Search Results (2,780)

Temperature excursions during refrigerated transport strongly affect the quality and shelf life of perishable food, yet reproducing realistic, time-varying cold-chain temperature histories in the laboratory remains challenging. In this study, we present a compact, portable climate chamber driven by Peltier modules and an identification-guided control architecture designed to reproduce real refrigerated-truck temperature histories with high fidelity. Control is implemented as a cascaded regulator: an outer two-degree-of-freedom PID for air-temperature tracking and faster inner PID loops for module-face regulation, enhanced with derivative filtering, anti-windup back-calculation, a Smith predictor, and hysteresis-based bumpless switching to manage dead time and polarity reversals. The system integrates distributed temperature and humidity sensors to provide real-time feedback for precise thermal control, enabling accurate reproduction of cold-chain conditions. Validation comprised two independent 36-day reproductions of field traces and a focused 24-h comparison against traditional control baselines. Over the long trials, the chamber achieved very low long-run errors ($\mathrm{MAE}\cong 0.19 °\mathrm{C}$, $\mathrm{MedAE}\cong 0.10 °\mathrm{C}$, $\mathrm{RMSE}\cong 0.33 °\mathrm{C}$, $R^2=0.9985$). The 24-h test demonstrated that our optimized controller tracked the reference, improving both transient and steady-state behaviour. The system tolerated realistic humidity transients without loss of closed-loop performance. This portable platform functions as a reproducible physical twin for cold-chain experiments and a reliable data source for training predictive shelf-life and digital-twin models to reduce food waste. Full article

The paper presents the findings of an analysis of a tank subjected to thermal effects caused by variations in air and liquid temperatures. The structural analysis focuses on the influence that thermal actions exert on the distribution of prestressing force. One of the important aspects addressed is the application of transient heat transfer analysis instead of the steady-state approach, allowing for a more accurate yet realistic representation of thermal effects within load combinations used to evaluate prestressing force. The study suggests that thermal actions should reflect the average annual temperatures of air and liquid separately, considering the transient thermal field. This hypothesis contradicts the standard approach. Numerical simulations using the finite element method were conducted in order to model transient heat transfer (CFD model) and the structural response of the tank (with axisymmetric shell model). The results indicated that temperature gradients across the tank wall may be linear or non-linear, varying with time and the amplitude of air temperature. Consequently, a modified formula for the reduced temperature gradient is proposed. The research emphasises the importance of incorporating transient thermal effects and the temperature-influenced distribution of prestressing force, which may have a significant impact on the safety of prestressed tanks. Full article

This paper presents a comprehensive analysis of the dynamic properties of low-power current transformers (LPCTs) in the context of their application in both power systems and electromechanical systems. Momentary changes in external loads occurring in the mechanical parts of systems, affecting their correct operation, cause the appropriate monitoring and control systems, including LPCTs, to operate in transient states where dynamic errors are significant. The issues discussed in this article are therefore important from both an electrical and mechanical engineering perspective. The study focuses on the evaluation of dynamic errors using two complementary performance criteria: the mean squared error and the absolute dynamic error. An equivalent circuit model of the LPCT is formulated and employed to investigate its response under transient conditions representative of modern energy networks as well as electromechanical devices, including drives, converters, and rotating machines operating under variable loads. A key contribution of this work is the determination of the upper bounds of dynamic errors, which establish the ultimate accuracy constraints of LPCTs when subjected to rapid current variations. The obtained results provide quantitative evidence of the impact of dynamic properties on the reliability of current measurements, thereby reinforcing the importance of the proposed error evaluation framework. In this context, the study demonstrates that a rigorous assessment of dynamic errors is essential for improving the functional performance of LPCTs, particularly in applications where steady-state accuracy must be complemented by a reliable transient response. Full article

