Comparison of several system identification methods for flexible structures

In the last few years various methods of identifying structural dynamics models from modal testing data have appeared. A comparison is presented of four of these algorithms: the Eigensystem Realization Algorithm (ERA), the modified version ERA/DC where DC indicated that it makes use of data correlation, the Q-Markov Cover algorithm, and an algorithm due to Moonen, DeMoor, Vandenberghe, and Vandewalle. The comparison is made using a five mode computer module of the 20 meter Mini-Mast truss structure at NASA Langley Research Center, and various noise levels are superimposed to produced simulated data. The results show that for the example considered ERA/DC generally gives the best results; that ERA/DC is always at least as good as ERA which is shown to be a special case of ERA/DC; that Q-Markov requires the use of significantly more data than ERA/DC to produce comparable results; and that is some situations Q-Markov cannot produce comparable results

Reduced order models for control of fluids using the Eigensystem Realization Algorithm

In feedback flow control, one of the challenges is to develop mathematical models that describe the fluid physics relevant to the task at hand, while neglecting irrelevant details of the flow in order to remain computationally tractable. A number of techniques are presently used to develop such reduced-order models, such as proper orthogonal decomposition (POD), and approximate snapshot-based balanced truncation, also known as balanced POD. Each method has its strengths and weaknesses: for instance, POD models can behave unpredictably and perform poorly, but they can be computed directly from experimental data; approximate balanced truncation often produces vastly superior models to POD, but requires data from adjoint simulations, and thus cannot be applied to experimental data. In this paper, we show that using the Eigensystem Realization Algorithm (ERA) \citep{JuPa-85}, one can theoretically obtain exactly the same reduced order models as by balanced POD. Moreover, the models can be obtained directly from experimental data, without the use of adjoint information. The algorithm can also substantially improve computational efficiency when forming reduced-order models from simulation data. If adjoint information is available, then balanced POD has some advantages over ERA: for instance, it produces modes that are useful for multiple purposes, and the method has been generalized to unstable systems. We also present a modified ERA procedure that produces modes without adjoint information, but for this procedure, the resulting models are not balanced, and do not perform as well in examples. We present a detailed comparison of the methods, and illustrate them on an example of the flow past an inclined flat plate at a low Reynolds number.Comment: 22 pages, 7 figure

SMLFire1.0: a stochastic machine learning (SML) model for wildfire activity in the western United States

The annual area burned due to wildfires in the western United States (WUS) increased by more than 300 % between 1984 and 2020. However, accounting for the nonlinear, spatially heterogeneous interactions between climate, vegetation, and human predictors driving the trends in fire frequency and sizes at different spatial scales remains a challenging problem for statistical fire models. Here we introduce a novel stochastic machine learning (SML) framework, SMLFire1.0, to model observed fire frequencies and sizes in 12 km × 12 km grid cells across the WUS. This framework is implemented using mixture density networks trained on a wide suite of input predictors. The modeled WUS fire frequency matches observations at both monthly (r=0.94) and annual (r=0.85) timescales, as do the monthly (r=0.90) and annual (r=0.88) area burned. Moreover, the modeled annual time series of both fire variables exhibit strong correlations (r≥0.6) with observations in 16 out of 18 ecoregions. Our ML model captures the interannual variability and the distinct multidecade increases in annual area burned for both forested and non-forested ecoregions. Evaluating predictor importance with Shapley additive explanations, we find that fire-month vapor pressure deficit (VPD) is the dominant driver of fire frequencies and sizes across the WUS, followed by 1000 h dead fuel moisture (FM1000), total monthly precipitation (Prec), mean daily maximum temperature (Tmax), and fraction of grassland cover in a grid cell. Our findings serve as a promising use case of ML techniques for wildfire prediction in particular and extreme event modeling more broadly. They also highlight the power of ML-driven parameterizations for potential implementation in fire modules of dynamic global vegetation models (DGVMs) and earth system models (ESMs).</p

