Non-steady States Research Articles

Model of Dynamic Mechanical Parameters and Vibration Analysis in Hot Rolling

As the core equipment of metal shaping processing, the vibration problem of rolling mill seriously affects the product quality and production efficiency. To address the problem of the limited prediction of mill vibration due to small sample data in non-steady states, we propose to predict dynamic mechanical parameters (rolling force and rolling torque) based on the TCN-LSTM step strategy transfer model. The prediction accuracies of the TCN-LSTM step strategy transfer model under 1000 sets of training data reach 95.8% and 93.2%, respectively, and at the same time, it saves the time of training and regulation of the deep learning model and can better meet the needs of online prediction. The horizontal-torsion hot rolling vibration model is further established to quantitatively analyze the relationship between process parameters and mill vibration. The experimental results show that with the vibration suppression measures of 10% reduction of the rolling speed and 10% reduction of the entrance thickness, the horizontal vibration displacement amplitude is reduced from 0.687 × 10−4 m to 0.229 × 10−4 m, and the rotational displacement amplitude is reduced from 0.0273 m to 0.0117 m, which effectively suppresses the vibration of the mill and improves the stability of the rolling process.

Numerical Thermo-Hydraulic Simulation of Infiltration and Evaporation of Small-Scale Replica of Typical Dike Covers

Measurements taken on a historical dike in the Netherlands over one year showed that interaction with the atmosphere led to oscillation of the piezometric surface of about 0.7 m. The observation raised concerns about the long-term performance of similar dikes and promoted a deeper investigation of the response of the cover layer to increasing climatic stresses. An experimental and numerical study was undertaken, which included an investigation in the laboratory of the unsaturated behavior of a scaled replica of the field cover. A sample extracted from the top clayey layer in the dike was subjected to eight drying and wetting cycles in a HYPROP™ device. Data recorded during the test provide an indication of the delayed response with depth during evaporation and infiltration. The measurements taken during this continuous dynamic process were simulated by means of a finite element discretization of the time-dependent coupled thermohydraulic response. The results of the numerical simulations are affected by the way in which the environmental loads are translated into numerical boundary conditions. Here, it was chosen to model drying considering only the transport of water vapor after equilibrium with the room atmosphere, while water in the liquid phase was added upon wetting. The simulation was able to reproduce the water mass balance exchange observed during four complete drying–wetting cycles, although the simulated drying rate was faster than the observed one. The numerical curves describing suction, the amount of vapor and temperature are identical, confirming that vapor generation and its equilibrium is control the hydraulic response of the material. Vapor generation and diffusion depend on temperature; therefore, correct characterization of the thermal properties of the soil is of paramount importance when dealing with evaporation and related non-steady equilibrium states.

Decoding aging and cognitive functioning through spatiotemporal EEG patterns: Introducing spatiotemporal information-based similarity analysis.

Exploring spatiotemporal patterns of high-dimensional electroencephalography (EEG) time series generated from complex brain system is crucial for deciphering aging and cognitive functioning. Analyzing high-dimensional EEG series poses challenges, particularly when employing distance-based methods for spatiotemporal dynamics. Therefore, we proposed an innovative methodology for multi-channel EEG data, termed as Spatiotemporal Information-based Similarity (STIBS) analysis. The core of this method is to first perform state space compression of multi-channel EEG time series using global field power, which can provide insight into the dynamic integration of spatiotemporal patterns between the steady states and non-steady states of brain. Subsequently, we quantify the pairwise differences and non-randomness of spatiotemporal patterns using an information-based similarity analysis. Results demonstrated that this method holds the potential to serve as a distinguishing marker between young and elderly on both pairwise differences and non-randomness indices. Young individuals and those with higher cognitive abilities exhibit more complex macrostructure and non-random spatiotemporal patterns, whereas both aging and cognitive decline lead to more randomized spatiotemporal patterns. We further extended the proposed analytics to brain regions adversarial STIBS (bra-STIBS), highlighting differences between young and elderly, as well as high and low cognitive groups. Furthermore, utilizing the STIBS-based XGBoost model yields superior recognition accuracy in aging (93.05%) and cognitive functioning (74.29%, 64.19%, and 80.28%, respectively, for attention, memory, and compatibility performance recognition). STIBS-based methodology not only contributes to the ongoing exploration of neurobiological changes in aging but also provides a powerful tool for characterizing the spatiotemporal nonlinear dynamics of the brain and their implications for cognitive functioning.

