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At least 415 records · Page 23

Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

Geology↗

California's harvested wood products: A time-dependent assessment of life cycle greenhouse gas emissions

Following life-cycle assessment (LCA) methodology, this study presents a state-level estimation of embodied carbon of wood products harvested in 2019 from California and subsequently processed, manufactured, transported, used, and disposed at the end-of-life (EoL). In a conventional static approach to LCA, all GHG emissions were aggregated and considered to occur at year 0 of the given time horizon (500 years in this study) and used a static characterization factor (CF). In dynamic LCA, GHG emissions occurring in different years were considered, and their global warming impact (GWI) was determined using a time-dependent CF over the selected time horizon of 500 years. Four scenarios were developed to examine the impact of EoL choices on GWI. It was found that dynamic GWI for all scenarios ranged from 0.27 to 0.93 million tonne CO₂e, which were 45–73 % lower than those estimated with static LCA approach, indicating that the static LCA approach could lead to an underestimation of the benefits of substituting wood for non-wood products, compared to those based on dynamic LCA approach. This analysis also demonstrated that the choice of EoL treatment option is a key factor affecting the estimated GWI as it directly determines the annual emission of GHGs released into atmosphere and subsequently their warming effect depending on the time harvested wood products (HWPs) spend in the horizon of assessment. Altogether, the dynamic LCA performed in this study enabled more robust interpretations of embodied carbon by including temporal boundaries associated with the HWPs life cycle.

54 ENVIRONMENTAL SCIENCES↗

Pattern Mining and Anomaly Detection based on the Power System Synchrophasor Measurements

Real-time monitoring of power system dynamics using phasor measurement units (PMUs) data improves situational awareness and system reliability and potentially can help prevent blackouts due to early anomaly detection. The study presented in the paper is based on the actual PMU measurements of the U.S. western interconnection system. Given the nonlinear and nonstationary PMUs data, we developed a robust anomaly detection framework. Wavelet-based multi-resolution analysis, combined with moving-window-based outlier detection and anomaly scoring, were deployed to identify potential PMU events. The candidate events were evaluated using spatiotemporal correlation analysis, and then classified for a better understanding of the event types. The results demonstrated successful anomaly detection and classification, compared with the recorded real-world events.

Ren, Huiying↗

Embedded Fiber Bragg Grating (FBG) Sensors Fabricated by Ultrasonic Additive Manufacturing for High-Frequency Dynamic Strain Measurements

This article demonstrates high-frequency dynamic strain measurements using fiber Bragg grating (FBG) sensors embedded in metal parts. Using an ultrasonic additive manufacturing (UAM) process, FBGs inscribed in polyimide coated optical fibers were embedded in aluminum parts. An electromagnetic shaker was used to exert dynamic events on the embedded FBG sensors with frequencies from 1 to 10 kHz. The high-speed interrogation of FBG sensors was accomplished using a tunable vertical-cavity surface-emitting laser (VCSEL) and a high-speed interrogation system sampling at 120 kHz. The strain response measured by the FBG sensors was compared with real-time measurements using a laser velocimeter. A finite-element analysis (FEA) was performed to simulate responses to both static strain and high-frequency dynamic strain. In conclusion, results show that strains as small as 2.5$με$ can be resolved at frequencies up to 10 kHz.

36 MATERIALS SCIENCE↗

Reduction of electron-phonon coupling in warm dense iron

The electron-ion relaxation dynamics in warm dense iron were investigated by time-resolved x-ray absorption near-edge spectroscopy (XANES). A novel analysis, combining ab initio density functional theory (DFT) and two temperature model (TTM) simulations, was developed to calculate the x-ray absorption spectra as a function of delay time. Here we present experimental evidence of changes at the XAS L3 edge of iron that are consistent with the reduction of the electron-phonon coupling under warm dense matter conditions. The experimental results are in agreement with the model that takes both the electron ($T_e$) and the ion temperature ($T_i$) dependence of the thermophysical properties into consideration, while models where either constant electron-phonon coupling factor (G) or only $T_e$- dependent G are used do not agree with the observed relaxation dynamics of iron.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Proton Transfer Dynamics in the Aprotic Proton Accepting Solvent 1-Methylimidazole

