Search Results (1,794)

Low and fluctuating root-zone temperatures constrain tomato productivity during winter greenhouse cultivation, yet the advantages of dynamic regulation over fixed-temperature control remain unclear. In this study, cherry tomato plants were subjected to an unregulated control (CK), three constant root-zone temperatures (15, 20, and 25 °C), and dynamic temperature treatment (DT). The experiment was conducted in a commercial winter greenhouse, where cherry tomato plants were grown in coconut coir and monitored from 70 to 145 days after transplanting, with five plants per treatment; root-zone temperature was regulated by circulating water through pipes embedded in the cultivation troughs. DT maintained root-zone temperature within 14.9–22.2 °C while reducing cumulative pump operating time by 11.45–21.23% relative to the fixed-temperature treatments. DT sustained high root activity during reproductive development, promoted dry-matter allocation to fruits, accelerated fruit expansion, and achieved the highest total and fourth-truss yields. In leaves, DT improved PSII photochemical performance, as indicated by increased PI_ABS and Φ_PSII and reduced DI₀/RC. It also maintained relatively low POD and SOD activities, comparatively high CAT activity during fruit expansion, and lower MDA accumulation, indicating reduced oxidative pressure and membrane lipid peroxidation. Transcriptomic responses were strongly stage-dependent, with the most pronounced changes occurring during fruit setting and expansion. Differentially expressed genes were mainly associated with auxin response, electron transfer, protein-disulfide reduction, cellular redox homeostasis, and phosphorylation-related processes. WGCNA further identified trait-associated modules linked to mitochondrial electron transport and oxidative phosphorylation, including eight candidate genes associated with respiratory complexes I, III, IV, and V. Collectively, dynamic root-zone temperature regulation improved the temporal matching between thermal supply and crop developmental demand, thereby sustaining root activity, optimizing leaf photochemical and redox status, and promoting dry-matter allocation to fruits. Transcriptomic and WGCNA analyses integrally indicate that mitochondrial electron transport and oxidative phosphorylation may participate in the leaf response to dynamic root-zone temperature regulation. Full article

Daily temperature variation associated with climate change can strongly affect the survival, development, and population growth of insect species. However, whether the amplitude of daily temperature fluctuation experienced during the early development of insects leads to carry-over effects across the later life stages remains insufficiently understood. Using the invasive pest Tuta absoluta, we exposed the eggs to different thermal regimes under two mean-temperature backgrounds (22 and 25 °C) and measured the immediate egg-stage responses and the subsequent carry-over effects. The immediate responses depended on mean temperature, consistent with the nonlinear shape of thermal performance curves. At 22 °C, the wide amplitude accelerated egg development and increased variation in developmental duration without significantly affecting egg survival. At 25 °C, the moderate amplitude accelerated development, whereas the wide amplitude partially reversed this acceleration and produced a steeper age-dependent increase in mortality. Temperature conditions experienced during the egg stage also generated pronounced carry-over effects: wide amplitudes reduced larval survival, shortened female adult longevity, and decreased fecundity, whereas male longevity remained comparatively stable—a pattern consistent with sex-specific sensitivity of adult fitness to early thermal history. The wide amplitude during the egg stage also reduced the intrinsic rate of increase and net reproductive rate. Thus, the thermal regime during the egg stage can suppress population growth through cross-stage effects and sex-dependent fitness responses. Models based only on mean temperature may overestimate population growth potential and mischaracterize phenology. Incorporating egg-stage thermal history and daily temperature fluctuation into phenological and demographic models could improve pest forecasting and integrated pest management decisions under climate change. Full article