Near-Field Probing of Microwave Oscillators with Josephson Microscopy.

Voltage-controlled oscillators, serving as fundamental components in semiconductor chips, find extensive applications in diverse modules such as phase-locked loops, clock generators, and frequency synthesizers within high-frequency integrated circuits. This study marks the first implementation of superconducting Josephson probe microscopy for near-field microwave detection on multiple voltage-controlled oscillators. Focusing on spectrum tracking, various phenomena, such as stray spectra and frequency drifts, were found under nonsteady operating states. Parasitic electromagnetic fields, originating from power supply lines and frequency divider circuits, were identified as sources of interference between units. The investigation further determined optimal working states by analyzing features of the microwave distributions. Our research not only provides insights into the optimization of circuit design and performance enhancement in oscillators but also emphasizes the significance of nondestructive near-field microwave microscopy as a pivotal tool in characterizing integrated millimeter-wave chips.

Dual-FBG arrays hybrid measurement technology for mechanical strain, temperature, and thermal strain on composite materials

The response measurement of spacecraft during reentry is very important for designing the base composite structure. This paper proposes a hybrid measurement method to measure the mechanical strain, the temperature, and the thermal strain using dual fiber Bragg grating (FBG) arrays. The decoupling of temperature and stain is illustrated by a three-step process such that triple physical variables are measured simultaneously. For the base composite structure, four heating scenarios with thermal steady and non-steady states encountered during the lifting re-entry were designed to illustrate the feasibility of the proposed method. Under the thermal non-steady state, the average absolute error of the temperature measured by the dual-FBG and the thermocouple did not exceed 2.799 K. Meanwhile, the dual FBG-based thermal strain was compared with the thermally measured strain with an average relative error of no more than 2.913%. A finite element model at different temperatures was developed to calculate mechanical responses and was compared with the results obtained by FBG. The results show significant agreement between the measurement and the simulation, with a maximum error of 3.61%.

Recent Development of Air Gauging in Industry 4.0 Context.

The paper presents a review of the research reports published in 2012-2022, dedicated to air gauging. Since most of the results are somehow related to Industry 4.0 concept, the review put the air gauging to the context of fourth industrial revolution. It was found that despite substantial decrease of the number of published papers in recent years, the investigations are still performed to improve air gauges, both in static and in non-steady states. Researchers paid attention to the digitization of the results, models and simulations, uncertainty estimation, calibration, and linearization. Specific applications covered real-time monitoring and in-process control, as well as form and surface topography measurements. Proposed solutions for integration with computer systems seem suitable for the air gauges be included to the sensor networks built according to the Industry 4.0 concept.

Housekeeping and excess entropy production for general nonlinear dynamics

We propose a housekeeping/excess decomposition of entropy production for general nonlinear dynamics in a discrete space, including chemical reaction networks and discrete stochastic systems. We exploit the geometric structure of thermodynamic forces to define the decomposition; this does not rely on the notion of a steady state, and it even applies to systems that exhibit multistability, limit cycles, and chaos. In the decomposition, distinct aspects of the dynamics contribute separately to entropy production: the housekeeping part stems from a cyclic mode that arises from external driving, generalizing Schnakenberg's cyclic decomposition to nonsteady states, while the excess part stems from an instantaneous relaxation mode that arises from conservative forces. Our decomposition refines previously known thermodynamic uncertainty relations and speed limits. In particular, it not only improves an optimal-transport-theoretic speed limit, but it also extends the optimal transport theory of discrete systems to nonlinear and nonconservative settings.

