Search Results (915)

Novel universal bulk-fill composites with reversible addition–fragmentation chain-transfer (RAFT)-modulated polymerization continue the trend towards increasing simplification of the restoration process to facilitate the reconstruction of deep posterior restorations in 4 mm increments as well as anterior restorations through improved aesthetics. This study aims to assess the suitability of such materials for rapid curing (3 s) with high-radiant emittance in terms of degree of conversion (DC) and polymerization kinetics at relevant depths (2 mm vs. 4 mm). For this purpose, two newly introduced bulk-fill universal composites (Tetric^® plus Flow and Tetric^® plus Fill) were compared with already established fast-curing composites (Tetric^® Power Flow and Tetric^® Power Fill). DC was measured in real time over 300 s using ATR-FTIR spectroscopy. The temporal DC evolution was modelled using an exponential sum function. Novel bulk-fill composites showed DC results that were independent of the measured sample depth or curing mode. The polymerization kinetics of all composites are somewhat slower in the gel phase at moderate irradiance or when measured at deeper layers, but compensate for the differences in the glass phase, finally reaching equivalent DC values by the end of the 300-s observation period. These novel composites are therefore suitable for rapid curing (3 s) at high irradiance. Full article

Soft open point (SOP) offers a viable alternative to traditional tie switches for optimizing power flow distribution between connected feeders, thereby improving power quality and enhancing the reliability of distribution networks (DNs). Among existing medium-voltage (MV) SOP demonstration projects, the modular multilevel converter (MMC) back-to-back voltage source converter (BTB-VSC) is the most commonly adopted configuration. However, MMC BTB-VSC suffers from high cost and significant volume, with device requirements increasing substantially as the number of feeders grows. To address these challenges, this paper proposes a novel star-connected cascaded H-bridge (CHB) STATCOM SOP (SCS-SOP). The SCS-SOP integrates the static synchronous compensator (STATCOM) and low-voltage (LV) BTB-VSC into a single device, enabling reactive power support within feeders and active power exchange between feeders, while achieving reduced component cost and volume, simplified power decoupling control, and increasing power quality management capabilities. The topology derivation, configuration, operational principles, and control strategies of the SCS-SOP are elaborated. Finally, simulation and experimental models of a two-port 3 Mvar/300 kW SCS-SOP are developed, with results validating the theoretical analysis. Full article

Background/Objectives: Diffusion-weighted imaging (DWI) of the liver is prone to cardiac motion-induced signal dropout, which can be reduced using flow-compensated (FloCo) instead of monopolar (MP) diffusion encodings. This study examined differences in lesion detection capabilities between FloCo and MP DWI and whether visibility depends on lesion size and position. Methods: Forty patients with at least one known or suspected focal liver lesion (FLL) underwent FloCo and MP DWI. For both sequences, b = 800 s/mm² images were used to manually segment FLLs, which were then sorted by size and location (liver segment). The number of detected lesions, the sensitivity, and the contrast-to-noise ratio (CNR) were calculated and compared across sequences, sizes, and locations. Results: Significantly more lesions were detected using FloCo DWI compared to MP DWI (1211 vs. 1154; p < 0.001). In total, 1258 unique lesions were detected, 104 of which were identified only by FloCo DWI, and 47 of which only by MP DWI. The sensitivities of FloCo DWI and MP DWI were 96.3% (95% CI: 95.1–97.2%) and 91.7% (95% CI: 90.1–93.2%), respectively. The largest additional lesion found with only one of the two sequences measured 10.9 mm in FloCo DWI and 8.2 mm in MP DWI. In relative numbers, more additional FloCo lesions were found in the left liver lobe than in the right liver lobe (6.4% vs. 3.5%). The lesion CNR was significantly higher for FloCo DWI than for MP DWI (p < 0.05) for all evaluated size intervals and liver segments. Conclusions: FloCo DWI appears to enhance the detectability of FLLs compared to MP DWI, particularly for small liver lesions and lesions in the left liver lobe. Full article