The primary objective of a parabolic distributed solar collector system (P-DSCS) is to regulate fluid heat generation so that it tracks a reference trajectory despite non-uniform solar irradiance. Fractional-order proportional-integral-derivative (FOPID) controllers offer superior dynamic flexibility to handle these complex thermal transients. However, existing tuning strategies for P-DSCS collapse frequency-domain requirements into an optimization problem solved by standard algorithms, masking critical trade-offs between competing performances and omitting closed-loop stability verification. To overcome these limitations, this paper presents an original multi-objective optimization framework for FOPID controlled P-DSCS. The tuning problem is formulated as a three-objective Optimization Problem that simultaneously minimizes phase-margin slope sensitivity for iso-damping robustness, peak sensitivity for low-frequency disturbance rejection, and complementary sensitivity for high-frequency noise attenuation. The Multi-Objective Imperialist Competitive Algorithm (MOICA) extracts a three-dimensional Pareto front, offering optimal control trade-offs. Comparative simulations against PID and literature algorithms (Multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II)) validate the superior performance of the MOICA-FOPID framework. MOICA consistently outperforms all algorithms across all metrics, improving iso-damping robustness by 38.99%. It also reduces high-frequency noise by 25.66%, while enhancing low-frequency disturbance rejection by 10.87%. Moreover, the optimal MOICA-FOPID controller maintained superior robustness despite P-DSCS gain and time-constant fluctuations. Full article

Condition indicators derived from multivariate monitoring signals are widely used to characterize ordered changes in machine operating states. However, an indicator constructed in one operating state may fluctuate or even reverse its direction when the same representation is applied to another state. A monotonicity-constrained symbolic regression method is developed to construct an explicit condition indicator that preserves its direction across predefined operating states. Candidate expressions are generated by deterministic exhaustive enumeration in a designated root state and screened in one or more branch states without coefficient refitting. Global Spearman monotonicity describes the overall relation with observation order, and a segment match ratio identifies local directional reversals. The method is evaluated on a motor-operated valve tested under combined thermal, pressure, and vibration stresses, with closing specified as the root state and opening as the branch state, the two states being named by the actuation that is performed and separated in the recorded drive current. The selected indicator is dominated by a decreasing trend in both states and achieves monotonicity magnitudes of 0.872 and 0.887 and segment match ratios of 0.667 and 0.833 for closing and opening, respectively; its opening-state monotonicity exceeds those of the single-feature, PCA, autoencoder, and error-driven symbolic-regression baselines. Applied to screened data from one prototype valve without refitting, the fixed expression retains its overall direction. These results demonstrate that the proposed method constructs an explicit and interpretable condition indicator while preserving its direction across predefined operating states. The constructed quantity is an indicator of ordered operational change, not a wear measurement. Broader applicability to other electromechanical machines and state sets remains to be established. Full article

To advance the modernization of power systems, the role of hydropower has transitioned from mere energy generation to serving as both a primary energy provider and a critical flexibility resource. However, conventional day-ahead scheduling methodologies for cascaded hydropower often prove inadequate in mitigating the short-term power imbalances induced by renewable energy variability, primarily due to an oversimplification of operational constraints. To fully harness the regulatory potential of hydropower, this paper proposes an optimal day-ahead scheduling strategy for a cascade hydro-wind-solar-thermal-storage system incorporating hybrid pumped storage (HPS). First, leveraging the operational characteristics of HPS, this study evaluates its capacity for renewable energy accommodation and identifies key challenges in power balancing from the perspectives of water resource management and energy dispatch. Second, a collaborative optimization framework is established. By introducing the concept of an “allowable reservoir water level fluctuation range” within the day-ahead dispatch cycle, the framework constrains the deviation between the actual end-of-period water level and its predefined target, thereby ensuring strict adherence to medium-to-long-term operational boundaries. Finally, case studies conducted on a modified IEEE 33-node system demonstrate that the integration of HPS significantly enhances system regulation capabilities. The results confirm that the proposed strategy contributes to secure, economical, and low-carbon grid operation while maintaining reservoir sustainability. Full article

