Transient Variations Research Articles

Hydrogen storage and refueling options: A performance evaluation

This study focuses on the comparative modeling and refueling simulations of hydrogen refueling stations for hydrogen-powered vehicles and high-pressure hydrogen storage options in tanks. The study further aims to simulate these under actual conditions in Ontario, Canada for better assessment which can be treated as a case study as well. The specific tests explore the modeling of hydrogen flow between the recharging station to the car's tank, as well as the optimization of transient variations in temperature, pressure and mass flow rate of hydrogen throughout the process of refueling a fuel cell electric vehicle. The H2FILLS program is utilized to assist for the simulation studies. The primary objective is to replicate various practical weather conditions, tank pressures, flow rates, and refueling periods for different categories of high-pressure hydrogen storage tanks and analyze their storage efficiency. The three different commercially available high-pressure type-IV hydrogen storage tanks were considered in the study as tank-I, tank-II and tank-III with working pressures of 500 bar, 700 bar, 700 bar, and hydrogen storage capacity of 9.5 kg, 4.6 kg, and 5 kg, respectively. Seven different ambient temperatures were selected to mimic seasonal effects. When the power output is constant, with temperature increases, flow rate decreases, and therefore time required to refuel also increases. There is a linear relationship between the final mass flow rate and the ambient temperature, where the mass flow rate drops by approximately 1.8 kg/h for every 10 °C rise in temperature. The variation in ultimate mass flow rate between the highest and lowest ambient temperatures is roughly 5.4 kg/h. Based on the refueling time and docking, undocking, downtime it’s been found that approximately five minutes is wasted between each vehicle. This can help reduce average of 230.02 kt, 231.70 kt, and 235.06 kt CO2 emission per year for vehicle-III, vehicle-II, and vehicle-I, respectively. Lastly, yearly CO2 reduction forecast shows that it may reach 0.9 Mt, 1.6 Mt, 2.7Mt, 3.76 Mt, and 4.73 Mt in the year 2030, 2035, 2040, 2045, and 2050, respectively corresponding to the Global Net-Zero scenario.

Ligand Controls Excited Charge Carrier Dynamics in Metal-Rich CdSe Quantum Dots: Computational Insights.

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron-phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd28Se17X22 QDs (X = HCOO-, OH-, Cl-, and SH-) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron-phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd28Se17(OH)22 has the fastest nonradiative recombination rate due to the strongest electron-phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron-phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

Investigation of double-PCM based PV composite wall for power-generation and building insulation: Thermal characteristics and energy consumption prediction

The integration of phase change material (PCM) with building-integrated photovoltaic (BIPV) presents a compelling approach to enhance solar energy utilization and mitigate indoor thermal loads, contributing to energy-efficient and low-carbon building development. Traditional BIPV-PCM structures, however, struggle to balance PV efficiency and thermal insulation, particularly with varying PCM wall positions. To address this situation, this study introduces a novel double-PCM BIPV composite envelope (BIPV-dPCM). An experimentally validated dynamic heat transfer model was developed and used to perform a comparative simulation analysis with three reference systems to quantify the energy-saving potential of the BIPV-dPCM, focusing on PV output and wall insulation effectiveness metrics. Further dimensionless parametric analysis were carried out to investigate the systematic performance of the two PCMs at different relativities. In addition, the coupled working mechanism of the BIPV-dPCM system concerning the power generation performance and thermal insulation performance under transient variations is explored. It was found that the BIPV-dPCM showcases superior thermoelectric coupling performance compared to three alternative enclosures. Incorporating two PCMs significantly enhances electrical exergy efficiency by 11.66 % and thermal exergy efficiency by 1.54 %, surpassing other reference systems. The increase in PCM latent heat ratio has a limited effect on performance gain. Notably, as the PCM thickness ratio exceeds 1, the decline in P value decelerates, for every 0.5 increment in the g, the P value diminishes by merely 0.2 %. The ideal h is identified between 1 and 1.5, with 1.5 being optimal for energy conservation objectives. Additionally, the self-sufficiency coefficient (SSC) of the BIPV-dPCM remains robust, sustaining a range of 55 % to 65 % over prolonged periods. This study offers novel perspectives and serves as a design reference for optimizing building energy systems and enhancing cooling efficiencies in subtropical climates.