Cell population and vascular vessel distribution analysis in membrane-based scaffolds for tissue engineering is crucial. Biomimetic nanostructured membranes of methyl methacrylate/hydroxyethyl methacrylate and methyl acrylate/hydroxyethyl acrylate (MMA)1-co-(HEMA)1/(MA)3-co-(HEA)2 loaded with 5% wt SiO2-nanoparticles (Si-M) were doped with zinc (Zn-M) or doxycycline (Dox-M). Critical bone defects were effectuated on six New Zealand-bred rabbit skulls and then they were covered with the membrane-based scaffolds. After six weeks, bone cell population in terms of osteoblasts, osteoclasts, osteocytes, fibroblasts, and M1 and M2 macrophages and vasculature was determined. The areas of interest were the space above (over) and below (under) the membrane, apart from the interior (inner) compartment. All membranes showed that vasculature and most cell types were more abundant under the membrane than in the inner or above regions. Quantitatively, osteoblast density increased by approximately 35% in Zn-M and 25% in Si-M compared with Dox-M. Osteoclast counts decreased by about 78% in Dox-M, indicating strong inhibition of bone resorption. Vascular structures were nearly twofold more frequent under the membranes, particularly in Si-M, while fibroblast presence remained moderate and evenly distributed. The M1/M2 macrophage ratio was higher in Zn-M, reflecting a transient pro-inflammatory state, whereas Dox-M favored an anti-inflammatory, pro-regenerative profile. These results indicate that the biomimetic electrospun membranes functioned as architectural templates that provided favorable microenvironments for cell colonization, angiogenesis, and early bone regeneration in a preclinical in vivo model. Zn-M membranes appear suitable for early osteogenic stimulation, while Dox-M membranes may be advantageous in clinical contexts requiring modulation of inflammation and osteoclastic activity. Full article

During the laser cladding process, the distribution of the temperature field directly influences the morphology, microstructure, and residual stress state of the cladding layer. However, the process involves transient characteristics of rapid heating and cooling, making it challenging to study temperature field variations directly through experimental methods. Therefore, numerical simulation has become a crucial tool for gaining a deeper understanding of the laser cladding mechanism, providing theoretical basis and guidance for optimizing process parameters. This study systematically integrates COMSOL Multiphysics coupling simulation with Jmatpro material thermal property data to perform simulations of temperature field evolution, melt pool flow behavior, and Marangoni effects during laser cladding of nickel-based alloy (IN718) onto an EA4T steel substrate. It highlights the influence patterns of different process parameters (e.g., laser power, scanning speed) on the temperature gradient and flow characteristics of the molten pool, providing an in-depth theoretical basis for understanding the formation mechanism of the molten pool and microstructure control. Full article

Supercritical carbon dioxide (sCO₂) Brayton cycle is a promising technology for concentrating solar power systems. However, existing studies predominantly rely on steady-state or quasi-steady-state assumptions, thereby neglecting transient characteristics of fluid flow and heat transfer. This study develops a transient analysis program for solar power tower systems integrated with sCO₂ Brayton cycles using the finite difference method. The program comprises two interactive modules—a molten salt loop and a Brayton cycle module—coupled through an intermediate heat exchanger. For the Brayton cycle module, a fluid network model enabling a unified framework for the simultaneous solution of all governing equations is adopted. The SIMPLE algorithm and Gauss–Seidel iteration method are employed to solve the conservation equations. Following validation of key components and system performance, dynamic simulations under load and solar irradiance step disturbances are conducted. The results demonstrate that the program accurately captures transient behaviors and supports control strategy design and safety analysis for solar power tower systems with arbitrary sCO₂ Brayton cycle layouts. Full article

