-corrected DFT-D2* methods. Finally, this integrative approach offers a powerful framework for advancing the structural understanding and quality control of creatine-based supplements and next-generation formulations, as well as a wide range of other solid pharmaceuticals and nutraceuticals.
NMR↗
A critical comparison of CH∙∙∙π versus π∙∙∙π interactions in the benzene dimer: obtaining benchmarks at the CCSD(T) level and assessing the accuracy of lower scaling methods
In this study, we have established CCSD(T)/CBS (Complete Basis Set) limits for 3 stationary points on the benzene dimer potential energy surface, corresponding to the π∙∙∙π (parallel displaced or PD(C 2h ), minimum) and CH∙∙∙π (T-shaped or T(C 2v ), transition state) and tilted T-shaped (or TT(Cs), minimum) bonding scenarios considering both the structure and binding energy. The CCSD(T)/CBS binding energies are -2.65 ± 0.02 (PD), -2.74 ± 0.03 (T), and -2.83 ± 0.01 kcal mol -1 (TT). To this end, the CH∙∙∙π is ~0.2 kcal mol -1 stronger than the π∙∙∙π interaction, whereas the tilting of the CH donating benzene molecule with respect to the other benzene is worth 0.1 kcal mol -1 . As previously discussed in the literature, the MP2 level of theory does not provide a close match for either the energy or structure, yet the SCS-MP2 yields structures in excellent agreement with respect to the CCSD(T) result. It is found that the SCS-MI-MP2 also gives optimized structures very close to SCS-MP2 (within ~0.01 Å of the benchmark). Despite the closer match in structure, the spin-biased MP2 methods (SCS-, SCS-MI-, and SOS-MP2) incorrectly predict the relative stabilities of the isomers. That said, none of the spin biased MP2 methods offers a good compromise between energy and structure for the systems examined. Finally, the CCSD(T)/CBS benchmarks were used to assess the performance of 13 DFT functionals selected from different rungs of Jacob's ladder. Several functionals such as TPSS-D3, B3LYP-D3, B97-D, B97-D3, and B2PLYP-D3 provided a good description of the binding energies for both CH∙∙∙π and π∙∙∙π interactions, yielding values within 6% of the CCSD(T)/CBS benchmark values. Unlike the MP2 methods, these functionals correctly predict the relative stability of the PD(C 2h ) and T(C 2v ) dimers. Further, we find that there is no systematic improvement as Jacob's ladder is ascended (increased complexity of functional). The best functionals that result in a good compromise between structure and energy accuracy are B97-D3 and B2PLYP-D3 for both the CH∙∙∙π and π∙∙∙π interaction. Despite the impressive performance of these functionals, a challenge that remains is ensuring the transferability of these density functionals in accurately describing the interaction between dimers of larger aromatic molecules, the latter requiring high-level benchmarks for these systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Active sampling for neural network potentials: Accelerated simulations of shear-induced deformation in Cu–Ni multilayers
Neural network potentials (NNPs) can greatly accelerate atomistic simulations relative to ab initio methods, allowing one to sample a broader range of structural outcomes and transformation pathways. In this work, we demonstrate an active sampling algorithm that trains an NNP that is able to produce microstructural evolutions with accuracy comparable to those obtained by density functional theory, exemplified during structure optimizations for a model Cu–Ni multilayer system. We then use the NNP, in conjunction with a perturbation scheme, to stochastically sample structural and energetic changes caused by shear-induced deformation, demonstrating the range of possible intermixing and vacancy migration pathways that can be obtained as a result of the speedups provided by the NNP. The code to implement our active learning strategy and NNP-driven stochastic shear simulations is openly available at https://github.com/pnnl/Active-Sampling-for-Atomistic-Potentials .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Extension of HCDstruct for Transonic Aeroservoelastic Analysis of Unconventional Aircraft Concepts
A substantial effort has been made to implement an enhanced aerodynamic modeling capability in the Higher-fidelity Conceptual Design and structural optimization tool. This additional capability is needed for a rapid, physics-based method of modeling advanced aircraft concepts at risk of structural failure due to dynamic aeroelastic instabilities. To adequately predict these instabilities, in particular for transonic applications, a generalized aerodynamic matching algorithm was implemented to correct the doublet-lattice model available in Nastran using solution data from a priori computational fluid dynamics anal- ysis. This new capability is demonstrated for two tube-and-wing aircraft configurations, including a Boeing 737-200 for implementation validation and the NASA D8 as a first use case. Results validate the current implementation of the aerodynamic matching utility and demonstrate the importance of using such a method for aircraft configurations featuring fuselage-wing aerodynamic interaction.