Anisohydric characteristics of a rice genotype 'ARC 11094' contribute to increased photosynthetic carbon fixation in response to high light.

Photosynthetic induction, which is the response of the CO2 assimilation rate to a stepwise increase in light intensity, potentially affects plant carbon gain and crop productivity in field environments. Although natural variations in photosynthetic induction are determined by CO2 supply and its fixation, detailed factors, especially CO2 supply, are unclear. This study investigated photosynthesis at steady and non-steady states in three rice (Oryza sativa L.) genotypes: ARC 11094, Takanari and Koshihikari. Stomatal traits and water relations in the plants were evaluated to characterise CO2 supply. Photosynthetic induction in ARC 11094 and Takanari was superior to that in Koshihikari owing to an efficient CO2 supply. The CO2 supply in Takanari is attributed to its high stomatal density, small guard cell length and extensive root mass, whereas that in ARC 11094 is attributed to its high stomatal conductance per stoma and stomatal opening in leaves with insufficient water (i.e., anisohydric stomatal behaviour). Our results suggest that there are various mechanisms for realising an efficient CO2 supply during the induction response. These characteristics can be useful for improving photosynthetic induction and, thus, crop productivity in field environments in future breeding programmes.

Steady-State Data Baseline Model for Nonstationary Monitoring Data of Urban Girder Bridges

In bridge structural health monitoring systems, an accurate baseline model is particularly important for identifying subsequent structural damage. Environmental and operational loads cause nonstationarity in the strain monitoring data of urban girder bridges. Such nonstationary monitoring data can mask damage and reduce the accuracy of the established baseline model. To address this problem, a steady-state data baseline model for bridges is proposed. First, for observable effects such as ambient temperature, a directional projection decoupling method for strain monitoring data is proposed, which can reduce the nonstationary effect of ambient temperature, and the effectiveness of this method is proven using equations. Second, for unobservable effects such as traffic load, a k-means clustering method for steady state of traffic loads is proposed; using this method, which can divide the steady and nonsteady states of traffic loads and reduce the nonstationary effect of traffic loads on strain monitoring data, a steady-state baseline model is established. Finally, the effectiveness of the steady-state baseline model is verified using an actual bridge. The results show that the proposed baseline model can reduce the error caused by nonstationary effects, improve the modelling accuracy, and provide useful information for subsequent damage identification.

A study of process-induced grain structures during steady state and non-steady state electron-beam welding of a titanium alloy

• Steady and non-steady state sections have different weld pool geometries. • Significant difference in cooling rates experienced in the steady and non-steady state sections. • Similar microstructures and textures were observed, while grain sizes are largely varied in steady and non-steady state sections. • Different states lead to a significant difference in measured porosity. • The use of electron beam welding significantly affected the performance of joints. A detailed microstructural characterisation of the emerging weld-line grain structure, for bead-upon-plate welds in Ti-6Al-4V (Ti64) of differing plate thickness, was performed. The microstructure studied was formed during both steady state and non-steady state sections within the weld path, with the non-steady state portion being taken from the end of the plate as the weld bead and heat source overhang the edge of the plate. This allows for the effects of welding process conditions on the microstructural evolution to be determined. The weld pool geometry and 3D tomography of the weld-induced defects have been investigated. Detailed characterisation of microstructure and texture for different welding parameters and for steady and non-steady states have been used to identify physical parameters for the microstructure predictions that are difficult to obtain otherwise. The different states significantly affect the weld crown shape and formation, weld toe, weld bead depth and width. However, the heat affected zone (HAZ) remains unchanged. Regarding the microstructural evolution, both the steady and non-steady states have similar microstructure and texture. No defects were observed in the steady state section of welds, but sub-surface spherical pores have been observed in the non-steady state section of a weld. Finite element modelling to simulate the thermal-metallurgical-mechanical fields within the steady and non-steady state sections of the welds was considered, and the cooling rates predicted within steady state and non-steady sections were interrogated to improve the theoretical understanding of the microstructure and defect formation differences in these Ti64 EB weld regions.