The Water Hammer Characteristics of Long-Distance Water Pipelines under Different Water Supply Modes

The pressure characteristics of long-distance water pipelines during hydraulic transient processes are crucial for ensuring the safe, stable, and long-term operation of water transfer projects. This paper establishes a one-dimensional mathematical model based on sections of the Yinjiangjihuai long-distance water diversion project in China. The water supply requirements of the pipelines are categorized into two replenishment modes as follows: gravity supply and pump-pressurized water supply. The opening and closing strategies of the water pipelines under different flow conditions are simulated and analyzed to explore the hydraulic transient processes under various water supply modes. The transient variations of key hydraulic parameters during valve closure are clarified. Simulation results indicate that the water pipeline design is reasonable, meeting the water supply demands at relatively low Manning values and that it has the capability for long-term supply. Due to the excessive head provided by the pumps, pump-pressurized water supply and gravity supply modes cannot operate simultaneously. Under gravity supply mode, the minimum pressure in the downstream pipeline is relatively higher overall, while the maximum pressure in the upstream pipeline is relatively lower overall. In the pump-pressurized water supply mode, the safety and stability of the water supply can be ensured by adjusting the closing time of individual pumps and the interval time between adjacent pumps. The research findings provide technical guidance and scientific basis for the construction of national water networks and water transfer projects.

Surface temperature field real-time reconstruction of hot forging die based on 1DCNN

Accurate reconstruction of the die surface temperature field during the hot forging process is crucial for ensuring optimal control of die temperature and high-quality metal forgings. In this study, we propose a novel method that combines hot forging process parameters with a deep neural network to reconstruct the temperature field on the die surface in real-time. Firstly, a high-fidelity finite element model of the hot forging process is created and validated with a forging experiment. Secondly, temperature observation points are initially selected based on the simulated temperature distribution of the forging die, and the correlation coefficient method is used to optimize the layout of observation points to improve reconstruction accuracy and efficiency. Subsequently, multiple high-quality simulations with varying process parameters are conducted, generating a comprehensive dataset. The 1DCNN algorithm is then presented to produce a mapping from the input to the surface temperature field. Finally, the effectiveness of the surface temperature field reconstruction method is verified. The results indicate that the overall performance of the proposed 1DCNN algorithm is better than the traditional regression algorithms. In terms of reconstruction accuracy, it achieves a prediction accuracy within an absolute error of 3 °C for the outer surface points and within a relative error of 5 % for the cavity region. Regarding reconstruction efficiency, it requires an approximate execution time of 0.064 s for predicting a new sample. This paper presents a method for real-time reconstruction of the die surface temperature field, leveraging hot forging process parameters and temperature data from observation points. This approach enables reliable online monitoring of transient temperature variations on the hot forging die surface, offering valuable support for operational control and maintenance.

Current Evidence for a New Surgical Technique for Scleral Fixation: The Implantation of a Carlevale Lens, a Systematic Review.