Quinlan, Jesse R.↗
Binding of carboxylate and water to monovalent cations
The interactions of carboxylate anions with water and cations are important for a wide variety of systems, both biological and synthetic. Here, in order to gain insight on properties of the local complexes, we apply density functional theory, to treat the complex electrostatic interactions, and investigate mixtures with varied numbers of carboxylate anions (acetate) and waters binding to monovalent cations, Li + , Na + and K + . The optimal structure with overall lowest free energy contains two acetates and two waters such that the cation is four-fold coordinated, similar to structures found earlier for pure water or pure carboxylate ligands. More generally, the complexes with two acetates have the lowest free energy. In transitioning from the overall optimal state, exchanging an acetate for water has a lower free energy barrier than exchanging water for an acetate. In most cases, the carboxylates are monodentate and in the first solvation shell. As water is added to the system, hydrogen bonding between waters and carboxylate O atoms further stabilizes monodentate structures. These structures, which have strong electrostatic interactions that involve hydrogen bonds of varying strength, are significantly polarized, with ChelpG partial charges that vary substantially as the bonding geometry varies. Overall, these results emphasize the increasing importance of water as a component of binding sites as the number of ligands increases, thus affecting the preferential solvation of specific metal ions and clarifying Hofmeister effects. Finally, structural analysis correlated with free energy analysis supports the idea that binding to more than the preferred number of carboxylates under architectural constraints are a key to ion transport.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Hypersonic wing test structure design, analysis, and fabrication
An investigation was conducted to provide the analyses, data, and hardware required to experimentally validate the beaded panel concept and demonstrate its usefulness as a basis for design of a hypersonic research airplane (HRA). Combinations of beaded panel structure, heat shields, channel caps, and corrugated webs for ribs and spars were analyzed for the wing of a specified HRA to operate at Mach 8 with a life span of 150 flights. Detailed analyses, conducted in accordance with established design criteria, included aerodynamic heating and load predictions, transient structural thermal calculations, extensive NASTRAN computer modeling, and structural optimization. After geometry was established for the total wing, part of the wing (85 sq ft) was designed, fabricated, and assembled into a test structure to experimentally verify the structural adequacy of the beaded panel design concept.
Plank, P. P.↗
Optimization applications in aircraft engine design and test
Starting with the NASA-sponsored STAEBL program, optimization methods based primarily upon the versatile program COPES/CONMIN were introduced over the past few years to a broad spectrum of engineering problems in structural optimization, engine design, engine test, and more recently, manufacturing processes. By automating design and testing processes, many repetitive and costly trade-off studies have been replaced by optimization procedures. Rather than taking engineers and designers out of the loop, optimization has, in fact, put them more in control by providing sophisticated search techniques. The ultimate decision whether to accept or reject an optimal feasible design still rests with the analyst. Feedback obtained from this decision process has been invaluable since it can be incorporated into the optimization procedure to make it more intelligent. On several occasions, optimization procedures have produced novel designs, such as the nonsymmetric placement of rotor case stiffener rings, not anticipated by engineering designers. In another case, a particularly difficult resonance contraint could not be satisfied using hand iterations for a compressor blade, when the STAEBL program was applied to the problem, a feasible solution was obtained in just two iterations.