In the eastern part of India, specifically in the coastal districts of Odisha, the Puri central canalsystem’s Phulnakhara distributary command, which is split between the districts of Cuttack and Khurda, is where the study was taken up during 2020 and 2021. The flow modelling of the Phulnakhara distributary command, covering a 49.03 km² area, was done by Visual MODFLOW (VMOD). The command area’s conceptual model was created by assigning various input data, and the developed model was calibrated with 1-year data (2020) and validated with 1-year data (2021) on a fortnightly basis for simulating the groundwater flow using VMOD. Both steady state and transient state circumstances were used to calibrate the hydraulic conductivity and storage coefficient for the various layers in 2020. The calibrated hydraulic conductivity values vary from 1.16 × 10⁻³ ms⁻¹ to 4.86 × 10⁻⁴ ms⁻¹, and the calibrated values (2.00 × 10⁻² m⁻¹ to 4.00 × 10⁻⁶ m⁻¹) of specific storage varied from the first to third layer in both state scenarios. The validated model could forecast the groundwater condition and the flow head for the following ten years, assuming a 0.5% annual drop in recharge by increasing the pumping rate five, six, and seven times throughout the validation period (2021). The modelling study suggested that the command area will not remain safe for 10 years from the point of future groundwater development. The model performance showed strong agreement between simulated and observed groundwater heads, with R² values ranging from 0.68 to 0.91 and NSE values between 0.64 and 0.88. Predictive simulations indicated groundwater drawdowns of 4.82 m, 5.72 m, and 6.11 m under 5×, 6×, and 7× pumping scenarios, respectively, over the next decade, highlighting a significant risk of depletion unless conjunctive use strategies are adopted. Full article

Background/Objectives: The drug development response to the unique pharmacology of fentanyl, which drives the current opioid epidemic, has primarily focused on increasing naloxone doses and employing longer-acting antidotes. While having lower withdrawal liability, the commonly perceived disadvantage of naloxone is its reduced effectiveness against re-narcotization or “fentanyl rebound,” due to a significant mismatch between its half-life (t_1/2) and that of fentanyl. Methods: We conducted a pharmacokinetic profile (PK) crossover study in fentanyl-sedated dogs to assess naloxone (NX) and its lipophilic prodrug (NX90) with regard to fentanyl PK and re-narcotization risk. Results: Our findings showed that naloxone redistributed fentanyl into the plasma, with correlating (R² = 0.9121) fentanyl and naloxone plasma levels when seven plasma samples per dog for each treatment (including placebo) were analyzed. This redistribution led to reductions in fentanyl’s volume of distribution at steady state (V_ss: 11.8 ± 1.7, 8.4 ± 2.4, and 8.7 ± 2.6 L/kg), mean residence time (MRT: 19.9 ± 1.8, 18.6 ± 7.2, and 16.2 ± 8.8 min), and half-life (t_1/2: 14.3 ± 1.9, 13.0 ± 4.9, and 11.2 ± 6.1 min) after the administration of a placebo, NX, and NX90, respectively. Additionally, we observed that the delay in the transient re-sedation (re-narcotization) of the dogs correlated (R² = 0.794) with naloxone’s exposure (AUC_inf). These data suggest that (i) the displacement of fentanyl into a metabolically active compartment and (ii) the delay in re-narcotization risk are both independent of naloxone’s half-life and are likely to be more effectively achieved with higher doses of naloxone. Conclusions: Combined with the lower risk of precipitating protracted withdrawal, these findings support the clinical use of higher-dose naloxone over longer-acting antidotes for reversing fentanyl-related overdoses. Full article

High-precision speed measurement at low speeds in PMSM drives is hindered by encoder quantization noise. This paper proposes an enhanced extended state observer (ESO)-based method to overcome limitations of conventional approaches such as direct differentiation with the low-pass filter (high noise), the phase-locked loop (PLL)-based method (limited dynamic response), and standard ESO (sensitivity to disturbance). The improved ESO incorporates reference torque feedforward and disturbance feedback, significantly suppressing noise and enhancing robustness. Simulations and experiments demonstrate that the proposed method reduces steady-state speed fluctuation by up to 42% compared to standard ESO and over 90.1% relative to differentiation-based methods, while also improving transient performance. It exhibits superior accuracy and stability across various low-speed conditions, offering a practical solution for high-performance servo applications. Full article

