Frequency Variation Research Articles

Magma fizz: Tremor during the Kīlauea summit reservoir decompression

Typical eruptions at Kīlauea volcano involve the evacuation of magma from the summit and/or south caldera reservoirs towards the East or Southwest rift zones. The reservoir drainage provokes the summit deflation, and on extreme occasions, such as in 2018, the summit caldera collapse. Systematically, seismic tremor, often with a particular multichromatic spectral signature characterized by frequency gliding, accompanies summit deflation episodes. In 2018, this type of continuous tremor accompanied the steady subsidence stage, whereas discrete earthquakes dominated the collapse stage. In this work, we aim to understand the source mechanism of the syn-deflation tremor of 2018. To locate the seismic source, we develop a novel machine-learning-based algorithm as an alternative to the amplitude source location technique. We use a large high-resolution catalog to resolve a composite amplitude decay function. Under these conditions, our method outperforms the traditional technique. We locate the tremor source 1 km below the eastern perimeter of the Halema‘uma‘u crater, which coincides with the position of the summit magma reservoir, as determined in many other studies. Furthermore, we model the seismic source as pressure oscillations driven by gas porous flow at the roof of the reservoir. In this model, gas accumulates temporarily in many gas pockets between the magma and the roof. Our modeling shows that the gas flux is responsible for the tremor amplitude modulations, whereas the gas pocket thickness controls the frequency variations. Beyond a critical point of depressurization, the magma cannot contribute further to the tremor oscillations via decompression-driven degassing, nor support the roof above it, resulting in rock failure. This work advances our understanding of magma-degassing dynamics and tremor generation at Kilauea volcano, and provides novel seismological techniques for volcano seismology monitoring and research.

Contrasting Dynamics of Intracellular and Extracellular Antibiotic Resistance Genes in Response to Nutrient Variations in Aquatic Environments.

The propagation of antibiotic resistance in environments, particularly aquatic environments that serve as primary pathways for antibiotic resistance genes (ARGs), poses significant health risks. The impact of nutrients, as key determinants of bacterial growth and metabolism, on the propagation of ARGs, particularly extracellular ARGs (eARGs), remains poorly understood. In this study, we collected microorganisms from the Yangtze River and established a series of microcosms to investigate how variations in nutrient levels and delivery frequency affect the relative abundance of intracellular ARGs (iARGs) and eARGs in bacterial communities. Our results show that the relative abundance of 7 out of 11 representative eARGs in water exceeds that of iARGs, while 8 iARGs dominate in biofilms. Notably, iARGs and eARGs consistently exhibited opposite responses to nutrient variation. When nutrient levels increased, iARGs in the water also increased, with the polluted group (COD = 333.3 mg/L, COD:N:P = 100:3:0.6, m/m) and the eutrophic group (COD = 100 mg/L, COD:N:P = 100:25:5, m/m) showing 1.2 and 3.2 times higher levels than the normal group (COD = 100 mg/L, COD:N:P = 100:10:2, m/m), respectively. In contrast, eARGs decreased by 6.7% and 8.4% in these groups. On the other hand, in biofilms, higher nutrient levels led to an increase in eARGs by 1.5 and 1.7 times, while iARGs decreased by 17.5% and 50.1% in the polluted and eutrophic groups compared to the normal group. Moreover, while increasing the frequency of nutrient delivery (from 1 time/10 d to 20 times/10 d) generally did not favor iARGs in either water or biofilm, it selectively enhanced eARGs in both. To further understand these dynamics, we developed an ARGs-nutrient model by integrating the Lotka-Volterra and Monod equations. The results highlight the complex interplay of bacterial growth, nutrient availability, and mechanisms such as horizontal gene transfer and secretion influencing ARGs' propagation, driving the opposite trend between these two forms of ARGs. This contrasting response between iARGs and eARGs contributes to a dynamic balance that stabilizes bacterial resistance levels amid nutrient fluctuations. This study offers helpful implications regarding the persistence of bacterial resistance in the environment.

