Search Results (519)

Building performance simulation is crucial for the design and optimization of sustainable buildings. However, the increasing complexity of building systems necessitates advanced modeling techniques capable of handling multi-domain interactions. This paper presents a novel application of the bond graph (BG) methodology to simulate and analyze the thermal behavior of an integrated trigeneration system within an experimental test cell. Unlike conventional simulation approaches, the BG framework enables unified modeling of thermal and hydraulic subsystems, offering a physically consistent and energy-based representation of system dynamics. The study investigates the system’s performance under both dynamic and steady-state conditions across two distinct climatic periods. Validation against experimental data reveals strong agreement between measured and simulated temperatures in heating and cooling scenarios, with minimal deviations. This confirms the method’s reliability and its capacity to capture transient thermal behaviors. The results also demonstrate the BG model’s effectiveness in supporting predictive control strategies, optimizing energy efficiency, and maintaining thermal comfort. By integrating hydraulic circuits and thermal exchange processes within a single modeling framework, this work highlights the potential of bond graphs as a robust and scalable tool for advanced building performance simulation. Full article

Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically aligns with peak irrigation periods. Despite this potential, photovoltaic pumping systems (PVPSs) often face reliability issues due to fluctuations in solar irradiance, resulting in frequent start/stop cycles and premature equipment wear. The IEC 62253 standard establishes procedures for evaluating PVPS performance but primarily addresses steady-state conditions, neglecting transient regimes. As the main contribution, the current paper proposes a non-intrusive, high-resolution monitoring system and a methodology to assess the performance of an isolated, high-power PVPS, considering also transient regimes. The system records critical electrical, hydraulic and environmental parameters every second, enabling in-depth analysis under various weather conditions. Two performance indicators, pumped volume efficiency and equivalent operating time, were used to evaluate the system’s performance. The results indicate that near-optimal performance is only achievable under clear sky conditions. Under the appearance of clouds, control strategies designed to protect the system reduce overall efficiency. The proposed methodology enables detailed performance diagnostics and supports the development of more robust PVPSs. Full article

Redwood (Sequoia sempervirens (Lamb. ex D. Don) Endl.) is a fast-growing, long-lived conifer native to a narrow coastal zone along the western seaboard of the United States. Redwood can accumulate very high amounts of carbon in plantation settings and continuous cover forestry (CCF) represents a highly profitable option, particularly for small-scale forest growers in the North Island of New Zealand. We evaluated the profitability of conceptual CCF regimes using two case study forests: Blue Mountain (109 ha, Taranaki Region, New Zealand) and Spring Creek (467 ha, Manawatu-Whanganui Region, New Zealand). We ran a strategic harvest scheduling model for both properties and used its results to guide a tactical-spatially explicit model harvesting small 0.7 ha units over a period that spanned 35 to 95 years after planting. The internal rates of return (IRRs) were 9.16 and 10.40% for Blue Mountain and Spring Creek, respectively, exceeding those considered robust for other forest species in New Zealand. The study showed that small owners could benefit from carbon revenue during the first 35 years after planting and then switch to a steady annual income from timber, maintaining a relatively constant carbon stock under a continuous cover forestry regime. Implementing adjacency constraints with a minimum green-up period of five years proved feasible. Although small coupes posed operational problems, which were linked to roading and harvesting, these issues were not insurmountable and could be managed with appropriate operational planning. Full article