The increasing integration of power-electronic devices, such as voltage source converter-based high-voltage direct current (VSC-HVDC) systems and inverter-interfaced renewable energy sources (RESs), has rendered conventional short-circuit current (SCC) calculation methods inadequate. This paper proposes a novel analytical model that explicitly incorporates the current-limiting control dynamics of voltage source converters to accurately determine SCCs. The key contribution is a simplified yet accurate formulation that captures the transient behavior during faults, offering a more realistic assessment compared to traditional quasi-steady-state approaches. The proposed model was rigorously validated through electromagnetic transient (EMT) simulations and large-scale case studies. The results demonstrate that the method reduces the SCC calculation error to below 4%. Furthermore, when applied to the real-world provincial power grids of ZJ and JS, all computations converged within 10 iterations, confirming its robust numerical stability. These findings offer valuable insights for protection coordination studies and verify the model’s effectiveness as a reliable tool for planning future power systems with high power-electronics penetration. Full article

Late-Archean seawater functioned as a vast, redox-tuned colloidal system for which its kinetics were largely governed by the surface chemistry of silica–iron nanoparticles. By reproducing Archean seawater (≈0.7 M ionic strength, 25 °C) in laboratory anoxic-to-mildly oxic reactors, the ζ potential (zeta-potential(ζ)) of silica–iron nanoparticles was investigated, and we tracked how transient O₂ pulses (≤9 mg L⁻¹) regulated it. The zeta (ζ) potential was applied as the key diagnostic parameter to quantify both the sign of the ζ potential and the colloidal stability of simulated silica–iron particles in dispersion. Under strictly anoxic conditions, silica colloids (SiO₂(aq)) exhibit a persistently negative ζ potential (ζ ≈ −25 mV) in the simulated seawater (pH 6.5), arising from deprotonated silanol groups (≡Si–O⁻). Upon the addition of Fe²⁺, the inner-sphere complexation of ferrous ions on SiO₂ colloids partially replaces ≡Si–O⁻ with ≡Si–O–Fe⁺/≡Si–O–Fe–OH sites; the net negative charge density at the outer Stern plane nevertheless increases, and the ζ potential shifts from −25 mV to −30 mV. As the simulated seawater was oxygenated, the dissolved and surface-bound Fe²⁺ ions were oxidized to Fe³⁺, causing the ζ potential to exceed −30 mV. This study demonstrates that Fe²⁺–silica interactions generate electrostatic destabilization, suspending micron-scale aggregates and thus modulating the solubility and speciation of SiO₂ in early oceans. Also, transient micro-oxic pulses are shown to shift silica–iron colloids between metastable aggregation and dispersion by modulating their ζ potential. Subsequently, AFM and TEM were used to characterize the morphological changes in the colloidal particles from the liquid state to the dry state. Furthermore, infrared and XPS analyses were conducted on the colloidal samples. These findings provide certain reference significance for reconstructing the chemical evolution process of seawater in the Late-Archean period and for understanding the factors influencing the silicon–iron cycle of seawater in the Late-Archean era. Full article

Deep learning on graphs has emerged as a leading paradigm for intrusion detection, yet its performance in optical networks is often hindered by sparse labeled data and severe class imbalance, leading to an “under-reaching” issue where supervision signals fail to propagate effectively. To address this, we introduce Pseudo-Metapaths: dynamic, semantically aware propagation routes discovered on-the-fly. Our framework first leverages Beta-Wavelet spectral filters for robust, frequency-aware node representations. It then transforms the graph into a dynamic heterogeneous structure using the model’s own pseudo-labels to define transient ‘normal’ or ‘anomaly’ node types. This enables an attention mechanism to learn the importance of different Pseudo-Metapaths (e.g., Anomaly–Normal–Anomaly), guiding supervision signals along the most informative routes. Extensive experiments on four benchmark datasets demonstrate quantitative superiority. Our model achieves state-of-the-art F1-scores, outperforming a strong spectral GNN backbone by up to 3.15%. Ablation studies further confirm that our Pseudo-Metapath module is critical, as its removal causes F1-scores to drop by as much as 7.12%, directly validating its effectiveness against the under-reaching problem. Full article