The dynamics of proton transfer to the aprotic solvent 1-methylimidazole (MeIm, proton acceptor) from the photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt (HPTS) were investigated using fast fluorescence measurements. The closely related molecule, 8- methoxypyrene-1,3,6-trisulfonic acid trisodium salt (MPTS), which is not a photoacid, was also studied for comparison. Following optical excitation, the wavelength-dependent population dynamics of HPTS in MeIm resulting from the deprotonation process were collected over the entire fluorescence emission window. Analysis of the time-dependent fluorescence spectra revealed four distinct fluorescence bands that appear and decay on different time scales. We label these four states as: protonated (P), associated I (A I ), associated II (A II ), and deprotonated (D). We find that the simple kinetic scheme of P → A I → A II → D is not consistent with the data. Instead, the kinetic scheme that describes the data has P decaying into A I , which mainly goes on to deprotonation (D), but AI can also feed into A II . A II can return to A I or decay to the ground state, but does not deprotonate within experimental error. Finally, quantum chemistry and excitedstate QM/MM Born-Oppenheimer molecular dynamics simulations indicate that A I and A II are two H-bonding conformations of MeIm to the HPTS hydroxyl, axial and equatorial, respectively.

14 SOLAR ENERGY↗

Analysis of ultrafast magnetization switching dynamics in exchange-coupled ferromagnet–ferrimagnet heterostructures

Magnetization switching in ferromagnets has so far been limited to the current-induced spin–orbit–torque effects. Recent observation of helicity-independent all-optical magnetization switching (HI-AOS) in an exchange-coupled ferromagnet–ferrimagnet (FM-FEM) heterostructures expanded the range and applicability of such ultrafast heat-driven magnetization switching. Here we report the element-resolved HI-AOS dynamics of such an exchange-coupled system, using a modified microscopic three-temperature model. We have studied the effect of (i) the Curie temperature of the FM, (ii) FEM composition, (iii) the long-range Ruderman–Kittel–Kasuya–Yosida (RKKY) exchange-coupling strength, and (iv) the absorbed optical energy on the element-specific time-resolved magnetization dynamics. The phase-space of magnetization illustrates how the RKKY coupling strength and the absorbed optical energy influence the switching time. Our analysis demonstrates that the threshold switching energy depends on the composition of the FEM and the switching time depends on the Curie temperature of the FM as well as RKKY coupling strength. Importantly, this simulation anticipates new insights into developing faster and more energy-efficient spintronics devices.

36 MATERIALS SCIENCE↗

The myth of URANS

Since the 1990s, RANS practitioners have observed spontaneous unsteadiness in RANS simulations. Some have suggested deliberately using this as a method of resolving large turbulent structures. However, to date, no one has produced a theoretical justification for this unsteady RANS (URANS) approach. Here, we extend the dynamical system fixed point analysis to create a theoretical model for URANS dynamics. The results are compared to URANS simulations for homogeneous isotropic decaying turbulence. The model shows that URANS can predict incorrect decay rates and that the solution tends towards steady RANS over time. Similar analysis for forced turbulence shows a fixed modelled energy of about 30% of total energy, regardless of the model parameters. The same analysis can be used to show how hybrid type models can begin to address these issues.

97 MATHEMATICS AND COMPUTING↗

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Towards the Ultimate Strength of Medium‐Entropy Alloys Through Pulsed Lasers

The tensile strength of metals at extreme strain rates is a key predictor of their performance in ballistic and structural impact applications. An important experimental method to reach these extreme strain rates is the use of high-amplitude, short-duration pulsed lasers. The Jupiter Laser Facility at the Lawrence Livermore National Laboratory enabled probing for the first time the mechanical response of several promising High Entropy Alloys at times on the order of nanoseconds (strain rates of ∼10 7 and ∼10 9 s −1 ). The measured strength is in the range of 6 to 10 GPa, ten times the quasistatic value. The mechanisms of plastic deformation and failure were identified and quantified through analysis and molecular dynamics simulation. The reflected wave amplitudes, obtained by VISAR, were used to determine the tensile (spall) stress. The high tensile strength obtained is due to two factors: the strain-rate dependence of plastic flow and the kinetics of void nucleation, growth, and coalescence. The experimental results are compared with an analytical prediction considering both grain-interior and grain-boundary void initiation. Molecular dynamics simulations, conducted at strain rates of 10 8 and 10 9 s −1 , rationalize the experimental results. In conclusion, they provide valuable information about the process of failure evolution, and reveal that grain boundary separation plays a pivotal role in spalling.