Actuators and power electronics are fundamental components of modern control systems, enabling high-precision functionality, enhanced energy efficiency, and sophisticated automation. This study investigates evolving research trends and thematic developments in these areas spanning the last two decades (2005–2024). This study analyzed 1840 peer-reviewed abstracts obtained from the Web of Science database using BERTopic modeling, which integrates transformer-based sentence embeddings with UMAP for dimensionality reduction and HDBSCAN for clustering. The approach also employed class-based TF-IDF calculations, intertopic distance visualization, and hierarchical clustering to clarify topic structures. The analysis revealed a steady increase in research publications, with a marked surge post-2015. From 2005 to 2014, investigations were mainly focused on established areas including piezoelectric actuators, adaptive control, and hydraulic systems. In contrast, the 2015–2024 period saw broader diversification into new topics such as advanced materials, robotic mechanisms, resilient systems, and networked actuator control through communication protocols. The structural topic analysis indicated a shift from a unified to a more differentiated and specialized spectrum of research themes. This study offers a rigorous, data-driven outlook on the increasing complexity and diversity of actuator and power electronics research. The findings are pertinent for researchers, engineers, and policymakers aiming to advance state-of-the-art, sustainable industrial technologies. Full article

Steady-state visual evoked potential (SSVEP) paradigms are widely used in brain–computer interface (BCI) systems due to their reliability and fast response. However, traditional static stimuli may reduce user comfort and engagement during prolonged use. This study proposes a dynamic stimulation paradigm combining periodic motion trajectories with speed control. Using four frequencies (6, 8.57, 10, 12 Hz) and three waveform patterns (sinusoidal, square, sawtooth), speed was modulated at 1/5, 1/10, and 1/20 of each frequency’s base rate. An offline experiment with 17 subjects showed that the low-speed sinusoidal and sawtooth trajectories matched the static accuracy (85.84% and 83.82%) while reducing cognitive workload by 22%. An online experiment with 12 subjects participating in a fruit-slicing game confirmed its practicality, achieving recognition accuracies above 82% and a System Usability Scale score of 75.96. These results indicate that coordinated trajectory and speed modulation preserves SSVEP signal quality and enhances user experience, offering a promising approach for fatigue-resistant, user-friendly BCI application. Full article

This story began half a century ago with the discovery of an unusually high presence of tryptophan (Trp, W) in transthyretin (TTR), one of the three carrier proteins of thyroid hormones. With the Trp-rich retinol-binding protein (RBP), TTR forms a plasma complex implicated in the delivery of retinoid compounds to body tissues. W has the lowest concentration among all AAs involved in the sequencing of human body proteins. The present review proposes molecular maps focusing on the ratio of W/AA residues found in the sequence of proteins involved in immune events, allowing us to ascribe the guidance of inflammatory processes as fully under the influence of W. Under the control of cytokine stimulation, plasma biomarkers of protein nutritional status work in concert with major acute-phase reactants (APRs) and with carrier proteins to release, in a free and active form, their W and hormonal ligands, interacting to generate hot spots affecting the course of acute stress disorders. The prognostic inflammatory and nutritional index (PINI) scoring formula contributes to identifying the respective roles played by each of the components prevailing during the progression of the disease. Glucagon demonstrates ambivalent properties, remaining passive under steady-state conditions while displaying stronger effects after cytokine activation. In developing countries, inappropriate weaning periods lead to toddlers eating W-deficient cereals as a staple, causing a dramatic reduction in the levels of W-rich biomarkers in plasma, constituting a novel nutritional deficiency at the global scale. Appropriate counseling should be set up using W implementations to cover the weaning period and extended until school age. In adult and elderly subjects, the helpful immune protections provided by W may be hindered by the surge in harmful catabolites with the occurrence of chronic complications, which can have a significant public health impact but lack the uncontrolled surges in PINI observed in young infants and teenagers. Biomarkers of neurodegenerative and neoplastic disorders measured in elderly patients indicate the slow-moving elevation of APRs due to rampant degradation processes. Full article