Optimization research on control strategies for photovoltaic energy storage systems considering multi-mode operation

In this paper, a selective input/output strategy is proposed for improving the life of photovoltaic energy storage (PV-storage) virtual synchronous generator (VSG) caused by random load interference, which can sharply reduce costs of storage device. The strategy consists of two operating modes and a power coordination control method for the VSGs. Firstly, a selective VSG input strategy is proposed based on the magnitude of disturbances, a method of offline solving model equation is used for determine the VSG input time. An online method is used for matching the disturbance frequency variations, which enables a selective VSG startup method, allowing the grid to prioritize the utilization of the generator's physical inertia. Secondly, a dynamic VSG exit strategy is developed based on dynamic frequency characteristics to prevent secondary oscillations in the frequency recovery phase of the PV-storage VSG following grid disturbances. This strategy is crucial as grid variations may affect energy storage lifespan and reduce frequency recovery speed. Finally, the proposed approach is validated for correctness and effectiveness through computer simulations and semi-physical experiments using the NI-PXI + LabVIEW platform. Through the above optimization and research, the selective start of VSG is realized, the energy storage life is improved, the capacity of charge and discharge cycles is reduced by 37.82 % compared with the strategy without investment and withdrawal, and the life loss in the secondary charge and discharge process of PV-storage VSG is avoided, which is conducive to frequency recovery.

Enhancing microgrid performance: Optimal proactive reactive power dispatch using photovoltaic active power forecasts

AbstractMicrogrids with substantial incorporation of distributed renewable energy sources face challenges such as magnitude voltage rise, frequency variations, and power quality issues. A novel method is proposed to managing and controlling reactive power within microgrids with high integration of photovoltaic panels. The proactive dispatch is carried out for a few minutes in advance, using power forecast and the inverters of the photovoltaic installations as reactive energy providers. The goal is to stabilise voltage levels and reduce overall energy losses. Optimising reactive power poses a non‐convex problem. The presented method tackles this challenge by employing Conic approximations and Wirtinger calculus techniques to convert and frame the issue within a convex framework, simplifying its resolution. It primarily concentrates on fine‐tuning reactive power output from photovoltaic inverters to minimise overall losses and maintain stable magnitude voltage levels. To enable the reactive power dispatch, a Markov switching forecasting model that uses on‐site data, including sky imagery and other external variables, predicting active power generation every 6 minutes. The proposed technique is evaluated in a CIGRE test network, showing an average loss reduction between 14% and 66% for sunny and cloudy conditions with different levels of PV penetration, this while maintaining the steady state voltages in range.

Optimizing real-time phase detection in diverse rhythmic biological signals for phase-specific neuromodulation.

Closed-loop, phase-specific neurostimulation is a powerful method to modulate ongoing brain activity for clinical and research applications. Phase-specific stimulation relies on estimating the phase of an ongoing oscillation in real time and issuing a control command at a target phase. Phase detection algorithms based on Fast Fourier transform (FFT) are widely used due to their computational efficiency and robustness. However, it is unclear how algorithm performance depends on the spectral properties of the input signal and how algorithm parameters can be optimized. We used offline simulation to evaluate the performance of three algorithms (endpoint-corrected Hilbert Transform, Hilbert Transform and phase mapping) on three rhythmic biological signals with distinct spectral properties (rodent hippocampal theta potential, human EEG alpha and human essential tremor). First, we found that algorithm performance was more strongly influenced by signal amplitude and frequency variation compared with signal to noise ratio. Second, our simulations showed that the size of the data window for phase estimation was critical for the performance of FFT-based algorithms, where the optimal data window corresponds to the period of the oscillation. We validated this prediction with real time phase detection of hippocampal theta oscillations in freely behaving rats performing spatial navigation. Our findings define the relationship between signal properties and algorithm performance and provide a convenient method for optimizing FFT-based phase detection algorithms.