Materials science↗

Microstructure Analysis and Rheological Behavior of Magnesium Alloys at Semi-solid Temperature Range

Microstructure and rheological properties of AZ91 and Elektron 21 magnesium alloys in semi-solid state were studied. Differential scanning calorimetry revealed significant differences in melting range in analyzed materials. Isothermal annealing for 5, 30 and 80 min, in semi-solid range, corresponding to 50 and 70% of solid fraction, showed slower microstructure coarsening kinetics in Elektron 21 due to the presence of Zr- and RE-enriched precipitations. Ostwald ripening and coalescence resulted in decrease in grains density with increasing annealing time and temperature. Hardness after annealing showed overall tendency to diminish with soaking time probably due to the growth of average grain size. Rheological analysis showed tendency to lower the value of dynamic viscosity coefficient as shear rate rise, which confirmed non-Newtonian flow behavior. The highest values of dynamic viscosity coefficient were obtained for alloy AZ91.

36 MATERIALS SCIENCE↗

A strategy based on thermal flexibility to design triosephosphate isomerase proteins with increased or decreased kinetic stability

Kinetic stability of proteins determines their susceptibility to irreversibly unfold in a time-dependent process, and therefore its half-life. A residue displacement analysis of temperature-induced unfolding molecular dynamics simulations was recently employed to define the thermal flexibility of proteins. This property was found to be correlated with the activation energy barrier (E{sub act}) separating the native from the transition state in the denaturation process. The E{sub act} was determined from the application of a two-state irreversible model to temperature unfolding experiments using differential scanning calorimetry (DSC). The contribution of each residue to the thermal flexibility of proteins is used here to propose multiple mutations in triosephosphate isomerase (TIM) from Trypanosoma brucei (TbTIM) and Trypanosoma cruzi (TcTIM), two parasites closely related by evolution. These two enzymes, taken as model systems, have practically identical structure but large differences in their kinetic stability. We constructed two functional TIM variants with more than twice and less than half the activation energy of their respective wild-type reference structures. The results show that the proposed strategy is able to identify the crucial residues for the kinetic stability in these enzymes. As it occurs with other protein properties reflecting their complex behavior, kinetic stability appears to be the consequence of an extensive network of inter-residue interactions, acting in a concerted manner. The proposed strategy to design variants can be used with other proteins, to increase or decrease their functional half-life.

60 APPLIED LIFE SCIENCES↗

Anomalous losses of energetic particles in the presence of an oscillating radial electric field in fusion plasmas

The confinement of energetic particles in nuclear fusion devices is studied in the presence of an oscillating radial electric field and an axisymmetric magnetic equilibrium. Here, it is shown that, despite the poloidal and toroidal symmetries, initially integrable orbits turn into chaotic regions that can potentially intercept the wall of the tokamak, leading to particle losses. It is observed that the losses exhibit algebraic time decay different from the expected exponential decay characteristic of radial diffusive transport. A dynamical explanation of this behaviour is presented, within the continuous time random walk theory. The central point of the analysis is based on the fact that, contrary to the radial displacement, the poloidal angle is not bounded and a proper statistical analysis can therefore be made, showing for the first time that energetic particle transport can be super-diffusive in the poloidal direction and characterised by asymmetric poloidal displacement. The connection between poloidal and radial positions ensured by the conservation of the toroidal canonical momentum, implies that energetic particles spend statistically more time in the inner region of the tokamak than in the outer one, which explains the observed algebraic decay. This indicates that energetic particles might be efficiently slowed down by the thermal population before leaving the system. Also, the asymmetric transport reveals a new possible mechanism of self-generation of momentum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In Situ X-ray Scattering Reveals Coarsening Rates of Superlattices Self-Assembled from Electrostatically Stabilized Metal Nanocrystals Depend Nonmonotonically on Driving Force

Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with promising functionalities. Mechanistic studies are still needed to uncover the design principles for SL self-assembly, but such studies have been difficult to perform due to the fast time and short length scales of NC systems. To address this challenge, we developed an apparatus to directly measure the evolving phases in situ and in real time of an electrostatically stabilized Au NC solution before, during, and after it is quenched to form SLs using small-angle X-ray scattering. By developing a quantitative model, we fit the time-dependent scattering patterns to obtain the phase diagram of the system and the kinetics of the colloidal and SL phases as a function of varying quench conditions. The extracted phase diagram is consistent with particles whose interactions are short in range relative to their diameter. We find the degree of SL order is primarily determined by fast (subsecond) initial nucleation and growth kinetics, while coarsening at later times depends nonmonotonically on the driving force for self-assembly. We validate these results by direct comparison with simulations and use them to suggest dynamic design principles to optimize the crystallinity within a finite time window. The combination of this measurement methodology, quantitative analysis, and simulation should be generalizable to elucidate and better control the microscopic self-assembly pathways of a wide range of bottom-up assembled systems and architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of NDE for Key Indicators of Aging Cables in Nuclear Power Plants – Interim Status

