Transient Phenomena Research Articles

Transient Phenomena of Inviscid Accretion Gasradiation Slim Disc in A Gravitational Potential after Adiabatic Perturbations of the Velocities

The formalisms for the analysis of the dynamics of slim inviscid accretion discs in a (also, non-Newtonian) gravitational potential are here developped; the role of the horizontal pressure and that of the entropy gradients are to be characterised. The adiabatic perturbations of the velocity are studied: the paradigms of the Lagrangian perturbations of the velocity are implemented. The perturbations of the slim disc is studied in the Lagrangean formalism of adiabatic perturbations of the velocities. The new conditions on the Eulerian variation of the gravitational potential are outlined. The equations of the transient phenomena are written.

Deep learning based hybrid POD-LSTM framework for laminar natural convection flow in a rectangular enclosure

Abstract Laminar natural convection in side-heated enclosures is characterized by transient phenomena of the working fluid till it reaches steady state. The side heating can done in several ways the most common way being heating one end at constant temperature and cooling the other end. One of the other ways is heating both sides of the enclosure at a constant heat flux. Mathematical modeling of such problems using Computational Fluid Dynamics (CFD) essentially involves considerable amount of computational time and power to predict the flow phenomena observed in actual experimentation. In the last few years, data driven model frameworks have proven to be anefficient way in saving both time and computational cost in several applications. In the present study, a data driven model framework using a combination of unsupervised machine learning (using Proper Orthogonal Decomposition [POD]) and supervised deep learning models (using Long Short Term Memory [LSTM]) has been developed and referred to as POD-LSTM framework. The selection of a few dominant spatial bases and accompanying temporal modes provides us with a reduced order model of the system. The flow is then reconstructed and compared with results of CFD simulations. The Rayleigh number (Ra) chosen for the study is 3.27 × 1010. The estimated time to reach stedy state for this Ra number is 15,000 s. The POD-LSTM framework is trained using data obtained from a validated CFD model for the first 1,000 s. The trained model was then tested to predict temporal dynamics for the entire 15,000 s. The predictions provided by POD-LSTM framework were found upto 98 % accurate compared to the ones predicted by CFD. The computational time and power was however an order of magnitude lower for the POD-LSTM framework than that required for the CFD model.

Ultrafast carrier dynamics and transient nonlinear absorption in chalcogenide perovskite BaZrS3

The unique combination of excellent semiconducting properties in halide perovskites and the high stability and nontoxicity of oxide perovskites has led to a recent surge in interest in chalcogenide perovskite BaZrS3 for optoelectronic applications. However, to realize its potential in future device technologies, a comprehensive understanding of photoexcited carrier dynamics and transient optical response is imperative, yet it remains largely unexplored for BaZrS3. In this work, employing transient absorption spectroscopy, we have revealed that photoexcited carriers in epitaxial BaZrS3 nanofilms exhibit two exponential decay components relating to optical phonon cooling and interband recombinations. Meanwhile, our investigation unveils an intriguing transient nonlinear absorption phenomenon in BaZrS3, characterized by the ultrafast switching of the pump-induced transparency (i.e., the saturable absorption) to the absorption enhancement within a timescale commensurate with the measurement resolution (hundreds of femtosecond). This study provides crucial dynamic insights essential for leveraging chalcogenide perovskites, such as BaZrS3, in the development of advanced optoelectronic devices.

Layout optimization and Performance of Large Array of imaging atmospheric Cherenkov Telescope (LACT)

Abstract Large Array of imaging atmospheric Cherenkov Telescope (LACT) is an array of 32 Cherenkov telescopes with 6-meter diameter mirrors to be constructed at the LHAASO site. In this work, we present a study on the layout optimization and performance analysis of LACT. We investigate two observation modes: large zenith angle observations for ultra-high energy events and small zenith angle observations for lower energy thresholds. For large zenith angles (60°), simulations show that an 8-telescope subarray can achieve an effective area of $3 ~\rm km^2$ and excellent angular resolution. For small zenith angles, we optimize the layout of 4-telescope cells and the full 32-telescope array. The threshold of the full array is about $200~\rm GeV$, which is particularly crucial for studying transient phenomena, including gamma-ray bursts (GRBs) and active galactic nuclei (AGNs). This study provides important guidance for the final LACT layout design and performance estimates under different observational conditions, demonstrating LACT's potential for deep observations of ultra-high energy \gray sources and morphological studies of PeVatrons, as well as time-domain \gray astronomy.