Background: The Carlevale lens (FIL SSF, Soleko IOL Division, Italy) is a new lens for suture-less scleral fixation. This paper aimed to systematically review articles on this lens, the surgical techniques used for its implantation, complications and outcomes. Methods: This systematic review was performed following the PRISMA guidelines. The search string used was "Carlevale" AND "scleral fixation" from inception until March 2024. For completeness, either case-control studies, case reports or case series written in English were included. The authors used the Newcastle-Ottawa scale for the case-control studies and the JBI Critical Appraisal Checklist for case reports and case series. Results: Twenty-nine articles were included. Scleral fixation with Carlevale lens can be performed by creating scleral flaps or, alternatively, by using scleral pockets. The two sclerotomies must be diametrically opposed, and are preferably created by 25-gauge trocars. A pars plana vitrectomy should be performed every time, and the design of the lens should be suitable for self-anchoring to the sclera; the most accredited strategy to achieve this is to avoid scleral sutures. There were only a few intraoperative and postoperative complications reported; vitreous hemorrhages were the most frequent intraoperative events, while the most relevant postoperative complications were vitreous hemorrhages, cystoid macular oedema and transient variations in the intraocular pressure. Excellent results have been obtained in terms of BCVA, IOL centration and stability, mean intraocular pressure, postoperative spherical equivalent, separation between anterior and posterior chamber and the distance of the IOL from anterior chamber structures. Conclusions: The foldable hydrophilic design of the Carlevale lens has shown good effectiveness, IOL stability and few intra and post-operative complications.

A novel hybrid deep learning time series forecasting model based on long-short-term patterns

Time series forecasting constitutes a cornerstone in decision-making processes across diverse domains, ranging from finance and economics to healthcare and environmental science. However, traditional long-term forecasting models often overlook the nuanced characteristics of short-term patterns, which exhibit rapid fluctuations within brief intervals. These short-term patterns, encapsulating frequency domain features, encode valuable information about transient phenomena and periodic variations that can significantly impact predictive accuracy. In the paper has been proposed a novel approach to long-term forecasting of multi-dimensional time series data using convolutional and recurrent neural networks. The proposed model harnesses the power of advanced neural network architectures, integrating both short and long-term time series patterns trends while concurrently leveraging Fourier transform analysis to extract frequency domain patterns. By synthesizing information from short-term fluctuations and long-term trends, the proposed model offers a comprehensive framework for robust forecasting, enhancing predictive accuracy across diverse applications. Through extensive simulations, the results of experiments demonstrate the superior performance of proposed model compared to conventional forecasting techniques, thereby showcasing its potential to revolutionize time series forecasting methodologies.

Study on the influence of intermediate airshafts on the aerodynamic effect of urban rapid rail transit

This study explores how intermediate airshafts affect the aerodynamics of urban rapid transit trains in tunnels. It employs a three-dimensional turbulence model to simulate train-tunnel interactions, specifically examining airshafts’ impact on transient pressure variations along surfaces. The model’s accuracy and reliability are confirmed by comparing results with full-scale experimental data. The results show that airshafts effectively mitigate peak tunnel wall pressures, with the lowest peak overpressure observed at the airshaft location. With the airshaft-reflected expansion wave arriving ahead of the train, the pressure between the train front and tunnel wall decreases compared to scenarios without airshafts. Similar transient pressure changes at the tunnel entrance and rear half suggest the emergence of a “secondary compression wave” due to the train’s transit.

Suppression mechanism of transient pressure during the turbine runaway of an ultra-high head pump-turbine

Abstract Pressure fluctuation (PF) is a serious issue in transitions of the ultra-high head (UHH) pump-turbines (PTs). To explore the mechanism and control method of PF, the turbine runaway process (TRP) of an UHH PT was simulated using the one- and three-dimensional coupled method. The study suggested that the local backflow (BF) near the high-pressure (HP) inlet of the impeller blocked the impeller channel and induced water hammer. The local BF near the HP inlet of the impeller were closely related to the ratio of rotational speed to PT head. To suppress the BF this study proposed an improved impeller channel with 5 degree spread angle in meridian plane. The study found that the increase of rotational speed and transient pressure variations induced by water hammer could be suppressed successfully by using the improved impeller. The study provided important reference for the design and optimization of the UHH PTs.