Design of Electrohydrodynamic Devices with Consideration of Electrostatic Energy.

The importance of actuators that can be integrated with flexible robot structures and mechanisms has increased in recent years with the advance of soft robotics. In particular, electrohydrodynamic (EHD) actuators, which have expandable integrability to adapt to the flexible motion of soft robots, have received much attention in the field of soft robotics. Studies have deepened the understanding of steady states of EHD phenomena but nonsteady states are not well understood. We herein observe the development process of fluid in a microchannel adopting a Schlieren technique with the aid of a high-speed camera. In addition, we analyze the behavior of fluid flow in a microchannel that is designed to have pairs of parallel plate electrodes adopting a computational fluid dynamics technique. Results indicate the importance of considering flow generated by electrostatic energy, which tends to be ignored in constructing and evaluating EHD devices, and by the body force generated by the ion-drag force. By considering these effects, we estimate the development process of EHD flow and confirm the importance of considering the generation of vortices and their interactions inside the microchannel during the development of EHD devices.

Nonequilibrium thermal transport and thermodynamic geometry in periodically driven systems

With the in-depth understanding of nano-/micro-scaled systems and the developing of the corresponding experimental techniques, the heat transport and energy conversion processes in these small systems have attracted much interest recently. In contrast to the static manipulation methods, which hinge on the steady nonequilibrium sources such as temperature bias, chemical potential difference, etc., the temporal driving methods can control small systems in nonequilibrium non-steady states with much more versatility and universality. The research on periodically driven small systems holds both fundamental and pragmatic promises. This review is based on the fundamental concept of geometry. By analyzing the geometric phase and thermodynamic length in the transport process and the energy conversion process, we provide a unified perspective for the recent researches on the thermodynamic properties of driven nonequilibrium quantum systems. Thermodynamic geometry not only is the intrinsic origin of the nontrivial transport and dissipation, but also provides us with an all-applicable theoretical framework. The discussion over the geometry would yield multiple thermodynamic constraints on the transport and energy conversion, and can naturally construct a general optimization method as well. This will conduce to a better understanding of functionality for nonequilibrium quantum many-body systems acting as thermal machines. Also, this will inspire people to design quantum thermal machines with simultaneously more ideal performance, i.e. higher efficiency, higher power and higher constancy.

An energy time-convexity second-order synchrosqueezing transform and application in weak fault diagnosis of rolling bearings in an aerospace engine

Although the original short-time Fourier-transform-based synchrosqueezing transform (FSST) and its second-order transform (FSST2) can effectively improve the readability of quasi-stationary signal and time-varying signal, respectively, the weak components of time–frequency representation are often submerged easily by noises and large-amplitude instantaneous frequencies (IFs). Moreover, aerospace engines always work in fierce vibration and non-steady states, and this easily causes the weak fault feature of rolling bearings obscured in the time–frequency domain. To solve this problem, we propose a time–frequency analysis algorithm called energy time-convexity second-order synchrosqueezing transform (ET-FSST2). This can sharpen the time-varying IFs like FSST2, and more importantly, it can extract the time-varying IFs with small amplitudes such as weak impulse-like components from multi-component vibration signals. The ET-FSST2 firstly calculates the energy convexity function in the time direction to extract the non-stationary IFs after employing FSST2. It then structures an optimization function by combining a hyperbolic tangent function with a chi-square distribution function as well as optimizing the targeted parameters, aiming to extract the weak components of the non-stationary IFs. Moreover, the effectiveness and robustness of the proposed method are validated by numerical simulation and rolling bearing fault tests. Finally, two case studies of weak fault diagnosis of Ni–Cu–Ag-based PVD-coated rolling bearings operating in cryogenic surroundings are given to illustrate the effectiveness of the proposed method for aerospace engine bearing fault diagnosis.