Establishment and evaluation of dynamic viscoelasticity constitutive model for asphalt mixtures based on PCA model: Utilizing coal-based synthetic natural gas slag and phosphogypsum whisker as substitute fillers

To promote the secondary utilization of solid waste in asphalt pavement and reduce resource waste and environmental damage, the fine solid waste powder from the secondary treatment of solid waste was used as a substitute filler to prepare asphalt mixtures. To more precisely characterize the effects of filler type and substitution ratio on the dynamic viscoelastic mechanical characteristics of asphalt mixtures, the dynamic modulus test was conducted on asphalt mixtures, while the dynamic modulus master curve of asphalt mixtures was established based on the time-temperature equivalent principle and the Sigmoidal function. The improved generalized Sigmoidal (IGS) model, five-parameter fractional Zener (FFZ) model, six-parameter fractional Zener (SFZ) model and ten-parameter fractional Zener (TFZ) model were used to construct the shrinkage frequency curves of different asphalt mixtures under different constitutive relationships, whereas the applicability of the constitutive models was further evaluated by the principal component analysis (PCA) model. The research results showed that the dynamic modulus and phase angle of the mixture exhibited a similar change rule with the variation of temperature and frequency, and the use of solid waste-based fillers could effectively reduce the effect of frequency variation on the viscoelasticity of the mixture. The dynamic modulus master curve constructed by Sigmoidal function could accurately describe the functional relationship between the dynamic modulus with loading frequency and temperature, and the variation trend of dynamic modulus in a wider frequency range was flattened with the increase in frequency, and this change rule was not affected by the substitution ratio of the filler, while the use of solid waste-based filler could reduce the dependence of the mixture on the temperature. Compared to several fractional constitutive models, the IGS model exhibited a higher fitting accuracy for the dynamic viscoelasticity of several mixtures, and with the use of solid waste-based fillers, the deviation of fitting curves gradually decreased. A comparative study showed that the fractional constitutive model was difficult to accurately describe the dynamic viscoelasticity of the mixture, and the IGS model was preferred to be recommended as a calculation model to investigate the constitutive relationship on the dynamic viscoelasticity of the mixture.

Complex Dispersion Analysis of Flexural Wave Propagation in Periodic Track Structure

The periodic characteristics of the track structure have filtering characteristics for the propagation of vibration waves within it, and the dispersion analysis is of great significance to understand the vibration transmission characteristics of the track structure. The accuracy of the traditional virtual spring method depends on the value of spring stiffness, which leads to poor stability. Therefore, this paper adopts a null space method with both stability, accuracy and efficiency, and takes the CRTSIII ballastless track structure as the research object. Based on the null space method and energy functional variational principle, the damping factor and the material frequency variation effect are considered in detail, and the complex frequency dispersion of the CRTSIII ballastless track structure is analyzed. The accuracy of the proposed method is verified by comparing it with the results of the existing literature, and the influence of fastener stiffness frequency variation, fastener damping and concrete support layer damping on the complex dispersion characteristics of vibration waves of track structures is analyzed by using this method. The results show that the stiffness frequency effect, fastener damping and concrete support layer damping have a great influence on the attenuation domain and attenuation rate of vibration, which must be considered in the vibration transmission analysis of track structures.

Estimation of vibrational spectra of Trp-cage protein from nonequilibrium metadynamics simulations

The development of methods that allow a structural interpretation of linear and nonlinear vibrational spectra is of great importance, both for spectroscopy and for optimizing force field quality. The experimentally measured signals are ensemble averages over all accessible configurations, which complicates spectral calculations. To account for this, we present a recipe for calculating vibrational amide-I spectra of proteins based on metadynamics molecular dynamics simulations. For each frame, a one-exciton Hamiltonian is set up for the backbone amide groups, in which the couplings are estimated with the transition-charge coupling model for nonnearest neighbors, and with a parametrized map of ab initio calculations that give the coupling as a function of the dihedral angles for nearest neighbors. The local-mode frequency variations due to environmental factors such as hydrogen bonds are modeled by exploiting the linear relationship between the amide C-O bond length and the amide-I frequency. The spectra are subsequently calculated while taking into account the equilibrium statistical weights of the frames that are determined using a previously published reweighting procedure. By implementing all these steps in an efficient Fortran code, the spectra can be averaged over very large amounts of structures, thereby extensively covering the phase space of proteins. Using this recipe, the spectral responses of 2.5 million frames of a metadynamics simulation of the miniprotein Trp-cage are averaged to reproduce the experimental temperature-dependent IR spectra very well. The spectral calculations provide new insight into the origin of the various spectral signatures (which are typically challenging to disentangle in the congested amide-I region), and allow for a direct structural interpretation of the experimental spectra and for validation of the molecular dynamics simulations of ensembles.