Understanding the spatio-temporal evolution of farmland carbon emissions, disentangling their underlying driving forces, and exploring the decoupling relationship between these emissions and economic development are pivotal to advancing low-carbon and high-quality agricultural development in Shandong Province, China. Using the Logarithmic Mean Divisia Index (LMDI) and Tapio decoupling model, this study conducted a comprehensive analysis of panel data from 16 cities in Shandong Province spanning 2004–2023. This research reveals that the total farmland carbon emissions in Shandong Province followed a trajectory of “initial fluctuating increase and subsequent steady decline” during the study period. The emissions peaked at 29.4 million tons in 2007 and then declined to 20.2 million tons in 2023, representing a 26.0% reduction compared to the 2004 level. Farmland carbon emission intensity in Shandong Province showed an overall downward trend over the period 2004–2023, with the 2023 intensity registering a 68.9% decline compared to 2004. The carbon emission intensity, agricultural structure, and labor effects acted as inhibiting factors on farmland carbon emissions in Shandong Province, while the economic development effect exerted a positive driving impact on the growth of such emissions. Over the 20-year period, these four factors cumulatively contributed to a reduction of 2.1 × 10⁵ tons in farmland carbon emissions. During 2004–2013, the farmland carbon emissions in Zaozhuang, Yantai, Jining, Linyi, Dezhou, Liaocheng, and Heze showed a weak decoupling state, while in 2014–2023, the farmland carbon emissions and economic development in all cities of Shandong Province showed a strong decoupling state. In the future, it is feasible to reduce farmland carbon emissions in Shandong Province by improving agricultural resource utilization efficiency through technological progress, adopting advanced low-carbon technologies, and promoting the transformation of agricultural industrial structures towards “high-value and low-carbon” designs. Full article

Hydraulic tomography (HT) based on the successive linear estimator (SLE) offers the high-resolution characterization of aquifer heterogeneity but conventionally requires prolonged pumping to achieve steady-state conditions, limiting its applicability in contamination-sensitive or low-permeability settings. This study bridged theoretical and practical gaps (1) by identifying spatial periodicity (hole effect) as the mechanism underlying divergences in steady-state cross-correlation patterns between random finite element method (RFEM) and first-order analysis, modeled via an oscillatory covariance function, and (2) by validating a novel short-term sampling strategy for SLE-based HT using field experiments at the University of Göttingen test site. Utilizing early-time drawdown data, we reconstructed spatially congruent distributions of hydraulic conductivity, specific storage, and hydraulic diffusivity after rigorous wavelet denoising. The results demonstrate that the short-term sampling strategy achieves accuracy comparable to that of long-term sampling strategy in characterizing aquifer heterogeneity. Critically, by decoupling SLE from steady-state requirements, this approach minimizes groundwater disturbance and time costs, expanding HT’s feasibility to challenging environments. Full article

This study evaluates and compares centralized and distributed reactive power compensation strategies using Static Var Compensators (SVCs) to enhance the performance of a high-voltage transmission system in the Caribbean region of Colombia. The methodology comprises four stages: system characterization, assessment of the uncompensated condition under peak demand, definition of four SVC-based scenarios, and steady-state analysis through power flow simulations using DIgSILENT PowerFactory. SVCs were modeled as Thyristor-Controlled Devices (“SVC Type 1”) operating as PV nodes for voltage regulation. The evaluated scenarios include centralized SVCs at the Slack node, node N4, and node N20, as well as a distributed scheme across load nodes N51 to N55. Node selection was guided by power flow analysis, identifying voltage drops below 0.9 pu and overloads above 125%. Technically, the distributed strategy outperformed the centralized alternatives, reducing active power losses by 37.5%, reactive power exchange by 46.1%, and improving node voltages from 0.71 pu to values above 0.92 pu while requiring only 437 MVAr of compensation compared to 600 MVAr in centralized cases. Economically, the distributed configuration achieved the highest annual energy savings (36 GWh), the greatest financial return (USD 5.94 M/year), and the shortest payback period (7.4 years), highlighting its cost-effectiveness. This study’s novelty lies in its system-level comparison of SVC deployment strategies under real operating constraints. The results demonstrate that distributed compensation not only improves technical performance but also provides a financially viable solution for enhancing grid reliability in infrastructure-limited transmission systems. Full article

