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At least 55 records · Page 3

Aeroelastic Stability Assessment Methodology and Application to Slat Noise Treatments on the High-Lift Common Research Model

This work supports a larger effort at NASA to reduce airframe noise and, thus, environmental noise around airports. The leading-edge slat of conventional high-lift systems is a prominent source of airframe noise, and two technologies were previously identified as promising for noise reduction without significant aerodynamic or weight penalty: the slat cove filler (SCF) and the slat gap filler (SGF). NASA fabricated a 10%-scale semispan aircraft model for wind tunnel testing based upon the High-Lift Common Research Model (CRM-HL). NASA embarked on a test campaign with the 10% CRM-HL to determine the noise reduction effectiveness and other performance metrics of 3D SCF and SGF treatments in flow conditions representative of flight. The highly flexible SCF and SGF treatments posed a risk to the model and aeroelastic instability would compromise research integrity, so aeroelastic stability assessment was required. This work briefly describes the 10% CRM-HL, design of the SCF and SGF treatments to the model, and supporting fluid structure interaction (FSI) research. Relations for static and dynamic aeroelastic similitude are then developed for convenience of reference, and simplifications are introduced of particular utility to the cases considered in this study. The similitude relations are employed to assess the stability of the treatments under wind tunnel flow conditions based upon known behaviors from the supporting research. It is shown that the treatments are safe for test under the anticipated wind tunnel flow conditions with significant margins/factors of safety. It is furthermore demonstrated that the SCF is more susceptible to aeroelastic instability than the SGF, which has implications for flight feasibility.

Similitude↗

Pseudodiagonalization Method for Accelerating Nonlinear Subspace Diagonalization in Density Functional Theory

In density functional theory, each self-consistent field (SCF) nonlinear step updates the discretized Kohn-Sham orbitals by solving a linear eigenvalue problem. The concept of pseudodiagonalization is to solve this linear eigenvalue problem approximately, and specifically utilizing a method involving a small number of Jacobi rotations that takes advantage of the good initial guess to the solution given by the approximation to the orbitals from the previous SCF iteration. The approximate solution to the linear eigenvalue problem can be very rapid, particularly for those steps near SCF convergence. Here, we adapt pseudodiagonalization to finite-temperature and metallic systems, where partially-occupied orbitals must be individually resolved with some accuracy. We apply pseudodiagonalization to the subspace eigenvalue problem that arises in Chebyshev-filtered subspace iteration. In tests on metallic and other systems for a range of temperatures, we show that pseudodiagonalization achieves similar rates of SCF convergence to exact diagonalization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revisiting Artifacts of Kohn–Sham Density Functionals for Biosimulation

We revisit the problem of unphysical charge density delocalization/fractionalization induced by the self-interaction error of common approximate Kohn–Sham (KS) density functional theory functionals on simulation of small to medium-sized proteins in a vacuum. Aside from producing unphysical electron densities and total energies, the vanishing of the HOMO–LUMO gap associated with the unphysical charge delocalization leads to an unphysical low-energy spectrum and catastrophic failure of most popular solvers for the KS self-consistent field (SCF) problem. We apply a robust quasi-Newton SCF solver to obtain solutions for some of these difficult cases. The anatomy of the charge delocalization is revealed by the natural deformation orbitals obtained from the density matrix difference between the Hartree–Fock and KS solutions; the charge delocalization not only can occur between charged fragments (such as in zwitterionic polypeptides) but also involves neutral fragments. The vanishing-gap phenomenon and troublesome SCF convergence are both attributed to the unphysical KS Fock operator eigenspectra of molecular fragments (e.g., amino acids or their side chains). Analysis of amino acid pairs suggests that the unphysical charge delocalization can be partially ameliorated by the use of some range-separated hybrid functionals but not by semilocal or standard hybrid functionals. Last, we demonstrate that solutions without the unphysical charge delocalization can be located even for semilocal KS functionals highly prone to such defects, but such solutions have non-Aufbau character and are unstable with respect to mixing of the non-overlapping “frontier” orbitals. Caution should be exercised when unexpectedly small (or vanishing) HOMO–LUMO gaps and atypical SCF convergence patterns (e.g., oscillatory) are observed in KS DFT simulations in any context (bio or otherwise).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis for dimerization quality control