Insight HXMT and GECAM joint observation of time domain astronomy from cosmic outbursts

Abstract The field of time-domain astronomy focuses on the observation of temporal variations in celestial phenomena, in particular gamma-ray bursts (GRBs). It emphasized the importance of monitoring transient events and phenomena, which occurred on different time scales, ranging from milliseconds to years. This paper also explained the properties of X-rays and Gamma-rays, their sources and the significance of studying them for understanding the dynamic nature of the universe. The collaboration between the Insight HXMT and GECAM missions was designed to detect and study high-energy astronomical events, such as those associated with black holes and neutron stars, and to provide for rapid data transmission and dissemination of astronomical alerts. By combining observations from the two instruments, researchers can gain a more comprehensive understanding of cosmic phenomena and explore the fundamental physics of the universe.

Investigation of the transient characteristics of the Francis turbine during runaway process

Transient hydraulic phenomena, including flow separation, vortex structure and high amplitude pressure fluctuation, occur in the turbine during runaway process, significantly affecting the safe and stable operation. To clarify the unsteady flow characteristics in the runaway process, this paper focus on a low head model Francis turbine, examining the transient flow dynamics from rated speed to runaway speed. Numerical simulations show good agreement with experimental test results for the runaway speed and discharge. Results identify that two typical cavitation vortex structures within the runner: A cloud cavitation vortex near the hub on the pressure side and a columnar cavitation vortex on the suction side. Further analysis reveals that the pressure fluctuation induced by the former are low-frequency (0.08fn and harmonics), whereas those induced by the latter are high-frequency (1.16fn and harmonics). Entropy production analysis in homogeneous flow indicates that energy dissipation mainly occurs in the runner and draft tube during the runaway process. Turbulent entropy production within the turbine comprises a significant portion of the total entropy production. Additionally, areas around the recirculation zone exhibit considerable high entropy production, indicating that the energy of the fluid is dissipated by cavitation vortex structures generated in these areas. Additionally, the analysis indicates that the entropy production rate correlates with vapor generation, underscoring the cavitation vortex as the primary cause of energy dissipation. This investigation can provide valuable insights into the energy dissipation mechanisms during the runaway process.

Expected insights into Type Ia supernovae from LISA’s gravitational wave observations

The nature of progenitors of Type Ia supernovae has long been debated, primarily due to the elusiveness of the progenitor systems to traditional electromagnetic observation methods. We argue that gravitational wave observations with the upcoming Laser Interferometer Space Antenna (LISA) offer the most promising way to test one of the leading progenitor scenarios – the double-degenerate scenario, which involves a binary system of two white dwarf stars. In this study we review published results, supplementing them with additional calculations for the context of Type Ia supernovae. We discuss the fact that LISA will be able to provide a complete sample of double white dwarf Type Ia supernova progenitors with orbital periods shorter than 16–11 minutes (gravitational wave frequencies above 2–3 millihertz). Such a sample will enable a statistical validation of the double-degenerate scenario by simply counting whether LISA detects enough double white dwarf binaries to account for the measured Type Ia merger rate in Milky Way-like galaxies. Additionally, we illustrate how LISA’s capability to measure the chirp mass will set lower bounds on the primary mass, revealing whether detected double white dwarf binaries will eventually end up as a Type Ia supernova. We estimate that the expected LISA constraints on the Type Ia merger rate for the Milky Way will be 4–9%. We also discuss the potential gravitational wave signal from a Type Ia supernova assuming a double-detonation mechanism and explore how multi-messenger observations could significantly advance our understanding of these transient phenomena.