Developing a predictive method based on the vibration behavior of a naval ship hull model using hybrid fuzzy meta-heuristic algorithms

Ships are complex structures composed of various components with exclusive dynamic behaviors and natural frequencies, so assessing their vibration behavior is essential. Some situations in practical applications could alter the ship's dynamic characteristics and cause significant changes in its vibration behavior. Since the ship's mass is one of the most important dynamic parameters in determining vibration behavior, local mass change can lead to changes in its dynamic characteristics and must be considered. This study aims to develop a method to predict the effect of the location and magnitude of mass change on the ship hull's vibration behavior. It would be feasible to enhance the dynamic behavior and reduce undesirable noises by locating the mass change on the ship hull. In this regard, experimental and numerical modal analysis is performed on a scaled model of a naval ship hull. The baseline FE model is used to calculate the variation in frequencies of the model caused by different local mass change scenarios. Using these measurements a fuzzy system is generated and optimized by Genetic and Particle Swarm Optimization algorithms. Finally, the efficiency of the fuzzy-PSO is validated by different mass change scenarios foreseen on the physical model of the ship hull.

Analytical Investigation of the Effects of Additional Load Mass on the Fundamental Frequency of Pedestrian Beam Bridges

The aspect of resonant vibrations due to pedestrian movement is of great significance in engineering practice. Therefore, understanding the variations in the natural frequency of bridge structures under varying positions of additional mass is of particular interest. This paper presents a procedure for the straightforward determination of the natural frequencies of a beam pedestrian bridge for various positions of pedestrians or a service vehicle based on derived analytical solutions. The calculation takes into account the inertial effects of the additional load mass, modeled as either uniformly distributed or concentrated. The importance of additional load mass effects on the fundamental frequency of a beam pedestrian bridge and its dynamic response to a moving pedestrian load is demonstrated on a bridge example. The proposed solutions are also applicable to other girder system structures with uniform mass and stiffness along their span.

Thunderstorm climatology of Slovakia between 1984–2023

Thunderstorms are among the most extreme meteorological phenomena that can cause widespread destruction and loss of life. Their occurrence varies significantly across different regions and times of the year. Despite various studies on thunderstorm activity across Central Europe, direct analyses based on data from the Slovak territory still need to be made available. Given Slovakia’s diverse natural conditions, there is a need for detailed knowledge about the frequency and spatial distribution of thunderstorms in this region. To address this knowledge gap, we analysed the frequency and spatiotemporal distribution of days with thunderstorm occurrences in Slovakia between 1984 and 2023, utilising climatological data from the Slovak Hydrometeorological Institute. We limited our analysis to data of days with close thunderstorms (thunderstorms occurring within 3 km of the monitoring station). Our findings reveal a significant variation in thunderstorm occurrences across Slovakia, with peak activity in the summer, especially in June and July. However, the spatial distribution of thunderstorms differed significantly across the country, with the highest frequency observed in mountainous regions and the east-central part of Slovakia. We found significant deceasing signals of the thunderstorm activity trends during the studied period, including analyses during the colder part of the year. Furthermore, our results underscore the critical role of synoptic situations in shaping these trends, where changes in certain atmospheric patterns were closely aligned with variations in thunderstorm frequency. The interaction between these synoptic conditions and regional topography was particularly evident, reinforcing the notion that topographical and environmental complexities substantially contribute to the observed thunderstorm distribution.