Intrusive mechanism of the 2018 Sierra Negra Galápagos eruption, constrained by 4D tomographic images

Understanding the mechanisms of magma intrusion underpins our ability to interpret geophysical monitoring signals at volcanoes and thus issue reliable forecasts of future activity. The basaltic caldera volcanoes of the western Galápagos Islands, Ecuador, exhibit exceptionally high rates of deformation driven by shallow magma accumulation and migration. However, the nature and evolution of magma storage at these volcanoes is poorly constrained by earthquake hypocentre locations or geodetic inversions. Here we show that transient variations in seismic velocity before, during, and after the 2018 eruption of the Sierra Negra volcano track the accumulation of magma in a shallow sill complex and the emplacement of a lateral flank intrusion. A four-dimensional tomographic technique applied to the P-wave arrivals of local earthquakes provides high spatiotemporal resolution of changes in the physical properties of the shallow volcanic system. In the month before the eruption, the expansion of a low-velocity zone above the sub-caldera sill complex coincides with caldera uplift and near-surface fracturing, driven by persistent shallow magma accumulation. A new low-velocity anomaly appeared progressively in the western flank of the volcano in the days after the onset of the eruption, coinciding with the opening of a curved sill that supplied magma to secondary eruptive fissures. The anomaly disappeared as the curved sill deflated after the initial opening, despite it remaining the conduit for magma from the caldera complex to the flank fissures. Low velocities across the shallow caldera after the end of the eruption likely result from rapid inflation due to recharge with fresh magma from depth. These results indicate a previously unknown complexity to the magmatic plumbing system at Sierra Negra and suggest velocity changes resulting from an interplay of thermal and stress perturbations.

Thermoelectric active cooling for transient hot spots in microprocessors

Modern microprocessor performance is limited by local hot spots induced at high frequency by busy integrated circuit elements such as the clock generator. Locally embedded thermoelectric devices (TEDs) are proposed to perform active cooling whereby thermoelectric effects enhance passive cooling by the Fourier law in removing heat from the hot spot to colder regions. To mitigate transient heating events and improve temperature stability, we propose a novel analytical solution that describes the temperature response of a periodically heated hot spot that is actively cooled by a TED driven electrically at the same frequency. The analytical solution that we present is validated by experimental data from frequency domain thermal reflectance (FDTR) measurements made directly on an actively cooled Si thermoelectric device where the pump laser replicates the transient hot spot. We herein demonstrate a practical method to actively cancel the transient temperature variations on circuit elements with TEDs. This result opens a new path to optimize the design of cooling systems for transient localized hot spots in integrated circuits.

Modeling of a PV/Thermal Hybrid Panel for Residential Hot Water System

Abstract Despite the extensive body of research on PV/thermal systems, a gap remains in evaluating their performance in residential settings. This study aims to bridge this gap by focusing on the energy modeling of a PV/Thermal (PVT) hybrid panel that incorporates heat pipe technology. The evaluation is conducted through MATLAB code to assess the system's capability to fulfill the electricity and heating demands of residential buildings. The model's reliability is affirmed by comparing it with experimental data from a PVT panel tested in Sydney, exploring the transient variations in both water heat gain rates and power generation. The model's precision is evident from the percentage of error in the estimated temperatures of the PV panel based on the test results under various weather conditions, which ranged from −8% to 6%. This method was also utilized to determine the overall energy efficiency of the PVT under different climatic conditions. The results reveal that the overall energy efficiency of the proposed PVT panel, on a typical day, is approximately 45%, significantly outperforming traditional PV panels by more than double. Furthermore, the payback period for a typical residential PVT system, providing both hot water and electricity, is found substantially shorter than that of installing separate PV and solar hot water systems, highlighting the economic and environmental benefits of the proposed hybrid system.

A Modified Enthalpic Lattice Boltzmann Method for Simulating Conjugate Heat Transfer Problems in Non-Homogeneous Media

A Modified Enthalpic Lattice Boltzmann Method for Simulating Conjugate Heat Transfer Problems in Non-Homogeneous Media

Transient skin friction behavior associated with hemisphere-based vortex ring collisions