Observation of super-Alfvénic slippage of reconnecting magnetic field lines on the Sun

AbstractSlipping motions of magnetic field lines are a distinct signature of three-dimensional magnetic reconnection, a fundamental process driving solar and stellar flares. While being a key prediction of numerical experiments, the rapid super-Alfvénic field line slippage driven by the ‘slip-running’ reconnection has remained elusive in previous observations. New frontiers into exploring transient flare phenomena were introduced by recently designed high cadence observing programs of the Interface Region Imaging Spectrograph (IRIS). By exploiting high temporal resolution imagery (~2 s) of IRIS, here we reveal slipping motions of flare kernels at speeds reaching thousands of kilometres per second. The fast kernel motions are direct evidence of slip-running reconnection in quasi-separatrix layers, regions where magnetic field strongly changes its connectivity. Our results provide observational proof of theoretical predictions unaddressed for nearly two decades and extend the range of magnetic field configurations where reconnection-related phenomena can occur.

Precision Manufacturing in China of Replication Mandrels for Ni-Based Monolithic Wolter-I X-ray Mirror Mandrels

The X-ray satellite “Einstein Probe” of the Chinese Academy of Sciences (CAS) was successfully launched on 9 January 2024 at 15:03 Beijing Time from the Xichang Satellite Launch Center in China with a “Long March-2C” rocket. The Einstein Probe is equipped with two scientific X-ray telescopes. One is the Wide-field X-ray Telescope (WXT), which uses lobster-eye optics. The other is the Follow-up X-ray Telescope (FXT), a Wolter-I type telescope. These telescopes are designed to study the universe for high-energy X-rays associated with transient high-energy phenomena. The FXT consists of two modules based on 54 thin X-ray Wolter-I grazing incidence Ni-replicated mirrors produced by the Italian Media Lario company, as contributions from the European Space Agency and the Max Planck Institute for Extraterrestrial Physics (MPE), which also provided the focal-plane detectors. Meanwhile, the Institute of High Energy Physics (IHEP), together with the Harbin Institute of Technology and Xi’an Institute of Optics and Precision Mechanics, has also completed the development and production of the structural and thermal model (STM), qualification model (QM) and flight model (FM) of FXT mirrors for the Einstein Probe (EP) satellites for demonstration purposes. This paper introduces the precision manufacturing adopted in China of Wolter-I X-ray mirror mandrels similar to those used for the EP-FXT payload. Moreover, the adopted electroformed nickel replication process, based on a chemical nickel–phosphorus alloy, is reported. The final results show that the surface of the produced mandrels after demolding and the internal surface of the mirrors have been super polished to the roughness level better than 0.3 nm RMS and the surface accuracy is better than 0.2 μm, and the mirror angular resolution for single mirror shells may be as good as 17.3 arcsec HPD (Half Power Diameter), 198 arcsec W90 (90% Energy Width) @1.49 keV (Al-K line). These results demonstrate the reliability and advancement of the process. As the first efficient X-ray-focusing optics manufacturing chain established in China, we successfully developed the first focusing mirror prototype that could be used for future X-ray satellite payloads.

Standing Still, Go Along, and Zooming In: Complementary Strategies of Participant-Observations in Urban Ethnography

This paper seeks to complement conventional ethnographic participant observation methods, proposing the integration of three distinct strategies. Motivated by own ethnographic studies, conducted in an urban supermarket and a food festival site, the paper contends that traditional long-term immersion may not always suffice for investigating transient urban phenomena. The paper advocates for the integration of complementary methodological strategies for participant observation adaptable to evolving contexts and research questions. Firstly, the "standing still" approach involves minimal engagement while observing a specific scene or interaction, offering a detached yet insightful perspective on fleeting moments or events. Secondly, the "go along" strategy entails tracking a particular individual, group, or object through movements and networks, providing valuable insights into routines, relationships, and controversies. Lastly, the "zooming in" technique uncovers unexpected details within scenes, interactions, or subject matter, enriching understanding of what might otherwise go unnoticed. While the first two strategies are practices employed by early pioneers in the field, the latter gains relevance in an era where video recordings are increasingly prevalent. The paper argues for the complementarity of the three strategies, fostering a more advanced comprehension of the supermarket and social landscape at large. This study holds significant implications for the practice of participant observation, encouraging researchers to embrace a repertoire of strategies tailored to the unique demands of each research inquiry and situational context. This attentive and context-driven approach allows for a more nuanced and comprehensive grasp of the social world under scrutiny.