Background/Objectives: To validate an artificial intelligence-based arterial input function (AI-AIF) deep learning model for myocardial blood flow (MBF) quantification during stress perfusion and assess its extension to rest perfusion, enabling myocardial perfusion reserve (MPR) calculation. Methods: Sixty patients with or at risk for vascular cognitive impairment, prospectively enrolled in the CRUCIAL consortium, underwent quantitative stress and rest myocardial perfusion imaging using a 3 T MRI system. Perfusion imaging was performed using a dual-sequence (DS) protocol after intravenous administration of 0.05 mmol/kg gadobutrol. Retrospectively, the AI-AIF was estimated from standard perfusion images using a 1-D U-Net model trained to predict an unsaturated AIF from a saturated input. MBF was quantified using Fermi function-constrained deconvolution with motion compensation. MPR was calculated as the stress-to-rest MBF ratio. MBF and MPR estimates from both AIF methods were compared using Bland–Altman analyses. Results: Complete stress and rest perfusion datasets were available for 31 patients. A bias of −0.07 mL/g/min was observed between AI-AIF and DS-AIF for stress MBF (median 2.19 vs. 2.30 mL/g/min), with concordant coronary artery disease classification based on the optimal MBF threshold in over 92% of myocardial segments and coronary arteries. Larger biases of 0.12 mL/g/min and −0.30 were observed for rest MBF (1.12 vs. 1.02 mL/g/min) and MPR (2.31 vs. 1.84), respectively, with lower concordance using the optimal MPR threshold (85% of segments, 72% of arteries). Conclusions: The AI-AIF model showed comparable performance to DS-AIF for stress MBF quantification but requires further training for accurate rest MBF and MPR assessment. Full article

Control valves are widely applied in nuclear power, offshore oil/gas extraction, and chemical engineering, but suffer from issues like pressure oscillation, flow control accuracy degradation, and motor overload due to unstable fluid loads (e.g., nuclear reactions in power plants and complex marine climates). This paper proposes a dual-motor redundant compensation method to address these challenges. The core lies in a control strategy where a single main motor drives the valve under normal conditions, while a redundant motor intervenes when load torque exceeds a preset threshold—calculated via the valve core’s fluid load model. By introducing excess load torque as positive feedback to the current loop, the method coordinates torque output between the two motors. AMESim and Matlab/Simulink joint simulations compare single-motor non-compensation, single-motor compensation, and dual-motor schemes. Results show that under inlet pressure step changes, the dual-motor compensation scheme shortens the stabilization time of the valve’s controlled variable by 40%, reduces overshoot by 65%, and decreases motor torque fluctuation by 50%. This redundant design enhances fault tolerance, providing a novel approach for reliability enhancement of deep-sea oil/gas control valves. Full article

The paper proposes a parallel transformerless (TL) static synchronous series compensator (SSSC) for the control of power flow along the power distribution lines under balanced or unbalanced voltages. This new SSSC configuration offers the advantages of a fast dynamic response, light weight, and high efficiency. By connecting multiple SSSCs in parallel, the current rating is increased, which improves the grid power transfer capabilities and flexibility. However, there may be circulating current flowing between the parallel-connected inverters, hence causing losses. A modified model predictive control scheme is thus developed, which ensures that the proposed SSSC accurately tracks the reference currents while effectively mitigating the circulating current. The model and cost function of the controller are derived and analyzed in the paper. A real-time simulation of a power line with the parallel TL SSSC controlled by a hardware-in-loop (HIL) DSP is developed to validate the performance of this device under both balanced and unbalanced line voltages. Full article

Long-term multivariate time series forecasting is crucial for real-world applications, including energy consumption, traffic flow, healthcare, and finance. Usually, some statistical approaches are used for predicting future observations based on historical temporal data. Recently, transformer-based models with patch mechanisms have demonstrated significant potential in enhancing computational efficiency. However, their inability to fully capture intra-patch temporal dependencies often limits the accuracy of predictions. To address this issue, we propose the Frequency Compensation Patch-wise transFormer (FCP-Former), which integrates a frequency compensation layer into the patching mechanism. This layer extracts frequency-domain features via Fast Fourier Transform (FFT) and incorporates them into patched data, thereby enriching patch representations and mitigating intra-patch information loss. To verify the feasibility of this model, FCP-Former was conducted on eight benchmark datasets via PyTorch 2.4.0 and trained on an NVIDIA RTX 4090 GPU (Santa Clara, CA, USA). Results demonstrate that FCP-Former 48 optimal experiment results and 17 suboptimal experiment results across all datasets. Especially on the ETTh1 dataset, it achieves an average MSE of 0.437 and an average MAE of 0.430, while on the Electricity dataset, it achieves an average MSE of 0.186 and an average MAE of 0.277. This demonstrates that FCP-Former has better forecasting accuracy and a superior ability to capture periodic and trend patterns. Full article