Thermodynamic Uncertainty Relation for Arbitrary Initial States.

The thermodynamic uncertainty relation (TUR) describes a trade-off relation between nonequilibrium currents and entropy production and serves as a fundamental principle of nonequilibrium thermodynamics. However, currently known TURs presuppose either specific initial states or an infinite-time average, which severely limits the range of applicability. Here we derive a finite-time TUR valid for arbitrary initial states from the Cramér-Rao inequality. We find that the variance of an accumulated current is bounded from below by the instantaneous current at the final time, which suggests that "the boundary is constrained by the bulk". We apply our results to feedback-controlled processes and successfully explain a recent experiment which reports a violation of a modified TUR with feedback control. We also derive a TUR that is linear in the total entropy production and valid for discrete-time Markov chains with nonsteady initial states. The obtained bound exponentially improves the existing bounds in a discrete-time regime.

The migration and diffusion of unsteady-state VOCs flow on activated carbon adsorption beds

ABSTRACT Traditionally, in engineering applications, VOC (volatile organic compound) emissions are usually under non-steady states due to intermittent emissions and concentration fluctuations, which adversely affects the stable and reliable operation of many existing purification systems and may constitute a safety hazard. However, previous studies on VOC adsorption by adsorbents have mostly focused on the adsorption performance and properties of different modified adsorbents. Few studies of VOC adsorption have focused on adsorption or movement for unsteady-state VOCs using activated carbon adsorption beds. This study investigated three common and important factors (load time ratio, load mode and no-load flow rate) that affect the adsorption of unsteady-state VOCs by activated carbon. This allowed the migration and movement of VOCs between activated carbon adsorption beds under different factors to be analyzed, which provides important insights in understanding VOC adsorption and can promote the development of homogeneous buffering technology for non-steady state VOCs. In addition, this information provides support for the development of pollution control processes for tidal VOCs discharge airflows that result from storage and transportation operations, and also provides parameters that could support practical applications of activated carbon to adsorb unsteady-state VOCs.

Optimal temperature estimation for a XXZ spin-1 2 chain coupled locally to independent thermal baths

Temperature as an environmental parameter influences the evolution of an open quantum system. In detail, temperature lies in Lindblad operator of quantum master equation that the evolution of an open quantum system follows. Hence, one can implement a temperature estimation of thermal baths through a measurement of quantum Fisher information about temperature brought from quantum states. Such a method by calculating quantum Fisher information about a parameter to estimate its value avoids measuring the parameter directly and it does not change the value of the parameter due to making measurements. In this paper, we consider a model consisting of a XXZ spin-[Formula: see text] chain coupled locally to independent thermal baths with different temperature. Based on the model, we investigate optimal temperature estimation for thermal baths with respect to an open quantum system subjected to non-steady states. We first study optimal probe time for temperature estimation in the case of non-steady states and find that the optimal time shows different features for different types of system variables. It proves that in a certain duration there exists a tradeoff between the trial times and the attaining amount of Fisher information in each trial. In addition, we pay attention to an issue on optimal probe states. We demonstrate that in many cases the optimal states are not always the maximally entangled states and even maybe the separable states, which is related with the measuring time, system couplings.

Trait-space patterning and the role of feedback in antigen-immunity coevolution

Coevolutionary arms races form between interacting populations that constitute each other's environment and respond to mutual changes. This inherently far-from-equilibrium process finds striking manifestations in the adaptive immune system, where highly variable antigens and a finite repertoire of immune receptors coevolve on comparable timescales. This unique challenge to the immune system motivates general questions: How do ecological and evolutionary processes interplay to shape diversity? What determine the endurance and fate of coevolution? Here, we take the perspective of responsive environments and develop a phenotypic model of coevolution between receptors and antigens that both exhibit cross-reactivity (one-to-many responses). The theory predicts that the extent of asymmetry in cross-reactivity is a key determinant of repertoire composition: small asymmetry supports persistent large diversity, whereas strong asymmetry yields long-lived transients of quasispecies in both populations. The latter represents a new type of Turing mechanism. More surprisingly, patterning in the trait space feeds back on population dynamics: spatial resonance between the Turing modes breaks the dynamic balance, leading to antigen extinction or unrestrained growth. Model predictions can be tested via combined genomic and phenotypic measurements. Our work identifies cross-reactivity as an important regulator of diversity and coevolutionary outcome, and reveals the remarkable effect of ecological feedback in pattern-forming systems, which drives evolution toward non-steady states different than the Red Queen persistent cycles.