High‐speed algorithm for fault detection and location in DC microgrids based on a novel time–frequency analysis

AbstractProtecting DC microgrids (DCMGs) from faults is critical due to the rapid current changes that occur in milliseconds. However, ensuring fast and accurate protection in DCMGs is more challenging than in AC systems. This study proposes a novel protection algorithm using traveling waves (TWs) for fault detection and localization. The high‐order synchrosqueezing transform (FSSTH) is applied to precisely identify TWs at the relay location. FSSTH offers a sharp time–frequency representation, enhancing the accuracy and speed of fault detection. This method can accurately detect transient phenomena like TWs in DCMGs, even with noise and variable fault resistance. By using the spectral envelope with FSSTH, ridges in time–frequency representations are extracted, improving fault diagnosis. The approach differentiates external from internal faults and recognizes fault direction by assessing TW polarity. Testing on two different DCMGs showed this algorithm's high efficiency and accuracy, with fault location errors ranging from 1 to 50 meters in low‐voltage and 13 to 64 meters in medium‐voltage DCMGs, even under challenging conditions like high resistance (up to 500 Ω) and low signal‐to‐noise ratio (5 dB). These results demonstrate the method's superior accuracy and robustness compared to existing techniques.

Dynamic processes of fate decision in inducible bistable systems

The process of biological fate decision regulated by gene regulatory networks (GRNs) involves numerous complex dynamical interactions among many components. Mathematical modeling typically employed ordinary differential equations (ODEs) and steady-state analysis, which has yielded valuable quantitative insights. However, stable states predicted by theoretical models often fail to capture transient or metastable phenomena that occur during most observation periods in experimental or real biological systems. We attribute this discrepancy to the omission of dynamic processes of various complex interactions. Here, we demonstrate the influence of delays in gene regulatory steps and the time scales of the external induction on the dynamic processes of the fate decision in inducible bistable systems. We propose that steady-state parameters determine the landscape of fate decision. However, during the dynamic evolution along the landscape, the unequal delays of biochemical interactions as well as time scale of external induction cause deviations in the differentiation trajectories, leading to the formation of new transient distributions that persist long-term. Our findings emphasize the importance of considering dynamic processes in fate decision, instead of relying solely on steady-state analysis. We provide insights into the interpretation of experimental phenomena, and offer valuable guidance for future efforts in dynamical modeling and synthetic biology design.

Predictive Patterns and Market Efficiency: A Deep Learning Approach to Financial Time Series Forecasting

This study explores market efficiency and behavior by integrating key theories such as the Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH), Informational Efficiency and Random Walk theory. Using LSTM enhanced by optimizers like Stochastic Gradient Descent (SGD), Adam, AdaGrad, and RMSprop, we analyze market inefficiencies in the Standard and Poor’s (SPX) index over a 22-year period. Our results reveal “pockets in time” that challenge EMH predictions, particularly with the AdaGrad optimizer at a size of the hidden layer (HS) of 64. Beyond forecasting, we apply the Dominguez–Lobato (DL) and General Spectral (GS) tests as part of the Martingale Difference Hypothesis to assess statistical inefficiencies and deviations from the Random Walk model. By emphasizing “informational efficiency”, we examine how quickly new information is reflected in stock prices. We argue that market inefficiencies are transient phenomena influenced by structural shifts and information flow, challenging the notion that forecasting alone can refute EMH. Additionally, we compare LSTM with ARIMA with Exponential Smoothing, and LightGBM to highlight the strengths and limitations of these models in financial forecasting. The LSTM model excels at capturing temporal dependencies, while LightGBM demonstrates its effectiveness in detecting non-linear relationships. Our comprehensive approach offers a nuanced understanding of market dynamics and inefficiencies.

Evaluation of Influence of Hydraulic Transient Phenomenon on the Flow of the Main Pipeline of Moamba Village Water Supply System

Evaluation of Influence of Hydraulic Transient Phenomenon on the Flow of the Main Pipeline of Moamba Village Water Supply System

Hydraulic impact of pressure transients from water conveyance tunnel on the complex hydrogeological system: A case study HPP Pirot, Serbia