Thermodynamic fault diagnosis of marine steam turbines remains challenging due to non-stationary multivariate sensor data under stochastic loads and transient conditions. While conventional threshold-based methods lack the sophistication for such dynamics, existing data-driven Transformers struggle with inherent non-stationarity. To address this, we propose a hybrid DLinear–Transformer framework that synergistically integrates localized trend decomposition with global feature extraction. The model employs a dual-branch architecture with adaptive positional encoding and a gated fusion mechanism to enhance robustness. Extensive evaluations demonstrate the framework’s superiority: on public benchmarks (SMD, SWaT), it achieves statistically significant F1-score improvements of 2.7% and 0.3% over the state-of-the-art TranAD model under a controlled, reproducible setup. Most importantly, validation on a real-world marine steam turbine dataset confirms a leading fault detection accuracy of 94.6% under variable conditions. By providing a reliable foundation for identifying precursor anomalies, this work establishes a robust offline benchmark that paves the way for practical predictive maintenance in marine engineering. Full article

Distributed temperature sensing (DTS) has long been employed in the oil and gas industry to characterize reservoirs, optimize production, and extend well life. More recently, its application has expanded to geothermal energy development, where DTS provides critical insights into transient wellbore temperature profiles and flow behavior. A comprehensive understanding of such field measurements can be achieved by systematically comparing and interpreting DTS data in conjunction with robust numerical models. However, many existing wellbore models rely on steady-state heat transfer assumptions that fail to capture transient dynamics, while fully coupled wellbore–reservoir simulations are often computationally demanding and mathematically complex. This study aims to address this gap by developing a transient wellbore heat transfer model validated with DTS data. The model was formulated using a thermal-analogy approach based on the theoretical framework of Eickmeier et al. and implemented with a finite-difference scheme. Validation was performed by comparing thermal slug velocities predicted by the model with those extracted from DTS measurements. The results demonstrated strong agreement between modeled and measured slug velocities, confirming the model’s reliability. In addition, the modeled thermal slug velocity was lower than the corresponding fluid velocity, indicating that thermal front propagates more slowly than the fluid front. Consequently, this computationally efficient approach enhances the interpretation of DTS data and offers a practical tool for improved monitoring and management of geothermal operations. Full article

Multi-robot ensembles comprising several manipulators are commonly used in industrial settings to process non-deterministic flows of items loaded by an upstream source onto a shared transportation system. After the execution of a given task, the robots regularly deposit the items on a common output flow, which conveys the semi-finished material towards the downstream portion of the plant for further processing. The productivity and reliability of the entire process, which is affected by the plant layout, by the quality of the adopted scheduling and task assignment algorithms, and by the proper balancing of the input and output flows, may be degraded by random disturbances and transient conditions of the input flow. In this paper, a highly accurate event-based simulator of this kind of system is used in conjunction with a rollout algorithm to optimize the performance of the plant in all operating scenarios. The proposed method relies on a simulation of the plant that comprehensively considers the dynamic performance of the manipulators, their actual motion planning algorithms, the adopted scheduling and task assignment methods, and the regulation of the material flows. The simulation environment is built upon computationally efficient maps able to predict the execution time of the tasks assigned to the robots, considering all the determining factors, and on a representation of the manipulators themselves as finite state automata. The proposed formalization of the line balancing problem as a Markov Decision Process and the resulting rollout optimization method are shown to substantially improve the performance of the plant, even in challenging situations, and to be well suited to real-time implementation even on commodity hardware. Full article