Most quality control pathways target misfolded proteins to prevent toxic aggregation and neurodegeneration 1 . Dimerization quality control further improves proteostasis by eliminating complexes of aberrant composition 2 , but how it detects incorrect subunits remains unknown. Here we provide structural insight into target selection by SCF-FBXL17, a dimerization-quality-control E3 ligase that ubiquitylates and helps to degrade inactive heterodimers of BTB proteins while sparing functional homodimers. We find that SCF-FBXL17 disrupts aberrant BTB dimers that fail to stabilize an intermolecular β-sheet around a highly divergent β-strand of the BTB domain. Furthermore, complex dissociation allows SCF-FBXL17 to wrap around a single BTB domain, resulting in robust ubiquitylation. SCF-FBXL17 therefore probes both shape and complementarity of BTB domains, a mechanism that is well suited to establish quality control of complex composition for recurrent interaction modules.

59 BASIC BIOLOGICAL SCIENCES↗

Generating accurate density matrices on the tangent space of a Grassmann manifold

Interpolating a density matrix from a set of known density matrices is not a trivial task. This is because a linear combination of density matrices does not necessarily correspond to another density matrix. In this Communication, density matrices are examined as objects of a Grassmann manifold. Although this manifold is not a vector space, its tangent space is a vector space. As a result, one can map the density matrices on this manifold to their corresponding vectors in the tangent space and then perform interpolations on that tangent space. The resulting interpolated vector can be mapped back to the Grassmann manifold, which can then be utilized (1) as an optimal initial guess for a self-consistent field (SCF) calculation or (2) to derive energy directly without time-consuming SCF iterations. Such a promising approach is denoted as Grassmann interpolation (G-Int). The hydrogen molecule has been used to illustrate that the described interpolated method in this work preserves the essential attributes of a density matrix. For phosphorus mononitride and ferrocene, it was demonstrated numerically that reference points for the definition of the corresponding tangent spaces can be chosen arbitrarily. In addition, the interpolated density matrices provide a superior and essentially converged initial guess for an SCF calculation to make the SCF procedure itself unnecessary. Finally, this accurate, efficient, robust, and systematically improved G-Int strategy has been used for the first time to generate highly accurate potential energy surfaces with fine details for the difficult case, ferrocene.

Chemistry↗

The Grassmann interpolation method for spin-unrestricted open-shell systems

The recently reported Grassmann interpolation (G-Int) method [J. A. Tan and K. U. Lao, J. Chem. Phys. 158, 051101 (2023)] has been extended to spin-unrestricted open-shell systems. In contrast to closed-shell systems, where G-Int has to be performed only once since the α and β density matrices are the same, spin-unrestricted open-shell systems require G-Int to be performed twice—one for the α spin and another for the β spin density matrix. In this work, we tested the performance of G-Int to the carbon monoxide radical cation CO●+ and nickelocene complex, which have the doublet and triple ground states, respectively. We found that the Frobenius norm errors associated with the interpolations for the α and β spin density matrices are comparable for a given molecular geometry. These G-Int density matrices, when used as an initial guess for a self-consistent field (SCF) calculation, outperform the conventional SCF guess schemes, such as the superposition of atomic densities, purified superposition of atomic densities, core Hamiltonian, and generalized Wolfsberg–Helmholtz approximation. Depending on the desired accuracy, these G-Int density matrices can be used to directly evaluate the SCF energy without performing SCF iterations. In addition, the spin-unrestricted G-Int density matrices have been used for the first time to directly calculate the atomic charges using the Mulliken and ChElPG population analysis.

Chemistry↗

Evaluation of digestively resistant or soluble fibers, short- and medium-chain fatty acids, trace minerals, and antibiotics in nonchallenged nursery pigs on performance, digestibility, and intestinal integrity