Modern power distribution grids are becoming increasingly complex due to dynamic network configurations, evolving customer behaviors, and fluctuating power demands. These factors introduce indirect spatial and temporal dependencies that critically affect voltage profiles, line loading, power losses, and overall system reliability. Consequently, grid operators require interactive decision-support tools to evaluate grid behavior under diverse operational scenarios. This paper presents ARGUS, an interactive agentic system for power distribution grid analysis based on the Model Context Protocol (MCP). The proposed framework enables operators to explore how modifications in grid configuration and load conditions influence key operational indicators, including bus voltages, line thermal limits, and network losses. By isolating the Large Language Model (LLM) to orchestration, intent recognition, and knowledge retrieval, all physical calculations are grounded in validated AC power-flow solvers and surrogate models. Demonstrated on the IEEE 33-bus system driven by empirical demand and DER profiles, ARGUS accelerates the detection and interpretation of operational bottlenecks, providing an auditable and trustworthy decision-support environment for modern distribution networks. Full article

This study examined the co-pyrolysis of high-density polyethylene (HDPE) and hydrochar from Camellia oleifera shell (HCS), focusing on thermal decomposition behavior, non-isothermal kinetics, thermodynamics, and the interaction mechanism between the two feedstocks. Hydrothermal carbonization raised the heating value of Camellia oleifera shell from 18.07 MJ/kg (raw CS) to 20.80 MJ/kg (HCS), confirming its fuel-upgrading effect, while HDPE alone reached 46.40 MJ/kg. TG-DTG analysis of HDPE, HCS, and their blends at five HCS:HDPE mass ratios (1:9, 3:7, 5:5, 7:3, and 9:1, denoted 1HCS9HDPE through 9HCS1HDPE) at 5–25 °C/min showed a single sharp decomposition stage for HDPE, a broader profile with much higher char yield for HCS, and non-additive DTG behavior in the blends, pointing to a synergistic interaction. Isoconversional kinetics (FWO, KAS, Starink, Friedman) showed activation energy rising steadily with conversion for HDPE (170–240 kJ/mol), a plateau-then-sharp-rise pattern for HCS (180–400 kJ/mol), and marked fluctuations at intermediate conversion for the balanced blends, a signature of composition-dependent synergy. Thermodynamic analysis (ΔH, ΔG, ΔS) confirmed an endothermic, non-spontaneous process throughout, with entropy trends mirroring the kinetic fluctuations. A hydrogen-radical transfer mechanism between HDPE- and hydrochar-derived intermediates is proposed to explain the reduced char yield and non-additive behavior of the blends. Overall, the results support hydrochar–HDPE co-pyrolysis as a viable route for combined agricultural and plastic waste valorization and provide kinetic and mechanistic data to guide co-pyrolysis process design. Full article

This study aims to investigate the coating properties of Stellite 21 powder laser-clad on 304 stainless steel substrates with different laser parameters, but under the same specific energy. The surface hardness of the coating was analyzed using a Vickers hardness tester and a nanoindenter instrument, while the microstructure and wear mechanisms were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Under the same laser energy density conditions, the 1260 W-540 mm/min process (S3) produced a fine equiaxed structure containing dispersed chromium-rich carbides. The coating surface achieved a maximum average microhardness of 420.51 HV_0.3, but its wear resistance was the worst, with a wear rate of 7.4 × 10⁻² μm³·N⁻¹·μm⁻¹. By comparison, the 1400 W-600 mm/min sample (S2) formed a relatively stable carbide network structure, exhibited the smallest fluctuation in friction coefficient, and had a lower wear rate of 5.2 × 10⁻² μm³·N⁻¹·μm⁻¹. The results indicate that identical laser energy density does not guarantee the same coating performance; the matching of power and scanning speed can significantly alter the thermal history and microstructural characteristics of the melt pool. Full article