Pratt, T. K.↗
Statistical Analysis of CMC Constituent and Processing Data
Ceramic Matrix Composites (CMCs) are the next "big thing" in high-temperature structural materials. In the case of jet engines, it is widely believed that the metallic superalloys currently being utilized for hot structures (combustors, shrouds, turbine vanes and blades) are nearing their potential limits of improvement. In order to allow for increased turbine temperatures to increase engine efficiency, material scientists have begun looking toward advanced CMCs and SiC/SiC composites in particular. Ceramic composites provide greater strength-to-weight ratios at higher temperatures than metallic alloys, but at the same time require greater challenges in micro-structural optimization that in turn increases the cost of the material as well as increases the risk of variability in the material s thermo-structural behavior. to model various potential CMC engine materials and examines the current variability in these properties due to variability in component processing conditions and constituent materials; then, to see how processing and constituent variations effect key strength, stiffness, and thermal properties of the finished components. Basically, this means trying to model variations in the component s behavior by knowing what went into creating it. inter-phase and manufactured by chemical vapor infiltration (CVI) and melt infiltration (MI) were considered. Examinations of: (1) the percent constituents by volume, (2) the inter-phase thickness, (3) variations in the total porosity, and (4) variations in the chemical composition of the Sic fiber are carried out and modeled using various codes used here at NASA-Glenn (PCGina, NASALife, CEMCAN, etc...). The effects of these variations and the ranking of their respective influences on the various thermo-mechanical material properties are studied and compared to available test data. The properties of the materials as well as minor changes to geometry are then made to the computer model and the detrimental effects observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)
Fornuff, Jonathan↗
Optimization of energy group structures in PARTISN with Particle Swarm Optimization [Slides]
Abstract not provided.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Stabilization of Dinuclear Rhodium and Iridium Clusters on Layered Titanate and Niobate Supports
Atomically dispersed organometallic clusters can provide well-defined nuclearity of active sites for both fundamental studies as well as new regimes of activity and selectivity in chemical transformations. More recently, dinuclear clusters adsorbed onto solid surfaces have shown novel catalytic properties resulting from the synergistic effect of two metal centers to anchor different reactant species. Difficulty in synthesizing, stabilizing, and characterizing isolated atoms and clusters without agglomeration challenges allocating catalytic performance to atomic structure. Here, we explore the stability of dinuclear rhodium and iridium clusters adsorbed onto layered titanate and niobate supports using molecular precursors. Both systems maintain their nuclearity when Statistical analysis of HAADF-STEM images revealed that rhodium and iridium dimers had mean cluster-to-cluster distances very similar to what is expected from a random distribution of atoms over a large area, indicating that they are dispersed without aggregation. The stability of dinuclear rhodium clusters supported on titanate nanosheets was also investigated by X-ray absorption fine structure (EXAFS), DRIFTS, and first-principles calculations. Both X-ray absorption spectroscopy and HAADF-STEM simulations, guided by density functional theory (DFT)-optimized structure models, suggested that rhodium dimers adsorb onto the nanosheets in an end-on binding mode that is stable up to 100 degrees C under reducing conditions. Finally, this study highlights that crystalline nanosheets derived from layered metal oxides can be used as model supports to selectively stabilize dinuclear clusters, which could have implications for heterogeneous catalysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
An efficient approach to explore the solution space of a wind turbine rotor design process
This study proposes a novel approach to explore the solution space of a wind turbine rotor design process. The goal is to offer to blade designers the possibility to select an optimal rotor for given market conditions, assessing trade-offs and alternatives in a matter of minutes. The design process consists of sequential aerodynamic-structural optimizations, where the two loops are linked via a blade-loading parameter that can be varied by the user. A design study is performed starting from the IEA Wind Task 37 land-based reference wind turbine. The solution space is characterized for rotor diameters in the range of 130–160 m, rated generator power values in the range of 3.0–6.0 MW, and tip-speed ratios in the range of 7.5–12.5. Results are discussed highlighting optimal design decisions and trade-offs.
17 WIND ENERGY↗
The NASA/Industry Design Analysis Methods for Vibrations (DAMVIBS) Program - A government overview
An overview is presented of government contributions to the program called Design Analysis Methods for Vibrations (DAMV) which attempted to develop finite-element-based analyses of rotorcraft vibrations. NASA initiated the program with a finite-element modeling program for the CH-47D tandem-rotor helicopter. The DAMV program emphasized four areas including: airframe finite-element modeling, difficult components studies, coupled rotor-airframe vibrations, and airframe structural optimization. Key accomplishments of the program include industrywide standards for modeling metal and composite airframes, improved industrial designs for vibrations, and the identification of critical structural contributors to airframe vibratory responses. The program also demonstrated the value of incorporating secondary modeling details to improving correlation, and the findings provide the basis for an improved finite-element-based dynamics design-analysis capability.