Abstract Three experiments (EXP) were conducted to determine the effect of feed additives on performance, intestinal integrity, gastrointestinal volatile fatty acids (VFA), and energy and nutrient digestion in nonchallenged nursery pigs. In EXP 1, 480 pigs (6.36-kg body weight, BW) were placed into 96 pens with 5 pigs/pen, and allotted to 1 of 10 dietary treatments: 1) negative control containing no feed additive (NC), 2) NC + 44 mg chlortetracycline and 38.5 mg tiamulin/kg diet (CTsb), 3) NC + 5% resistant potato starch (RSpo), 4) NC + 5% soluble corn fiber (SCF), 5) NC + 5% sugar beet pulp (SBP), 6) NC + 0.30% fatty acid mix (FAM), 7) NC + 0.10% phytogenic blend of essential oils and flavoring compounds (PHY), 8) NC + 50 mg Cu and 1,600 mg zinc oxide/kg diet (CuZn), 9) NC + 5% resistant corn starch (RScn), and 10) NC + 0.05% β-glucan (BG) for 28 d. There was no impact of dietary treatment on BW gain or feed intake (P ≥ 0.22). Pigs fed diets containing SCF, CTsb, and RSpo resulted in microbial community differences compared to pigs fed the NC (P < 0.05). In EXP 2, 48 barrows (12.8 kg BW) were selected at the end of EXP 1 and fed the same dietary treatments they had previously received: 1) NC, 2) NC + 5% RScn, 3) NC + 5% SCF, and 4) NC + FAM for 8 d. There was no effect of feeding diets containing RScn, SCF, or FAM on in vivo intestinal permeability (P ≤ 0.21). Ileal or colon pH, concentrations of VFA did not differ due to dietary treatment (P ≥ 0.36), but pigs fed diets containing FAM resulted in a greater butyric acid concentration in the cecum compared to pigs fed the NC (P ≤ 0.05). In EXP 3, 156 pigs (6.11 kg BW) were placed into 52 pens with 3 pigs/pen and allotted to 1 of 4 dietary treatments arranged in a factorial manner: 1) NC, 2) NC + 5% RSpo, 3) NC + 0.30% FAM, and 4) NC + 5% RSpo + 0.30% FAM for 24 d. Feeding pigs diets containing RSpo did not affect BW gain (P = 0.91) while pigs fed diets containing FAM grew improved BW gain (P = 0.09). Colonic butyric acid concentrations were greater in pigs fed diets containing RSpo (P = 0.03), while pigs fed diets containing FAM exhibited reduced total VFA concentrations (P = 0.11). The results indicate that supplementing diets with digestively resistant but fermentable fibers, short- and medium-chain fatty acids, or antibiotics do not have a consistent effect, positive or negative, on markers of intestinal integrity or barrier function, intestinal VFA patterns, ATTD of energy and nutrients, or on pig performance.

Agriculture↗

Frank–Kasper Phases of Diblock Copolymer Melts: Self-Consistent Field Results of Two Commonly Used Models

We constructed phase diagrams of conformationally asymmetric diblock copolymer A-B melts using the polymer self-consistent field (SCF) calculations of both the dissipative particle dynamics chain (DPDC) model (i.e., compressible melts of discrete Gaussian chains with the DPD non-bonded potential) and the “standard” model (i.e., incompressible melts of continuous Gaussian chains with the Dirac δ-function non-bonded potential) in the χN-ε plane, where χN and ε characterize, respectively, the repulsion and conformational asymmetry between the A and B blocks, at the A-block volume fraction f = 0.2 and 0.3. Consistent with previous SCF calculations of the “standard” model, σ and A15 are the only stable Frank–Kasper (FK) phases among the five FK (i.e., σ, A15, C14, C15 and Z) phases considered. The stability of σ and A15 is due to their delicate balance between the energetic and entropic contributions to the Helmholtz free energy per chain of the system, which, within our parameter range, increases in the order of σ/A15, Z, and C14/C15. While in general the SCF phase diagrams of these two models are qualitatively consistent, A15 is not stable for the DPDC model at the copolymer chain length N = 10 and f = 0.3; any differences in the SCF phase diagrams are solely due to the differences between these two models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance characteristics of two multiaxis thrust-vectoring nozzles at Mach numbers up to 1.28

The thrust-vectoring axisymmetric (VA) nozzle and a spherical convergent flap (SCF) thrust-vectoring nozzle were tested along with a baseline nonvectoring axisymmetric (NVA) nozzle in the Langley 16-Foot Transonic Tunnel at Mach numbers from 0 to 1.28 and nozzle pressure ratios from 1 to 8. Test parameters included geometric yaw vector angle and unvectored divergent flap length. No pitch vectoring was studied. Nozzle drag, thrust minus drag, yaw thrust vector angle, discharge coefficient, and static thrust performance were measured and analyzed, as well as external static pressure distributions. The NVA nozzle and the VA nozzle displayed higher static thrust performance than the SCF nozzle throughout the nozzle pressure ratio (NPR) range tested. The NVA nozzle had higher overall thrust minus drag than the other nozzles throughout the NPR and Mach number ranges tested. The SCF nozzle had the lowest jet-on nozzle drag of the three nozzles throughout the test conditions. The SCF nozzle provided yaw thrust angles that were equal to the geometric angle and constant with NPR. The VA nozzle achieved yaw thrust vector angles that were significantly higher than the geometric angle but not constant with NPR. Nozzle drag generally increased with increases in thrust vectoring for all the nozzles tested.