As the demand for advanced cooling solutions increases with the rise in artificial intelligence and high-performance computing, efficient thermal management becomes critical, particularly for data centers and electronic systems. Triply Periodic Minimal Surface (TPMS) heat sinks have shown superior thermal performance over conventional designs by enhancing heat transfer efficiency. In this study, a novel Fischer–Koch-S (FKS) TPMS heat sink was experimentally tested with four porosity configurations, 0.6 (identified as P6), 0.7 (identified as P7), 0.8 (identified as P8), and a gradient porosity ranging from 0.6 to 0.8 (identified as P678) along the flow direction, under a mass flow rate range of 0.012 to 0.019 kg/s. Key thermal parameters including surface temperature, thermal resistance, heat transfer coefficient, and Nusselt number were analyzed and compared to the conventional straight-channel heat sink (SCHS) using numerical modeling. Among all configurations, the P6 design demonstrated the best performance, with surface temperature differences ranging from 13.1 to 14.2 °C at 0.019 kg/s and a 54.46% higher heat transfer coefficient compared to the P8 design at the lowest mass flow rate. Thermal resistance decreased consistently with an increasing mass flow rate, with P6 achieving a 31.8% reduction compared to P8 at 0.019 kg/s. The P678 gradient design offered improved temperature uniformity and performance at higher mass flow rates. Nusselt number ratios confirmed that low-porosity and gradient TPMS designs outperform the SCHS, with performance advantages increasing as the mass flow rate rises. To further enhance the experimental process, a deep learning model based on a Temporal Convolutional Network (TCN) was developed to predict steady-state surface temperatures using early-stage time-series data, to reduce test time and enable efficient validation. Full article

Digital control in UPS systems is currently the only reasonable way of controlling a voltage source inverter (VSI). The control frequency range is restricted to up to about 1 kHz owing to the output low-pass LC filter, which should also maintain the output voltage during one switching period for the step unload. The measurement channels in the low-pass frequency range can be modeled as delays equal to some switching periods. A reasonably high (about 50 kHz) switching frequency minimizes the delays of the measurement channels. Two control systems will be compared—the pure discrete control, in this case a one-sample-ahead preview deadbeat control (OSAP), and a discretized passivity-based control (PBC). The OSAP control is easy to realize, is very fast, and enables one to obtain a steady state in a restricted number of steps after disturbance. However, the single-input single-output deadbeat control version is useless because it depends very strongly on the parameters of the inverter. The multi-input single-output OSAP (MISO-OSAP) control is directly based on discrete state equations (we treat the output voltage, output current, and inductor current as the measured state variables) and works perfectly for the nonlinear rectifier RC load (PF = 0.7) in a system without delay. The version of this with a linear prediction of state variables by means of a full-order state Luenberger observer (MISO-OSAP-LO) will be used in systems with different delays and compared with the discretized MISO passivity-based control without prediction for relatively high switching frequency (about 50 kHz). The aim and the novelty of the paper are in enabling a choice between one of these control systems for high switching frequency VSI with delays in the measurement channels. Full article

For energy management systems, it is crucial to determine, in advance, the available energy from renewable sources to be dispatched in the next hours or days, in order to meet their generation and consumption goals. Predicting the photovoltaic power output strongly depends on accurate weather forecasting data and properly photovoltaic panel models. In this context, several traditional thermal models are expected to become obsolete due to the removal of the widely used Nominal Module Operating Temperature parameter, stated in the IEC 61215-2:2021 standard, according to reports of longer time periods in test data processing. The main contribution of the photovoltaic power estimation algorithm developed in this paper is the integration of an accurate procedure to calculate the hourly day-ahead power output of a photovoltaic plant, based on three simplified thermal models in steady state. These models are proposed and evaluated as remedial alternatives to the removal of the Nominal Module Operating Temperature parameter—a subject that has not been widely addressed in the related literature. The proposed estimation algorithm converts specific Numerical Weather Prediction data and solar module specifications into photovoltaic power output, which can be used in energy management applications to provide economic and ecological benefits. This approach focuses on rooftop-mounted mono-crystalline silicon photovoltaic panel arrays and incorporates a nonlinear translation of Standard Test Conditions parameters to real operating conditions. All necessary input data are provided for the analysis, and the accuracy of experimental results is validated using appropriate error metrics. Full article