Hydraulic tunnels, integral components of hydropower plant (HPP) systems, traversing diverse rock masses, pose challenges for long-term operation. The study’s main goal was to investigate how hydraulic transients originating from the headrace tunnel transfer through the concrete lining and manifest in surrounding aquifer systems. In this experimental study at the water pressure tunnel of HPP Pirot (Serbia), a novel monitoring approach was employed. The internal piezometers with highly sensitive probes are distributed strategically along the tunnel in different geological environments. This approach involved monitoring of water pressure in the surrounding rock masses and observing the impact of hydraulic transients generated by HPP operation. A comprehensive analysis of monitoring data, incorporating ordinal and partial correlations and considering geological features, provides a profound understanding of groundwater dynamics, pressure transient phenomena, and hydrogeological characterization during HPP operation. The study highlights the complex and spatially diverse hydrogeological environment, emphasizing the varying reactivity of pore pressure during HPP operation, particularly concerning Water Mass Oscillations (WMO). Reactive piezometers near the surge tank demonstrate significant pressure variations, while those located further away display synchronous pressure changes with reduced amplitudes. Schematic hydrogeological models have been created based on the hydraulic impacts of HPPs in different geological environments along the tunnel route. The water pressure response enabled aquifer characterization of (1) a thin-layered, low-fissured aquifer closely related to the reservoir, with low influence on WMO transients; (2) a low-fissured, compartment aquifer or non-aquifer with minimal to no influence on WMO transients; (3) a well-structured karst aquifer system influenced by WMO transients; (4) a fault-controlled zone of deep hypogene karst aquifer discharge highly influenced by WMO transients; and (5) an aquifer with a dominant development of the karst conduit system highly influenced by WMO transients. The study highlights the significance of monitoring water pressure within the rock mass as a fundamental element in analyzing the interaction between water pressure tunnels and the hydrogeological environment. Applying the presented instrumentation and methodology facilitates effective monitoring in research areas where pressure tunnels are constructed.

Predicting nickel catalyst deactivation in biogas steam and dry reforming for hydrogen production using machine learning

This study employs Random Forests (RF) and Artificial Neural Networks (ANN) to model the transient behavior of Ni catalyst deactivation during steam and dry reforming of model biogas containing H2S, with a focus on hydrogen production. Deactivation, induced by carbon deposition and sulfur poisoning, is a complex and transient phenomenon demanding precise kinetic mechanisms for accurately predicting Ni catalyst behavior in biogas reforming. Black-box machine learning (ML) models are developed, incorporating catalyst properties, biogas composition, and operating conditions. Encompassing both dry and steam reforming, the ML models aim to predict catalyst behavior, expressed in terms of packed bed reactor exit mole fractions (H2, CO, CH4, and CO2) and conversions (CH4 and CO2). The ML models are trained and tested across a temperature range of 700–900 C with 0–145 ppm of H2S in model biogas (CH4/CO2 ratio varying from 1.0 to 2.0). RF outperforms the ANN across all performance metrics, including overall R2 and root mean squared error (RMSE). The RF achieves a mean overall R2 of 0.979, with training and testing RMSE equal to 6.7×10−3 and 1.47×10−2 respectively. In contrast, the ANN achieves a mean overall R2 of 0.939, with training and testing RMSE equal to 2.6×10−2 and 2.55×10−2 respectively. Moreover, pre-trained RF models are validated with unseen data of dry reforming of biogas containing 30 ppm of H2S (25 data points). It is suggested that 35 % of this unseen experimental data is required to train the RF model for it to predict catalyst deactivation, achieving a validation R sufficiently2> 0.9. The mean overall R2 values attained by the RF fine-tuned on 35 % of the unseen experiment data for both CH4 and CO2 conversions, as well as for all mole fraction predictions, are 0.952 and 0.948, respectively.

Co‐occurrence in snake and lizard sister species is unrelated to major ecomorphological traits