Reliable thermo-mechanical performance is typically required in intensive thermal management applications, such as thermal energy storage systems and concrete-structured data centers; however, there is usually a trade-off between thermal conductivity and strength when designing thermally conductive concrete. To address the critical demand for concrete that combines high thermal conductivity with excellent structural stability after thermal loading, a novel multi-dimensional thermally conductive network was constructed by incorporating one-dimensional steel fibers and two-dimensional graphite-modified recycled aggregates to form a synergistic composite (SFRHCC). Results demonstrate that the thermal and mechanical stability of SFRHCC subjected to 200 °C was substantially improved compared with the unmodified reference. Specifically, after thermal treatment at 200 °C, SFRHCC restricted its thermal conductivity loss to only 7.6%, in stark contrast to the 28.2% reduction observed in ordinary recycled aggregate concrete (RAC). Furthermore, SFRHCC retained 92.0% and 91.3% of its reference compressive and splitting tensile strengths, vastly outperforming the unmodified reference (which retained only 75.0% and 72.4%, respectively). Both X-ray computed tomography (X-CT) and Euclidean distance transform (EDT) characterizations elucidate a high-density linear-planar overlapping network with an overall spatial connectivity of 9.94%, where the soft graphite coating layer accommodates thermal mismatch deformations and restricts volumetric fluctuations. This structural integrity effectively transforms the interfacial failure mode from simple weak-interface debonding to cohesive matrix tearing. These findings offer a promising materials design strategy for developing structural-functional integrated concrete for thermal management applications. Full article

Under the energy transition, renewable intermittency poses a challenge to supply–demand matching. Buildings possess thermal inertia that can serve as virtual storage. This study proposed a capacity-operation co-optimization model for a heating-season-integrated energy system, integrating building thermal inertia with thermal energy storage (TES). The building envelope was modeled as a first-order resistor–capacitor (RC) thermal network, and TES capacity was treated as a decision variable within a mixed-integer quadratic programming (MIQP) framework. The objective minimized total costs, including operating, TES investment, curtailment penalties, and demand response compensation, subject to power balance, thermal comfort, and renewable accommodation constraints. Four scenarios were compared to quantify the substitution effect. The results showed that building thermal inertia increased the net benefit by 23.87% by shifting heat supply to low-price periods. Capacity optimization reduced TES capacity from 600 kWh to 137.82 kWh, a 77.03% decrease. Building thermal inertia substituted 57.5% of the optimized TES capacity, corresponding to a 90.24% total capacity reduction relative to the fixed 600 kWh configuration, and this substitution effect may become more evident with larger thermal capacitance, smaller peak–valley price gaps, and wider temperature ranges, although these trends were not quantitatively analyzed in this study. The synergy of both measures lowered total cost by 22.73% and reduced TES cycling intensity and state-of-charge (SOC) fluctuations, which may help extend equipment life. These findings provided a quantitative basis for sizing TES in heating-season-integrated energy systems. Full article