Quasiparticle dynamics and phonon softening in FeSe superconductors

Quasiparticle dynamics of FeSe single crystals revealed by dual-color transient reflectivity measurements ({\Delta}R/R) provides unprecedented information on Fe-based superconductors. The amplitude of fast component in {\Delta}R/R clearly tells a competing scenario between spin fluctuations and superconductivity. Together with the transport measurements, the relaxation time analysis further exhibits anomalous changes at 90 K and 230 K. The former manifests a structure phase transition as well as the associated phonon softening. The latter suggests a previously overlooked phase transition or crossover in FeSe. The electron-phonon coupling constant {\lambda} is found to be 0.16, identical to the value of theoretical calculations. Such a small {\lambda} demonstrates an unconventional origin of superconductivity in FeSe.Comment: Final published version; 5 pages; 4 figure

Three-dimensional optical method for integrated visualization of mouse islet microstructure and vascular network with subcellular-level resolution

Microscopic visualization of islets of Langerhans under normal and diabetic conditions is essential for understanding the pathophysiology of the disease. The intrinsic opacity of pancreata, however, limits optical accessibility for high-resolution light microscopy of islets in situ. Because the standard microtome-based, 2-D tissue analysis confines visualization of the islet architecture at a specific cut plane, 3-D representation of image data is preferable for islet assessment. We applied optical clearing to minimize the random light scattering in the mouse pancreatic tissue. The optical-cleared pancreas allowed penetrative, 3-D microscopic imaging of the islet microstructure and vasculature. Specifically, the islet vasculature was revealed by vessel painting-lipophilic dye labeling of blood vessels-for confocal microscopy. The voxel-based confocal micrographs were digitally processed with projection algorithms for 3-D visualization. Unlike the microtome-based tissue imaging, this optical method for penetrative imaging of mouse islets yielded clear, continuous optical sections for an integrated visualization of the islet microstructure and vasculature with subcellular-level resolution. We thus provide a useful imaging approach to change our conventional planar view of the islet structure into a 3-D panorama for better understanding of the islet physiology. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3470241

Endothelial cell-surface tissue transglutaminase inhibits neutrophil adhesion by binding and releasing nitric oxide

Nitric oxide (NO) produced by endothelial cells in response to cytokines displays anti-inflammatory activity by preventing the adherence, migration and activation of neutrophils. The molecular mechanism by which NO operates at the blood-endothelium interface to exert anti-inflammatory properties is largely unknown. Here we show that on endothelial surfaces, NO is associated with the sulfhydryl-rich protein tissue transglutaminase (TG2), thereby endowing the membrane surfaces with anti-inflammatory properties. We find that tumor necrosis factor-α-stimulated neutrophil adherence is opposed by TG2 molecules that are bound to the endothelial surface. Alkylation of cysteine residues in TG2 or inhibition of endothelial NO synthesis renders the surface-bound TG2 inactive, whereas specific, high affinity binding of S-nitrosylated TG2 (SNO-TG2) to endothelial surfaces restores the anti-inflammatory properties of the endothelium, and reconstitutes the activity of endothelial-derived NO. We also show that SNO-TG2 is present in healthy tissues and that it forms on the membranes of shear-activated endothelial cells. Thus, the anti-inflammatory mechanism that prevents neutrophils from adhering to endothelial cells is identified with TG2 S-nitrosylation at the endothelial cell-blood interface

Spatial Symmetry of Superconducting Gap in YBa2Cu3O7-\delta Obtained from Femtosecond Spectroscopy

The polarized femtosecond spectroscopies obtained from well characterized (100) and (110) YBa2Cu3O7-\delta thin films are reported. This bulk-sensitive spectroscopy, combining with the well-textured samples, serves as an effective probe to quasiparticle relaxation dynamics in different crystalline orientations. The significant anisotropy in both the magnitude of the photoinduced transient reflectivity change and the characteristic relaxation time indicates that the nature of the relaxation channel is intrinsically different in various axes and planes. By the orientation-dependent analysis, d-wave symmetry of the bulk-superconducting gap in cuprate superconductors emerges naturally.Comment: 8 pages, 4 figures. To be published in Physical Review B, Rapid Communication

Simultaneous Excitation of Multiple-Input Multiple-Output CFD-Based Unsteady Aerodynamic Systems

A significant improvement to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) is presented. This improvement involves the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system that enables the computation of the unsteady aerodynamic state-space model using a single CFD execution, independent of the number of structural modes. Four different types of inputs are presented that can be used for the simultaneous excitation of the structural modes. Results are presented for a flexible, supersonic semi-span configuration using the CFL3Dv6.4 code