Wing, David J.↗

Probabilistic Simulation of Stress Concentration in Composite Laminates

A computational methodology is described to probabilistically simulate the stress concentration factors (SCF's) in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties, whereas the finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate SCF's, such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using is to simulate the SCF's in three different composite laminates. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the SCF's are influenced by local stiffness variables, by load eccentricities, and by initial stress fields.

Chamis, C. C.↗

A comparison of two algorithms for simulating collisionless systems

Two completely different simulation algorithms are compared by applying them to the same stellar dynamical problems: one is a self-consistent field (SCF) method for solving Poisson's equation and the other is a phase-space method for integrating the collisionless Boltzmann equation. We consider simulations of spherical stellar systems which are initially far from equilibrium and relax to their final states by gravitational collapse. The initial conditions consist of either uniform-density spheres or nonequilibrium models having Plummer density profiles, in which velocity dispersions are assigned according to given virial ratios. If a few tens of radial expansion terms with hundreds of thousands of particles are used in the SCF code, excellent agreement is found between the results it generates and those obtained with the phase-space solver, provided that a sufficiently large number of grid cells are employed with the latter. These findings imply that for simulating collisionless systmes over many dynamical times, the SCF approach based on sampling phase space is competitive with the approach treating phase space as a continuous fluid. The results of our tests make it possible to estimate the number of particles and basis functions required in situations like those modeled. Limitations of the SCF method and the choice of an optimal set of basis functions are also discussed.

Hozumi, Shunsuke↗

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗

Impact of Random Micron-Sized Surface Roughness on Stationary Crossflow Instabilities

This study examines the effect of random micron-sized distributed roughness on stationary crossflow (SCF) instabilities. The roughness parameters are varied by creating nanoparticle coatings of various formulations and applying them to inserts that cover approximately the first 14% of the swept flat-plate model. In addition to the baseline configuration (no added roughness, root-mean-square (RMS) ≈ 0.4 µm ), 5 panels with RMS roughness values of 4.8 up to 17 µm and correlation lengths ranging from 92 to 876 µm were tested. Despite the significant roughness levels tested, the transition location was found to be only mildly impacted by the additional roughness. However, the SCF amplitudes and wavelength content were found to vary substantially depending on the roughness input. The results were somewhat unexpected, in that the panel with the highest roughness RMS level did not result in the largest initial amplitudes, nor did the panel with the most energy in the SCF wavelength range. Rather, the panel with the most energy in the smaller wavelengths resulted in the largest SCF amplitude. There were, however, significant variations in the results when the panels were rotated by 180 ◦ , indicating that the important factor for some of the panels may be isolated peaks that occur near the neutral point.

stationary crossflow instabilities↗

Long‐term continuous cropping affects ecoenzymatic stoichiometry of microbial nutrient acquisition: a case study from a Chinese Mollisol

Abstract BACKGROUND Soil‐ and plant‐produced extracellular enzymes drive nutrient cycling in soils and are assumed to regulate supply and demand for carbon (C) and nutrients within the soil. Thus, agriculture management decisions that alter the balance of plant and supplemental nutrients should directly alter extracellular enzyme activities (EEAs), and EEA stoichiometry in predictable ways. We used a 12‐year experiment that varyied three major continuous grain crops (wheat, soybean, and maize), each crossed with mineral fertilizer (WCF, SCF and MCF, respectively) or not fertilized (WC, SC and MC, respectively, as controls). In response, we measured the phospholipid fatty acids (PLFAs), EEAs and their stoichiometry to examine the changes to soil microbial nutrient demand under the continuous cropping of crops, which differed with respect to the input of plant litter and fertilizer. RESULTS Fertilizer generally decreased soil microbial biomass and enzyme activity compared to non‐fertilized soil. According to enzyme stoichiometry, microbial nutrient demand was generally C‐ and phosphorus (P)‐limited, but not nitrogen (N)‐limited. However, the degree of microbial resource limitation differed among the three crops. The enzymatic C:N ratio was significantly lower by 13.3% and 26.8%, whereas the enzymatic N:P ratio was significantly higher by 9.9% and 42.4%, in MCF than in WCF and SCF, respectively. The abundances of arbuscular mycorrhizal fungi and aerobic PLFAs were significantly higher in MCF than in WCF and SCF. CONCLUSION These findings are crucial for characterizing enzymatic activities and their stoichiometries that drive microbial metabolism with respect to understanding soil nutrient cycles and environmental conditions and optimizing practices of agricultural management. © 2021 Society of Chemical Industry.