Identifying crystal nucleation mechanisms in a synthetic trachybasalt: a multimodal approach

To develop new criteria to distinguish different crystal nucleation mechanisms in silicate melts, we performed crystallization experiments using a synthetic hydrous (2 wt% H2O) trachybasalt and combined three-dimensional information from synchrotron X-ray computed microtomography with two-dimensional mapping of crystallographic orientation relationships (CORs) using electron backscatter diffraction. Crystallization experiments were performed at 400 MPa by cooling the melt from 1300 °C to resting temperatures of 1150 and 1100 °C and maintaining isothermal conditions for 30 min and 8 h. Three distinct titanomagnetite (Tmt) populations formed: (1) skeletal crystals, isolated or partially embedded in clinopyroxene (Cpx); (2) anhedral crystals, always attached to Cpx; (3) flattened needle-shaped crystals, embedded in Cpx. These morphologically different Tmt populations formed in response to one cooling event, with varying nucleation mechanisms and at different undercooling conditions. The clustered three-dimensional distribution of population 2 and 3 Tmt grains and the high proportion of Tmt-Cpx interfaces sharing CORs indicate that these Tmt grains heterogeneously nucleated on Cpx. The near-random three-dimensional distribution of (often isolated) population 1 Tmt grains, together with the low proportion of Tmt-Cpx interfaces sharing CORs, imply their isolated, possibly homogeneous nucleation, potentially followed by heterogeneous nucleation of Cpx on population 1 Tmt. Heterogeneous nucleation in slightly to moderately undercooled magmas should affect the sequence of crystallization as well as morphology and clustering of crystals, which may actively contribute to the variation of rheological parameters like viscosity. Finally, observed intra- and inter-sample variations in Tmt-Cpx COR frequencies indicate the potential for this parameter to record further petrological information.

Assessment the carrier frequency of monogenic diseases in populations requiring assisted reproductive technology

PurposeThe objective of this study is to assess the carrier frequency and pathogenic variation of monogenetic diseases in a population of 114 subjects in Han Chinese from Hebei province who are undergoing assisted reproductive technology through the utilization of Expanded Carrier Screening (ECS).MethodsThe study utilized a panel consisting of 155 severe monogenic recessive genetic diseases for ECS. Next-generation sequencing technology was employed to identify specific variants associated with ECS in a cohort of 114 subjects from 97 couples, comprising 97 females and 17 male spouses.ResultsA total of 114 individuals received ECS. The carrier rate of pathogenic genes in the enrolled population was 44.74% (51/114). Among the 97 females, the carrier rate of pathogenic genes was higher in those without assisted reproduction indicators than in those with assisted reproduction indicators (59.09% vs. 41.33%). However, the carrier rate of pathogenic genes in males without assisted reproductive technology was slightly lower than that with assisted reproductive technology (40% vs. 41.67%). Among both female and male participants, the carrier rate of pathogenic genes between individuals without indicators of assisted reproduction and those with such indicators was 55.55% vs. 41.38%. In 51 carriers, 72.55% (37/51) carried one genetic variant, 25.49% (13/51) carried two genetic variants, and 1.96% (1/51) carried three genetic variants. A total of 38 pathogenic genes were detected in this study, and GJB2 and MMACHC were most common. The carrier rates of the two genes were both 5.26% (6/114). A total of 55 variations were detected, and c.235delC was most frequently found. The carrier rate was 3.51% (4/114). The incidence of couples carrying the same pathogenic genes was 1.03% (1/97).ConclusionsThe findings elucidate the carrier rate of pathogenic genes among 155 severe monogenic recessive genetic diseases and underscore the significance of ECS as a preventive measure against congenital anomalies. When both partners carry the same genetic mutation for a monogenic disease, preventive strategies can be taken in offspring through preimplantation genetic testing (PGT), prenatal genetic testing, or the utilization of donor gametes. ECS is instrumental in assessing reproductive risk, guiding fertility-related decisions, and reducing the prevalence of monogenic recessive genetic disorders in subsequent generations.

Chaotic dynamics for homeostatic hematopoiesis.