Global and local transient skin friction variations resulting from a large-eddy simulation study on ReΓ0=3000 vortex rings colliding with surface-mounted hemispheres of hemisphere-to-vortex-ring diameter-ratios of 0.5≤D/d≤2 are investigated here. Skin friction distribution changes due to the approaching primary vortex ring, formation of secondary/tertiary vortex rings, subsequent mutual interactions between various vortex ring structures, and azimuthal instabilities are clarified with a view to better establish their relationships when the relative hemisphere size varies. Results show that the primary vortex ring produces the highest skin friction levels when it is close to or collides with the hemisphere/flat wall. Additionally, entrainment of wavy secondary/tertiary vortex rings leads to them entangling around the primary vortex ring and resulting in segmented skin friction regions at later stages of the collision process, regardless of the diameter-ratio. Unlike smaller hemispheres, the largest D/d=2 hemisphere here restricts all skin friction changes along its surface with the flat wall unaffected. It is also revealed here that while the diameter-ratio governs the global skin friction distributions, how secondary/tertiary vortex rings interact with the primary vortex ring and how azimuthal instabilities manifest and evolve for all the various vortex rings confer strong influences on the breaking-up and dissipation of regions with high skin friction levels.

Evaluating the effects of mefenoxam on taxonomic and functional dynamics of nontarget fungal communities during carrot cultivation

Ridomil Gold SL (45.3% a.i. mefenoxam) is a widely used chemical fungicide for the control of oomycetes. However, its impact on fungal communities remains unexplored. Therefore, the goal of this study was to examine the effects of mefenoxam on the temporal dynamics of fungal taxonomic and functional diversities during carrot cultivation under four treatment groups: mefenoxam application with and without Pythium inoculation, and untreated control groups with and without Pythium inoculation. Our in vitro sensitivity assay showed that the maximum recommended concentration of mefenoxam, 0.24 ppm, did not suppress the mycelial growth of P. irregulare. At 100 ppm, mycelial growth was only reduced by 11.4%, indicating that the isolate was resistant to mefenoxam. MiSeq sequencing data revealed transient taxonomic variations among treatments 2 weeks post-treatment. Mortierella dominated the fungal community in the mefenoxam-Pythium combination treatment, as confirmed through PCR using our newly designed Mortierella-specific primers. Conversely, mefenoxam-Pythium combination had adverse effects on Penicillium, Trichoderma, and Fusarium, and decrease the overall alpha diversity. However, these compositional changes gradually reverted to those observed in the control by the 12th week. The predicted ecological functions of fungal communities in all Pythium and mefenoxam treatments shifted, leading to a decrease in symbiotrophs and plant pathogen functional groups. Moreover, the community-level physiological profiling approach, utilizing 96-well Biolog FF microplates, showed discernible variations in the utilization of 95 diverse carbon sources among the treatments. Notably, arbutin, l-arabinose, Tween 80, and succinamic acid demonstrated a strong positive association with Mortierella. Our findings demonstrate that a single application of mefenoxam at its recommended rate triggers substantial taxonomic and functional shifts in the soil fungal community. Considering this impact, the conventional agricultural practice of repeated mefenoxam application is likely to exert considerable shifts on the soil ecosystem that may affect agricultural sustainability.

Physics-informed neural networks in groundwater flow modeling: Advantages and future directions

In recent years, there has been enormous development in soft computing, especially artificial intelligence (AI), which has developed robust methods for solving complex engineering problems. Researchers in the field of water resources engineering have applied these AI methods to solve a variety of hydrological problems. Despite their widespread use in the surface and atmospheric hydrology fields, groundwater hydrologists have not widely used AI methods in their routine field-scale modeling efforts. This is because AI models have been primarily considered black box models that lack physical meaning. Furthermore, using AI models to generate the space-time distribution of transient groundwater level variations is challenging and requires further flux balance and mass transport analyses. More recently, a new type of physics-informed neural network (PINN) model has been developed to address several limitations by integrating governing physics (groundwater flow equations) into the AI tools. This study presents the systematic advantages of the PINN algorithm for solving groundwater problems using a set of classic test problems. As discussed in detail in the article, these advantages and potentials are associated with the meshless nature of PINN, its continuous time and space dimensions, its independence from time-stepping and incremental marching in space, and its efficiency in running time. However, despite PINN's promising attributes, it is important to acknowledge its nascent stage of development and the inherent limitations of all neural network models, such as training challenges and hyperparameter selection. Thus, collaborative efforts between groundwater modelers and computer scientists are imperative to explore and exploit the full potential of PINN in tackling increasingly complex groundwater problems and nurturing PINN into a dependable modeling tool in industry and academia.