Chen, Xu↗

Helium Incorporation into Scandium Fluoride, a Model Negative Thermal Expansion Material

Scandium trifluoride is a model negative thermal expansion (NTE) material. Its simple structure can be described as an A-site vacant perovskite, and it shows isotropic NTE over a very wide temperature range (up to ~1100 K), due to transverse vibrational motion of the fluoride. Like many framework NTE materials, it undergoes a phase transition at low pressures, adopting a rhombohedral (R3̅c) structure at >0.7 GPa and 300 K in commonly used nonpenetrating pressure media, such as silicone oil. High pressure X-ray diffraction data and gas uptake/release measurements indicate that, on compression in helium above ~200 K, helium is inserted into ScF 3 to form the defect perovskite He x ScF 3 . The incorporation of helium stiffens the structure and changes its phase behavior. At room temperature, complete filling of the structure with helium does not occur until >1.5 GPa. On compression, a cubic perovskite structure is maintained until ~5 GPa. As the pressure was increased to ~9.5 GPa, a further transition occurred at ~7 GPa. The first transition at ~5 GPa is likely to a tetragonal (P4/mbm) perovskite, but the detailed structure of the perovskite phase formed on compression above ~7 GPa is unclear. Cooling down from 300 to 100 K in helium at ~0.4 GPa leads to an approximate composition of He 0.1 ScF 3 . High pressure neutron diffraction measurements, in the temperature range 15–150 K show that the incorporation of helium increases the pressure at which the cubic (Pm3̅m) to rhombohedral (R3̅c) putative quantum structural phase transition occurs from close to 0 GPa to ~0.2 GPa at 0 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Localized Active Space Pair-Density Functional Theory

Accurate quantum chemical methods for the prediction of spin-state energy gaps for strongly correlated systems are computationally expensive and scale poorly with the size of the system. This makes calculations for many experimentally interesting molecules impractical even with abundant computational resources. Previous work has shown that the localized active space (LAS) self-consistent field (SCF) method can be an efficient way to obtain multiconfiguration SCF wave functions of comparable quality to the corresponding complete active space (CAS) ones. To obtain quantitative results, a post-SCF method is needed to estimate the complete correlation energy. One such method is multiconfiguration pair-density functional theory (PDFT), which calculates the energy based on the density and on-top pair density obtained from a multiconfiguration wave function. In this work, we introduce localized-active-space PDFT, which uses a LAS wave function for subsequent PDFT calculations. The method is tested by computing spin-state energies and gaps in conjugated organic molecules and a bimetallic compound and comparing to the corresponding CAS-PDFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Slater transition methods for core-level electron binding energies

Methods for computing core-level ionization energies using self-consistent field (SCF) calculations are evaluated and benchmarked. These include a “full core hole” (or “ΔSCF”) approach that fully accounts for orbital relaxation upon ionization, but also methods based on Slater’s transition concept in which the binding energy is estimated from an orbital energy level that is obtained from a fractional-occupancy SCF calculation. A generalization that uses two different fractional-occupancy SCF calculations is also considered. The best of the Slater-type methods afford mean errors of 0.3–0.4 eV with respect to experiment for a dataset of K-shell ionization energies, a level of accuracy that is competitive with more expensive many-body techniques. An empirical shifting procedure with one adjustable parameter reduces the average error below 0.2 eV. Here, this shifted Slater transition method is a simple and practical way to compute core-level binding energies using only initial-state Kohn–Sham eigenvalues. It requires no more computational effort than ΔSCF and may be especially useful for simulating transient x-ray experiments where core-level spectroscopy is used to probe an excited electronic state, for which the ΔSCF approach requires a tedious state-by-state calculation of the spectrum. As an example, we use Slater-type methods to model x-ray emission spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