A three-dimensional coupled finite element model incorporating the cutting tool, workpiece, and simulated impact pin was developed using ABAQUS/Explicit to investigate the machining behavior of Inconel 718 under conventional cutting and ultrasonic impact-assisted cutting conditions. Three ultrasonic impact trajectory spacings of 2, 3, and 4 mm were considered, where the trajectory spacing denotes the transverse distance between the centerlines of adjacent ultrasonic impact trajectories. Single-factor analyses were conducted by varying the cutting speed, depth of cut, and tool rake angle. The investigated cutting speeds ranged from 400 to 2000 mm/min, the depths of cut from 0.09 to 0.21 mm, and the tool angle from 10° to 30°. Experiments were performed using a KZUIT-20C ultrasonic system operating at 20 kHz with a 4 mm diameter impact head and a Mitsubishi MV820 CNC machine tool equipped with a titanium-alloy cutting tool. The numerical model was established based on the Johnson–Cook constitutive model and validated against experimentally measured cutting forces, with a maximum relative error of 11.23%. The results show that the ultrasonic impact trajectory spacing has a pronounced influence on the subsequent cutting-force response of Inconel 718. With increasing cutting speed, the X-direction cutting force generally increases under all investigated conditions, whereas the Y-direction force exhibits a more condition-dependent response. At a cutting speed of 2000 mm/min, the X-direction cutting forces under conventional cutting and 2, 3, and 4 mm trajectory spacings are 53.48, 56.38, 56.45, and 40.49 N, respectively. The 4 mm spacing consistently produces the lowest X- and Y-direction cutting forces over the investigated cutting-speed range. As the depth of cut increases, the X-direction cutting force generally increases, particularly at larger cutting depths, while the 4 mm condition maintains a comparatively low and smooth force response. The Y-direction cutting force shows stronger fluctuations depending on the trajectory spacing and cutting depth. Variation in tool angle produces relatively moderate changes in the X-direction force, whereas the Y-direction force exhibits a more pronounced condition-dependent response, including a localized increase under the 3 mm spacing condition. The residual stress and tool-temperature responses further demonstrate that the spatial distribution of ultrasonic impact trajectories affects the subsequent thermomechanical behavior of the machined material. Within the investigated parameter range, the 4 mm trajectory spacing generally maintains relatively low cutting-force levels and a comparatively stable thermal response. These results suggest that an appropriate separation between adjacent impact trajectories can reduce excessive interaction between neighboring impact-affected regions and thereby modify the mechanical resistance encountered during subsequent material removal. The present findings provide a numerical and experimental basis for selecting suitable ultrasonic impact trajectory spacing and machining parameters for the high-performance machining of Inconel 718. Full article

With the increasing penetration of renewable energy represented by wind and photovoltaic (PV) power in the power grid, the fluctuation amplitude of the net load curve is growing significantly, and the regulation capability of thermal power units can hardly accommodate such large fluctuations. When the adjustable range fails to meet the net load fluctuations, power curtailment and deficit issues arise in the system. Deploying energy storage is a common method to addressing power curtailment and deficit. However, over-sizing the storage capacity leads to low utilization of the storage equipment, while under-sizing fails to effectively mitigate the curtailment and deficit issues. Addressing the insufficiency of regulation capacity in future power systems with high wind and solar penetration, this paper proposes an optimal energy storage capacity allocation method based on the characteristics of power curtailment and deficit. First, a characterization model for the regulation capacity of existing conventional power sources is constructed. Combined with the annual wind and PV output curves, the temporal distribution of annual curtailment and deficit events is quantified based on the existing regulation capacity. Second, an optimal energy storage capacity allocation method matching the power–energy characteristics of curtailment and shortage is developed to minimize storage investment and maximize the reduction in losses caused by curtailment and deficit. Finally, the proposed method is validated based on a full-cycle operation scenario of a provincial power grid. The results show that compared with traditional empirical sizing schemes, the proposed scheme increases the complete mitigation rate of curtailment and deficit events from 32.57% to 49.01%; compared with the extreme sizing scheme that completely covers the gaps, it avoids a massive investment of nearly 380 million RMB/year. In future scenarios with gradually increasing renewable energy penetration, both the optimal charge/discharge duration and the event mitigation rate derived by the proposed scheme increase steadily, demonstrating its significant guiding value for long-term planning. Full article