Effect of Extreme Variations of Fundamental Constants on the Structure of Atoms and Molecules.

The fundamental constants (FCs) of physics are promoted to dynamic quantities in modern theories. So far most of the literature focused on small fractional variations in the values of FCs. In this paper, we investigate the novel regime of extreme but transient variations of FCs. We focus on the speed of light (c) and show that its variation can dramatically change the electronic structure and chemistry of atoms and molecules. These changes are induced by increased relativistic effects when c is reduced from its nominal value. To model these changes, we solve the fully relativistic Dirac equation at different values of c. We show that at extreme variations of c, the periodic table is truncated, the nominal ground states of atoms can change, water fails to serve as a universal solvent, and the ammonia molecule becomes planar.

Oxygenation heterogeneity facilitates spatiotemporal flow pattern visualization inside human blood vessels using photoacoustic computed tomography

Hemodynamics can be explored through various biomedical imaging techniques. However, observing transient spatiotemporal variations in the saturation of oxygen (sO2) within human blood vessels proves challenging with conventional methods. In this study, we employed photoacoustic computed tomography (PACT) to reconstruct the evolving spatiotemporal patterns in a human vein. Through analysis of the multi-wavelength photoacoustic (PA) spectrum, we illustrated the dynamic distribution within blood vessels. Additionally, we computationally rendered the dynamic process of venous blood flowing into the major vein and entering a branching vessel. Notably, we successfully recovered, in real time, the parabolic wavefront profile of laminar flow inside a deep vein in vivo—a first-time achievement. While the study is preliminary, the demonstrated capability of dynamic sO2 imaging holds promise for new applications in biology and medicine.

Time-domain electric field analysis of few-cycle pulse damage behavior in ultra-broadband chirped mirrors

The laser-induced damage resistance performance of ultra-broadband chirped mirrors (UBCM) is a critical factor influencing the generation of petawatt or exawatt laser pulses in thin film compression techniques. In this study, a few-cycle pulse damage testing platform was set up, and two UBCMs with different designs were fabricated for a comparative study of their laser-induced damage. Because light of varying wavelengths forms an electric field at different times within UBCMs under few-cycle pulse irradiation, a time-domain electric field model was developed to obtain transient electric field variations and explain the damage behavior. The model successfully elucidated the origin of the damage and discrepancy between the two UBCMs in terms of damage thresholds, showcasing its potential applications in designing high-threshold UBCMs for high-power laser systems.

Searching for large dark matter clumps using the Galileo Constellation clock variations

This study presents bounds on transient variations of fundamental constants, with typical timescales ranging from minutes to months, using clocks in space. The underlying phenomenology describing such transient variations relies on models for Dark Matter (DM) which suggest possible encounters of macroscopic compact objects with the Earth, due to the motion of the solar system in the galactic halo. If such compact objects possess an effective feeble interaction with the ordinary matter beyond the gravitational one, it may result in effective transient variations of fundamental constants. Such variations leave signatures on clocks onboard GNSS satellites. In this paper, we introduce a phenomenological study dedicated to the search for such DM transient objects using the network of passive hydrogen masers (H-Masers) onboard Galileo satellites. We first model the signature of transient variations of fundamental constants as a frequency modulation in the difference between two satellite clocks, considering the satellite trajectories relative to the transient event. Then, we present first results based on a fast analysis method, the maximum reach analysis. The main result is a significant extension of the discovery range for DM transients, with a sensitivity never achieved before. We investigate indeed the range of transient sizes from 105 to 109 kilometres, which, apart from indirect and model-dependent non-transient effects, has never been explored previously.