Kvaternik, Raymond G.↗
Multiphysics Modeling of a Single Channel in a Nuclear Thermal Propulsion Grooved Ring Fuel Element
In the past, fuel rods have been used in nuclear propulsion applications. A new fuel element concept that reduces weight and increases efficiency uses a stack of grooved discs. Each fuel element is a flat disc with a hole on the interior and grooves across the top. Many grooved ring fuel elements for use in nuclear thermal propulsion systems have been modeled, and a single flow channel for each design has been analyzed. For increased efficiency, a fuel element with a higher surface-area-to-volume ratio is ideal. When grooves are shallower, i.e., they have a lower surface area, the results show that the exit temperature is higher. By coupling the physics of turbulence with those of heat transfer, the effects on the cooler gas flowing through the grooves of the thermally excited solid can be predicted. Parametric studies were done to show how a pressure drop across the axial length of the channels will affect the exit temperatures of the gas. Geometric optimization was done to show the behaviors that result from the manipulation of various parameters. Temperature profiles of the solid and gas showed that more structural optimization is needed to produce the desired results. Keywords: Nuclear Thermal Propulsion, Fuel Element, Heat Transfer, Computational Fluid Dynamics, Coupled Physics Computations, Finite Element Analysis
Kim, Tony↗
Multiobjective and categorical global optimization of photonic structures based on ResNet generative neural networks
Abstract We show that deep generative neural networks, based on global optimization networks (GLOnets), can be configured to perform the multiobjective and categorical global optimization of photonic devices. A residual network scheme enables GLOnets to evolve from a deep architecture, which is required to properly search the full design space early in the optimization process, to a shallow network that generates a narrow distribution of globally optimal devices. As a proof-of-concept demonstration, we adapt our method to design thin-film stacks consisting of multiple material types. Benchmarks with known globally optimized antireflection structures indicate that GLOnets can find the global optimum with orders of magnitude faster speeds compared to conventional algorithms. We also demonstrate the utility of our method in complex design tasks with its application to incandescent light filters. These results indicate that advanced concepts in deep learning can push the capabilities of inverse design algorithms for photonics.
Jiang, Jiaqi↗
Hydrokinetic Energy Conversion by Flow-Induced Oscillation of Two Tandem Cylinders of Different Stiffness
Abstract The vortex-induced vibration for aquatic clean energy (VIVACE) converter harnesses hydrokinetic energy by enhancing flow-induced oscillations (FIOs) of elastically supported rigid cylinders in a river, tide, or ocean current. The harnessing power depends on the intensity of the oscillation, which is a consequence of the flow–structure interaction. The inflow condition for the downstream (second) cylinder is slowed down and perturbed by the upstream (first) cylinder, due to the shielding effect. Therefore, the optimal structural parameters, i.e., stiffness and damping ratio, for the second cylinder may be different from the first cylinder, in terms of energy harnessing. To improve the performance of the VIVACE converter, a series of experiments are conducted in a recirculating water channel, with various stiffness combinations of two cylinders in tandem. Results show that the stiffness of the second cylinder, K2, does not affect the energy harnessing power in vortex-induced vibration (VIV) occurring at low speeds, because the oscillation of the downstream cylinder in this velocity range is completely dominated by the wake of the upstream cylinder. K2 has a great influence on the harnessing power at higher velocities in the transition region from VIV to galloping and in galloping. Changing K2 onsets and enhances galloping at lower flow velocity and harnesses up to 110% more energy than the case of K1 = K2.
Engineering↗
Sensitivity of optimum solutions to problem parameters
In an aircraft configuration optimization, the information of interest is the sensitivity of optimal block fuel consumption and wing aspect ratio and area, to variations of required range and payload. The objectives of this study are: (1) to show how the equations capable of yielding the sensitivity derivatives (the sensitivity equations) can be obtained for a constrained optimum regardless of the type of optimization algorithm that was used to arrive at the optimum point, (2) to review the solvability of the sensitivity equations and (3) to report on applications on structural optimization. Numerical examples, which demonstrate the sensitivity analysis, include a tubular column and a three-bar truss for which closed form solutions are obtained, a ten-bar truss that requires the use of a finite element analysis, and a thin-walled beam characterized by strongly nonlinear constraints for local buckling. It is concluded that a practically significant extrapolation accuracy may be obtained for a reasonably broad range of parameter changes; and that accuracy does not depend strongly on the degree of convergence of the optimum solution from which the sensitivity derivatives are obtained.
Sobieszczanski-Sobieski, J.↗
The multi-disciplinary design study. A life cycle cost algorithm
Life-cycle cost (LCC) is investigated as a comprehensive design criterion for two major interrelated spacecraft subsystems, Controls and Structures. A Multi-Disciplinary Design Tool (MDDT) is developed to evaluate the sensitivity of LCC to subsystem design parameters. Major costs addressed are: non-recurring; launch; ground support; maintenance; expendables; and software. Examples and results from the MDDT are described, including a structural optimization study between different truss designs; a solar array feathering trade for a minimal drag configuration during umbra; and the cost of active control of a flexible structure is compared against the cost of passive damping using visco-elastic material.
Harding, R. R.↗