Hematopoiesis is a highly dynamical and stochastic process, challenging our understanding of homeostasis. Clinical studies of leukemia or neutropenic patients revealed that multiple blood cell types fluctuate spontaneously with large yet regular oscillations of their frequencies. Yet the stability of hematopoiesis in healthy individuals remains understudied. Here we report on both cross-sectional and longitudinal studies of dozens of healthy mice, through high-dimensional mass and spectral cytometry, to understand hematopoiesis at homeostasis. We found that all cell types in the bone marrow, blood, and spleen exhibit large variations of frequency (e.g., with coefficients of variation larger than 1). While the frequencies of individual cell type fluctuate, there existed extensive and robust correlations/anti-correlations between cell types, exemplified by the pronounced anti-correlation between blood neutrophils and B cells. Through longitudinal study of the blood content of healthy mice, we found that leukocyte fluctuations are ergodic yet subject to chaotic behaviors characterized by a broad spectrum of characteristic timescales. We then built a minimal mathematical model to capture these dynamical features of hematopoiesis (fluctuations, correlations, and chaos) and explain how the accumulation of B cells (e.g. during lymphoma development) would transition the blood cell dynamics from chaos to oscillations (as observed clinically). Finally, we demonstrated the ubiquity and consistency of the correlated fluctuations in hematopoiesis by comparing mouse cohorts of different genetic backgrounds and ages. To conclude, we discuss how study of hematopoiesis must factor in the newfound chaotic dynamics at homeostasis, towards better modeling the responses to perturbations.

Romantic Love and Sexual Frequency: Challenging Beliefs

Common conceptions of romantic love suggest that romantic love is associated with increased sexual activity with more frequent sex in the earlier stages of a romantic relationship. To our knowledge, no studies have investigated individual-level factors and sexual frequency using a validated measure of romantic love. This study tested a number of hypotheses about the factors associated with sexual frequency among 720 sexually active young adults experiencing romantic love from the Romantic Love Survey 2022. We hypothesized that relationship duration, the intensity of romantic love and obsessive thinking about a loved one, commitment, and hypomanic-like features would be associated with sexual frequency. Using hierarchical linear regression, controlling for known covariates, we found no significant associations between any of our variables of interest and the sexual frequency and our entire model of 14 well-reasoned predictors explained only 4.06% of the variation in sexual frequency. The findings are surprising and highlight how little is currently known about sexual activity and sexual desire among individuals experiencing romantic love.

Sensing performance of Schiff base-calix[4]arene including amide units for detection of pharmaceutically active compounds on QCM sensor system

This study aimed to investigate the sensing performance of a Quartz Crystal Microbalance (QCM) sensor coated with a calix[4]arene derivative (calixarene phenol amide, CPhA), containing both Schiff base and amide groups against various pharmaceutically active compounds (PhACs) such as ibuprofen, diphenhydramine, naproxen, and ascorbic acid in aqueous media. CPhA was successfully coated on the QCM crystal surface, and its surface properties were studied using Atomic Force Microscopy (AFM) and contact angle measurements. Sensing studies showed that the CPhA-coated QCM sensor detected more PhACs than the compound 4 (unfunctionalized derivative)-coated sensor. The highest frequency variation and binding ratio values were achieved with the QCM sensor with a relatively low coating amount. The CPhA-coated QCM sensor achieved higher adsorption capacity and was significantly more sensitive to all PhACs than the compound 4-coated one. The fabricated sensor showed remarkable reproducibility for all PhACs except naproxen (NAP). The fabricated sensor exhibited a remarkable sensing performance for detecting PhACs, which is promising for developing novel calix[4]arene-coated QCM sensors for PhACs.

Dynamic Formation of a Posterior-to-Anterior Peak-Alpha-Frequency Gradient Driven by Two Distinct Processes.

Peak-alpha frequency varies across individuals and mental states, but it also forms a negative gradient from posterior to anterior regions in association with increases in cortical thickness and connectivity, reflecting a cortical hierarchy in temporal integration. Tracking the spatial standard deviation of peak-alpha frequency in scalp EEG, we observed that a posterior-to-anterior gradient dynamically formed and dissolved. Periods of high spatial standard deviation yielded robustly negative posterior-to-anterior gradients-the "gradient state"-while periods of low spatial standard deviation yielded globally converged peak-alpha frequency-the "uniform state." The state variations were characterized by a combination of slow (0.3-0.5 Hz) oscillations and random-walk-like fluctuations. They were relatively independently correlated with peak-alpha frequency variations in anterior regions and peak-alpha power variations in central regions driven by posterior regions (together accounting for ∼50% of the state variations), suggesting that two distinct mechanisms modulate the state variations: an anterior mechanism that directly adjusts peak-alpha frequencies and a posterior-central mechanism that indirectly adjusts them by influencing synchronization. The state variations likely reflect general operations as their spatiotemporal characteristics remained unchanged while participants engaged in a variety of tasks (breath focus, vigilance, working memory, mental arithmetic, and generative thinking) with their eyes closed or watched a silent nature video. The ongoing state variations may dynamically balance two global processing modes, one that facilitates greater temporal integration (and potentially also information influx) toward anterior regions in the gradient state and the other that facilitates flexible global communication (via phase locking) in the uniform state.