Background/Objectives: Titanium and its flagship alloy (Ti6Al4V) represent the clinical gold standard for orthopedic and dental implants; however, optimizing their surface architecture to serve as high-capacity, reliable platforms for localized therapeutic delivery remains a significant clinical challenge. In this study, we aim to establish a systematic design roadmap linking surface engineering parameters directly to functional drug delivery performance. Methods: To achieve this, a comparative investigation was performed to map the electrochemical growth kinetics, voltage-driven morphological evolution, and processing limits of TiO₂ nanotube (TNT) arrays developed on commercially pure titanium (CP-Ti) and Ti6Al4V substrates in an ethylene glycol-based electrolyte containing NH₄F. Anodization was carried out at three different potentials (40 V, 50 V, and 60 V) for 30 min, followed by structural and statistical evaluation. Results: Scanning electron microscopy (SEM) combined with Gaussian size-distribution modeling confirmed a strong linear correlation between applied potential and pore dimensions, expanding mean diameters from 59 nm to 88 nm on CP-Ti and from 56 nm to 96 nm on Ti6Al4V. Current–time (I-t) transient analysis revealed distinct growth kinetics, with Ti6Al4V exhibiting enhanced current fluctuations driven by the differential oxidation rates of its dual-phase (α + β) microstructure. Furthermore, post-anodization thermal annealing at 450 °C is identified as a necessary structural processing step to stabilize the amorphous layers into crystalline polymorphs, providing the essential capillary stress resistance required to prevent film delamination during fluidic drug loading (MgSO₄ simulation). Conclusions: By establishing a comprehensive parameter-property matrix, this study provides a practical design roadmap that categorizes specific anodization regimes for tailored pharmaceutical and biomedical functions, ranging from direct osteoblast adhesion (40–50 V) to superhydrophilic architectures structurally optimized for high-capacity drug delivery (60 V). Full article

Salt rock is an ideal host for compressed air energy storage (CAES) due to its low permeability, creep self-healing, and stable properties. Chinese bedded salt deposits have thin salt layers and frequent mudstone interlayers. The response law of surrounding rock under cyclic injection–production-induced temperature fluctuations and creep-fatigue loading remains unclear. This study combines experiments and simulations to investigate the mechanical behavior and damage evolution of salt rock and mudstone interlayers under temperature and cyclic loading. Uniaxial tests at 20 °C, 50 °C, and 80 °C reveal thermal softening of salt rock and thermal hardening of mudstone. Creep-fatigue tests under loading rates of 0.25, 1, and 2 kN/s show salt rock has residual strain of 0.9–1.375% after 30 cycles, dominated by viscoplastic creep, while mudstone has a residual strain of less than 0.1% and is dominated by elastic deformation. A thermo-mechanical model based on the Jintan cavern simulates 150 cycles. The temperature field reaches a dynamic equilibrium after 500 h with spatial non-uniformity. Displacements concentrate at cavern waist and interlayer interfaces. The simulated volumetric contraction is 6.28% after 150 operational days, providing a baseline for short-term stability assessment. This study reveals the contrasting mechanical responses of salt rock and mudstone and the resulting interface deformation incompatibility. These findings support the stability assessment and operational optimization of bedded salt cavern CAES. Full article

Ultrasound-assisted metal additive manufacturing (U-FAAM) has emerged as a promising in situ melt-pool regulation strategy for addressing the challenges of conventional metal additive manufacturing, including process instability, defect formation, and microstructural anisotropy. This review systematically summarizes recent progress in contact and non-contact ultrasound-assisted metal additive manufacturing from the perspective of acoustic energy delivery pathways. The interactions between ultrasonic excitation and melt-pool behavior, thermal transport, solidification-front evolution, defect formation, microstructural transformation, and mechanical performance are comprehensively discussed. Contact ultrasound approaches transmit acoustic energy through solid media. Cavitation can occur only when the melt-side acoustic pressure reaches the required threshold; under such conditions, cavitation-associated effects may act with acoustic streaming and inertial melt flow to enhance mixing, grain refinement, and defect mitigation. Non-contact ultrasound approaches provide improved geometric adaptability and mainly influence melt-pool evolution through acoustic streaming and cyclic pressure fluctuations. The relationships among ultrasonic input conditions, melt-side responses, solidification behavior, and final properties are critically analyzed. Furthermore, current limitations associated with acoustic energy attenuation, coupling efficiency, process scalability, and quantitative characterization of ultrasonic effects within the melt pool are highlighted. This review synthesizes current evidence for ultrasound-driven melt-pool control in the investigated fusion-based AM systems, particularly DED/LDED and WAAM, while recognizing the limited evidence for LPBF. Full article