AbstractEnvironmental factors and interspecific interactions, such as competition and facilitation, can shape species' geographic ranges. Here, we tested the relationship between geographic range overlap of squamate sister species, and their divergence in body size, diel activity, and microhabitat use. Competition theory predicts that sister species with similar traits will overlap less geographically than sister pairs with dissimilar traits. However, similar distributions may present similar selective pressures and favour similar adaptations, such that habitat filtering may result in species with more similar traits in sympatry. Across 1434 sister species contrasts, we found little relationship between range overlap and niche divergence. In some models, the divergence in body size and microhabitat use marginally increased with sympatry, while in other models, sympatric sisters had similar activity times. However, the low R‐squared values of almost all these models lend only weak support to predictions from competition or habitat filtering theories. Sympatric sister species within the same biome showed more similar activity times than expected, lending some support to habitat filtering. Niche divergence in allopatry or sympatry, as calculated using a multi‐trait dissimilarity index, did not show a phylogenetic signal, and niches of sister species from different squamate clades did not deviate significantly from the null expectation. Overall, niche divergence or convergence, across the axes we explored, is not a prerequisite for regional species co‐occurrence. We suggest here that the lack of consistent support for either limiting similarity or habitat filtering may reflect that both these forces act as transient phenomena. More fine‐grained analyses, in space and time, would be needed to detect their fingerprints. Thus, coexistence in the face of competition can arise due to various evolutionary and biogeographic mechanisms, acting concurrently or asynchronously.

Erroneous Automated WBC Differentials—A Case Series

Background and Aims: Peroxidase deficiency is one of the commonly inherited phagocytic defects. It has been also found to exist as a transient phenomenon in association with some clinical conditions. But that it can interfere and cause erroneous automated differential WBC count is something which is not commonly known. Materials and methods: Complete blood counts were analysed using Advia 2120i and Coulter DXH 900 haematology analysers and manually reviewed on peripheral blood smear stained with Leishman stain. Results: Peroxidase deficiency in neutrophils and eosinophils resulted in them getting counted as monocytes by the analyser causing pseudomonocytosis, pseudoneutropenia and pseudoeosinopenia. These were detected by a slide review and by reanalysing the samples on an analyser which worked on a different principle. Conclusion: There is a need to confirm monocytosis given by analysers working on the peroxidase principle with an alternate method. This will prevent needless medical investigations for pseudoneutropenia, pseudoeosinopenia and persistent monocytosis, thus preventing unwarranted mental agony and financial burden to patients. It also helps to save the laboratory’s reputation. A careful review of instrument flags not only helps reach an accurate result but sometimes they can also aid in the diagnosis of a rare potential genetic disorder like MPO deficiency.

Large‐signal stability analysis for hybridized vehicular power supply systems of rolling stocks

AbstractHybridized vehicular power supply (HVPS) are acquiring widespread adoption in various applications such as providing power for passenger or heavy‐duty electric vehicles, more‐electric ships, electrified rolling stocks, and more. Stability analysis is a critical issue for HVPS, but it presents significant challenges due to their prominent high‐dimensional and nonlinear characteristics. This paper presents a large‐signal stability analysis scheme for HVPS of rolling stocks, enabling the assessment of system stability under sudden load changes. Based on the state‐space averaging method, a mathematical model for the large‐signal behavior of the system is established. Subsequently, the small‐signal stability parameter range of the system is determined by analyzing the eigenvalues of the Jacobian matrix. To further analyze the stability of the system during large‐signal disturbances, a nonlinear decoupling transformation approach is employed to decompose the original high‐order state equations into multiple lower‐order equations. For the decoupled lower‐order subsystems, their stability is analyzed using phase portrait, and the region of attraction (ROA) is determined using the inverse trajectory method. Based on the stability analysis results, the controller is enhanced to bring the points outside the ROA back within it, thereby mitigating the transient instability phenomenon of the system. The effectiveness of the proposed method was demonstrated using two case studies.

Observations and Simulations of a Double‐Core Hot Flow Anomaly

AbstractHot Flow anomalies (HFAs), one of the most well‐analyzed transient phenomena in the Earth's foreshock, are known as kinetic structures driven by tangential discontinuities (TDs). Recently, a 2‐dimensional (2D) magnetohydrodynamics (MHD) model reproduced HFAs with either a high‐ or low‐density core. Further investigation of an HFA with two cores observed by the Magnetospheric Multiscale (MMS) mission is reported. The observation via the Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) mission suggests this MHD HFA is associated with a foreshock density hole‐like structure. The trailing flux tube in simulation may propagate with a TD in the foreshock. Our work suggests that HFAs with two low‐density cores can also be achieved in MHD process. Results show the total ram pressure can be an excellent diagnostic for the presence of transient structures, such as HFAs, at the bow shock.