Analysis of the periodic variation of pellet ablation radiation intensity in ASDEX Upgrade

Abstract In a future fusion reactor, the main fuelling method will likely rely on the injection of solid hydrogen pellets. Current predictions assume that this goal can be achieved, since being based on a technology which is already largely developed. However, this belief is founded on modelling tools that are usually aligned to the observation made in existing devices and then extrapolated to reactor conditions. This approach needs a sound consideration of its intrinsic restrictions and any observed feature not reproduced by the utilised codes should be applied to check their validation and possibly contribute to their refinement. One specific feature still lacking an explanation of a reasonable and self-consistent mechanism in the current models is the appearance of a phenomenon called striations, which are high frequency variations in the radiation emitted during the pellet ablation process. In order to provide a sound and reliable database for further considerations, a dedicated analysis of this effect has been performed on the mid-size tokamak ASDEX Upgrade. Therefore, such cases have been selected with the relevant signal recorded with sufficient temporal resolution during experiments covering a wide variation of plasma and pellet parameters which are regarded to be potentially influential on the striation pattern. In addition, it was ensured that for any specific case the observed behaviour was reproducible for several individual ablation events under identical conditions. In all cases considered, the observed radiation-intensity variations appear with a typical pattern showing a broad peak of frequencies in the range 50 to 150 kHz. This characteristic unveils a notable resilience against any parameter variation. This new collection of data can now act as firm basis to corroborate future modelling code-validation efforts. In addition, the analysis method can provide a relatively simple way of reviewing future modelling predictions.

Uncertainty quantification for natural frequency and mode of variable angle tow composite plates with random and interval uncertainties

Variable angle tow (VAT) composite laminated structures are produced by automated tow-placement technology which can take advantage of the designability of composites to meet the aerospace industry’s need for dynamic properties. Complex production techniques inevitably lead to uncertainties in material properties due to manufacturing defects. The aim of this work is to present an efficient computational method for estimating the dynamical properties of VAT composite laminated plates due to multiscale hybrid uncertainties. This method consists of perturbation stochastic finite element method and particle swarm optimization combined with Mori-Tanaka homogenization. The degree of influence of the multiscale parameters on the dynamic properties of VAT composites with different structural forms has been obtained by sensitivity analyses of the frequency and mode. The method is applied to investigate variations in natural frequency and mode of a variety of VAT composite laminated plates with different fiber tow paths, layers, and boundary conditions. The results indicate that variations in natural frequencies and mode shapes are strongly linked to fiber tow paths and boundary conditions. The frequency and modes of the VAT show a nonlinear variation with angle. This method can quickly obtain the probability distribution intervals of the frequency, which is of great significance for assessing the reliability of VAT composites laminated plates dynamic designs.

Structural and optical studies of copper doped zinc oxide thin films synthesized by co-precipitation method

This study presents the fabrication and characterization of pure and copper doped zinc oxide (Cu-doped ZnO) thin films with varying copper concentrations. The films were synthesized using co-precipitation and spin coating methods, followed by post-annealing at 450 °C for 6 h in ambient air. Structural and optical properties of the samples were analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) spectroscopy, ultraviolet–visible (UV–Vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and Raman spectroscopy. Structural analysis revealed a decrease in average crystalline size up to 2 wt% copper doping, followed by an increase with higher doping concentrations. SEM micrographs supported these findings. The band gap of the samples narrowed with increasing copper doping, from approximately 3.22 eV for pure ZnO to 2.72 eV for the 6 wt% copper doped sample. Furthermore, frequency variations in the 400–600 cm−1 wavelength interval were observed in the FTIR vibrational bands of zinc oxide due to increasing copper doping.