Winter CO2 emission and its production rate in cold temperate soils of northern Japan: 222Rn as a proxy for the validation of CO2 diffusivity

In the context of a changing seasonal snow-covered period and extent in northern high latitude regions, winter CO2 emissions are vulnerable to drastic climate change, prompting rigorous evaluation of regional carbon budgets. The significance of winter CO2 contributions to the atmosphere in these regions has likewise been recognized. In this study, concentrations of CO2 and 222Rn were observed in the snowpack and underlying cold temperate soils of northern Japan during two winter seasons. Winter CO2 emissions, estimated alternately by snow density, 222Rn tracer (under steady and non-steady states), and chamber, were 56 ± 2, 42 ± 6, 44 ± 15, and 34 ± 3 gCO2-C/m2/season, respectively, suggesting that contribution from average winter CO2 emission corresponds to 25% (range: 19–33%) of annual emission. Winter CO2 emission is highly regulated by soil temperature at 5 cm, depending on snow depth. Winter CO2 emission transport is not suppressed through the snowpack to the atmosphere; rather it is stimulated when seasonal snow depth is over the 40-cm threshold in the soils. The higher soil CO2 production of 0.11 ± 0.02 gCO2-C/m3/h estimated by 222Rn transfer velocity reflects vigorous microbial activity in soils underlying winter snowpack. Therefore, 222Rn is an important proxy for the estimation of winter CO2 emission and diffusivity in snowpack, and of CO2 production rate and transfer velocity in the seasonal, snow-covered.

Influence of diffusion and deposition processes on the electrochemical formation of gold amalgam

In this study, gold amalgam was prepared on a gold nanorods (Au Rs) modified ITO electrode through an electrochemical reduction of mercury ions (Hg2+), and the formation of amalgam was explored under steady and non-steady states. Under static system, Hg2+ was preferentially deposited at the tips of the Au NRs, and diffused along the Au NRs, because of the electrodeposition rate of Hg2+ was higher than the diffusion rate of Hg2+ in the electrolyte. Under disturbed condition, based on the continuous supply of Hg2+, mercury was gradually reduced and swelled into the interior of Au NRs leading to the formation of nanospheres. UV–vis absorption spectroscopy, transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM) were utilized to demonstrate the reaction processes. This study might be able to provide the experimental basis for the preparation of bimetallic nanoalloys.

Frequency estimation and tracking by two-layered iterative DFT with re-sampling in non-steady states of power system

Frequency deviation off the nominal one is incurred by sudden changes of frequency and could introduce harmonics and inter-harmonics in the power system, which influences the accuracy of frequency estimation with method of discrete Fourier transform (DFT). A two-layered iterative DFT (TLI-DFT) with re-sampling was presented to measure the frequency in non-steady states. A simple frequency estimation method named exponential sampling is amended to calculate the initial sampling frequency in the inner-layered process of the DFT iteration. In reality, frequencies of two consecutive cycles are always interrelated with each other, so an idea of frequency tracking by outer-layered DFT between cycles is adopted. TLI-DFT can track the frequency in non-steady state in different scenarios, e.g., sudden and random frequency change, signal modulated by a cosine signal, and contaminated by decaying direct current offsets. Mean squared error of measured frequency, rate of change of frequency, and total vector error at different transient conditions indicate that the proposed algorithm is valid and more accurate than the traditional one in the non-steady states of a power system.