Degradation of the cable jacket, electrical insulation, and other cable components of installed cables within nuclear power plants (NPPs) is known to occur as a function of age, temperature, radiation, and other environmental factors. System tests verify cable function under normal loads; however, the concern is over cable performance under exceptional loads associated with design-basis events (DBEs). The cable’s ability to perform safely over the initial 40 year planned and licensed life has generally been demonstrated and there have been very few age-related cable failures. With greater than 1000 km of power, control, instrumentation, and other cables typically found in an NPP, replacing all the cables would be a severe cost burden. Justification for life extension to 60 and 80 years requires a cable aging management program to justify cable performance under normal operation as well as accident conditions. Currently the gold standard for determining cable insulation degradation is the elongation-at-break (EAB). This, however, is an ex-situ measurement and requires removal of a sample for laboratory investigation. A reliable nondestructive examination (NDE) in-situ approach is desirable to objectively determine the suitability of the cable for service. A variety of tests are available to assess various aspects of electrical and mechanical cable performance, but none of these tests are suitable for all cable configurations nor does any single test confirm all features of interest. Nevertheless, the complete collection of test possibilities offers a powerful range of tools to assure the integrity of critical cables. Licensees and regulators have settled on a practical program to justify continued operation based on condition monitoring of a lead sample set of cables where test data is tracked in a database and the required test data are continually adjusted based on plant and fleet-wide experience. As part of the Light Water Reactor Sustainability program sponsored by the U.S. Nuclear Regulatory Commission, the U.S. Department of Energy, and industry (represented by the Electric Power Research Institute), an assessment of cable NDE methods was commissioned. Technologies include both bulk electrical measurements (Tan d, time domain reflectometry, frequency domain reflectometry (FDR), partial discharge, and other techniques) and local insulation measurement (indenter, dynamic mechanical analysis interdigital capacitance, infrared spectral measurement, etc.). This aging cable NDE program update reviews the full range of techniques but focuses on the most interesting test approaches that have a chance to be deployed in-situ, particularly including Tan d, FDR, and ultrasound methods that have been reviewed most completely in this progress period.

cable aging inspection↗

Quantum advantage for differential equation analysis

Quantum algorithms for differential equation solving, data processing, and machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. In this study, we demonstrate that, when combined, these difficulties solve one another. We show how the output of quantum differential equation solving can serve as the input for quantum data processing and machine learning, allowing dynamical analysis in terms of principal components, power spectra, and wavelet decompositions. To illustrate this, we consider continuous-time Markov processes on epidemiological and social networks. These quantum algorithms provide an exponential advantage over existing classical Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing with Patterned Nanomagnet Arrays

Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previous works have demonstrated methods to physically probe these magnetization dynamics of PNAs to realize neuromorphic reservoir systems that exhibit chaotic dynamical behavior and high-dimensional nonlinearity. These PNA reservoir systems from prior works leverage echo state properties and linear/nonlinear short-term memory of component reservoir nodes to map and preserve the dynamical information of the input time-series data into nondelay spatial embeddings. Such mappings enable these PNA reservoir systems to imitate and predict/forecast the input time series data. However, these prior PNA reservoir systems are based solely on the nondelay spatial embeddings obtained at component reservoir nodes. As a result, they require a massive number of component reservoir nodes, or a very large spatial embedding (i.e., high-dimensional spatial embedding) per reservoir node, or both, to achieve acceptable imitation and prediction accuracy. These requirements reduce the practical feasibility of such PNA reservoir systems. To address this shortcoming, we present a mixed delay/nondelay embeddings-based PNA reservoir system. Our system uses a single PNA reservoir node with the ability to obtain a mixture of delay/nondelay embeddings of the dynamical information of the time-series data applied at the input of a single PNA reservoir node. Our analysis shows that when these mixed delay/nondelay embeddings are used to train a perceptron at the output layer, our reservoir system outperforms existing PNA-based reservoir systems for the imitation of NARMA 2, NARMA 5, NARMA 7, and NARMA 10 time series data, and for the short-term and long-term prediction of the Mackey Glass time series data.

Ti, Changpeng↗