Diagnostic systems for drive with AC motors of key importance for machine safety require the use of limitations related to the processing of measurement information. These limitations result in significant difficulties in assessing the technical condition of the object’s components. The article proposes the use of a combination of artificial intelligence techniques in the form of shallow and convolutional structures in the diagnostics of stator winding damage from an induction motor. The proposed approach ensures a high level of defect detection efficiency while using information preserved in samples from three periods of current signals. The research presents the possibility of combining the data classification capabilities of self-organizing maps (SOMs) with the automatic feature extraction of a convolutional neural network (CNN). The system was verified in steady and transient operating states on a test stand with a 1.5 kW motor. Remarkably, this approach achieves a high detection precision of 97.92% using only 600 samples, demonstrating that this reduced data acquisition does not compromise performance. On the contrary, this efficiency facilitates effective fault detection even in transient operating states, a challenge for traditional methods, and surpasses the 97.22% effectiveness of a reference system utilizing a full 6 s signal. Full article

Time-varying digital filters are widely used in dynamic signal processing applications, but their transient response can significantly impact performance, particularly in real-time systems. This study focuses on reducing transient time in time-varying filters through second-order section (SOS) optimization. By employing a numerical optimization approach, we selectively adjust the coefficients of a single SOS within a higher-order filter to minimize the transient period while maintaining overall stability. Using a sequential quadratic programming (SQP) algorithm, we determine a time-varying coefficient trajectory over a finite horizon, ensuring a rapid convergence to steady-state behavior. Experimental results demonstrate that this targeted coefficient adaptation reduces transient time by up to 80% compared to conventional static designs, with minimal computational overhead. Additionally, a comparative analysis with traditional linear time-invariant (LTI) filters highlights the advantage of this method in suppressing transient oscillations while preserving long-term filter characteristics. The proposed approach provides a practical and efficient strategy for enhancing filter responsiveness in applications requiring both stability and real-time adaptability. These findings suggest that selective time variation in SOS decomposition can be a valuable tool in digital filter design, improving efficiency without excessive memory or processing demands. Full article

Aluminum alloys, serving as critical structural materials in the aviation and aerospace industry, frequently endure variable amplitude loading under complex service conditions. The resulting non-steady-state crack propagation behavior directly impacts structural safety. This study considers the engineering application requirements of the 7055-T7751 aluminum alloy and conducts fatigue crack growth experiments on compact tensile specimens subjected to constant amplitude loading and periodic variable amplitude overloading conditions. The findings indicate that the 7055 aluminum alloy exhibits an instantaneous acceleration period under tensile overload, which is important in the comprehensive analysis of crack growth life. The experimental findings show no significant correlation between post-overload minimum crack growth rate deviation and thickness or crack size at overload, where the values are 50.3% and 94.8% at 1.4 and 1.7 R_OL, respectively. An analytical model for the crack growth increment a_ii during this period was developed. Additionally, the delay distance influenced by overloads a_d and the number of delay cycles N_d are identified as effective parameters for evaluating the retardation effects induced by overloading. Our comparative analysis of crack growth experimental data under varying overload ratios R_OL and specimen thicknesses B revealed that existing plastic zone models inadequately assess a_d, prompting the establishment of a corresponding evaluation model. By incorporating the parameters a_ii and a_d into the Wheeler model, a method for calculating the delay cycles N_d was constructed, which effectively captured the variation trend. Finally, an analysis of fractography revealed numerous secondary cracks within the overload damage zone, and the ductile fracture characteristics in this region were significantly weaker compared to areas subjected to fatigue loading. Full article