Loop heat pipes are efficiently two-phase heat transfer devices in the field of aircraft thermal management. To investigate the startup behavior and thermal instability of loop heat pipes under acceleration force, this study designed a novel loop heat pipe featuring two visual compensation chambers and a visual condenser. Elevated acceleration experiments were conducted across four different heat loads, acceleration magnitudes, and directions. The heat load ranged from 30 W to 150 W, while the acceleration magnitude varied from 1 g to 15 g, with four acceleration directions (A, B, C, and D). The startup behavior, thermal instability, internal flow pattern, and phase distribution were analyzed systematically. The experimental results reveal the following: (i) The startup behaviors vary across the four acceleration directions. In direction A, startup is more difficult due to additional resistance induced by the acceleration force. In direction C, startup time generally decreases with increasing heat load and acceleration up to 7 g. The longest startup time observed is 372 s at 30 W and 11 g. (ii) At high heat load, periodic temperature fluctuations are observed, particularly in directions B and C. Simultaneously, the vapor–liquid phase interface in the condenser exhibits periodic back-and-forth movement. (iii) The visual DCCLHP exhibits a loss of temperature control under the combined influence of high heat loads and acceleration force, often accompanied by working fluid reverse flow, periodic temperature fluctuations, or wick dry-out. Full article

Highway on-ramp merging areas represent critical bottlenecks that significantly impact traffic efficiency and sustainability. This paper proposes a novel Delay-Compensated Merging Control (DCMC) framework that addresses the practical challenges of cloud-based cooperative vehicle control under realistic communication conditions. The system integrates an efficient mixed-integer linear programming (MILP) model for trajectory optimization with a robust two-stage delay compensation mechanism. The MILP model coordinates mainline and ramp vehicles through proactive gap creation and speed harmonization, while the compensation framework addresses both deterministic and stochastic communication delays through Kalman filter-based prediction and real-time trajectory correction. Extensive simulations demonstrate that the DCMC system prevents traffic breakdown at near-capacity conditions (2200 vehicles per hour), achieving up to 31.6% delay reduction and 16.4% travel time improvement compared to conventional merging operations. The system maintains robust performance despite 2 s mean communication delays with 30 ms standard deviation, validating its readiness for practical deployment. By effectively balancing computational efficiency, safety requirements, and communication uncertainties, this research provides a viable pathway for implementing cloud-based cooperative control at highway merging bottlenecks to enhance both traffic flow efficiency and environmental sustainability. Full article

In petroleum production processes, the water used to maintain formation pressure often plays a key role and is pumped into injection wells to compensate for the pressure drop in the formation after oil extraction and displacement of the remaining petroleum products to the development well. The source of such water may be produced by waters extracted together with oil and previously purified from mechanical impurities and hydrocarbons. However, a significant disadvantage of using such water is the presence of pollutants such as sulphur-reducing bacteria (SRB) and a high content of hydrogen sulfide. Traditional purification methods against them show low efficiency. Hydrogen sulfide and SRB are not only a threat of environmental pollution, but they also pose a high risk to pipelines in the petroleum industry due to an increase in the rate of metal corrosion. In this paper, formation water was treated with a field deployment flow-mode plasma discharge unit. A significant decrease in the growth rate of SRB in treated water was achieved. Bacterial growth was suppressed for up to 14 days after three treatment cycles of treatment. The hydrogen sulfide content was reduced by 33% after one cycle of plasma discharge water treatment. Full article

Efficient and convenient intelligent online detection methods can provide important technical support for the standardization of processing flow in the tea industry. Hence, this study focuses on the key chemical indicators—tea pigments in the rolling process of black tea as the research object, and uses multi-source information fusion methods to predict the changes of tea pigments content. Firstly, the tea pigments content of the samples under different rolling time series of black tea is determined by system analysis methods. Secondly, the spectra and images of the corresponding samples under different rolling time series are simultaneously obtained through the portable near-infrared spectrometer and the machine vision system. Then, by extracting the principal components of the image feature information and screening characteristic wavelengths from the spectral information, low-level and middle-level data fusion strategies are chosen to effectively integrate sensor data from different sources. At last, the linear (PLSR) and nonlinear (SVR and LSSVR) models are established respectively based on the different characteristic data information. The research results show that the LSSVR based on middle-level data fusion strategy have the best effect. In the prediction results of theaflavins, thearubigins, and theabrownins, the correlation coefficients of the testing sets are all greater than 0.98, and the relative percentage deviations are all greater than 5. The complementary fusion of the spectrum and image information effectively compensates for the problems of information redundancy and feature missing in the quantitative analysis of tea pigments content using the single-modal data information. Full article

This paper seeks to provide a cost benefit analysis of the implementation of a vehicle-to-grid (V2G) charging strategy relative to a smart charging (V1G) strategy from the perspective of an individual electric vehicle (EV) owner with and without solar photovoltaics (PV) located on their roof. This work utilizes a novel AC optimized power flow model (ACOPF) to produce distributed location marginal prices (DLMP) on a modified IEEE-33 node network and uses a complete set of real-world costs and benefits to perform this analysis. Costs, in the form of the addition of a bi-directional charger and the increased vehicle depreciation incurred by a V2G strategy, are calculated using modern reference sources. This produces a more true-to-life comparison of the V1G and V2G strategies from the frame of reference of EV owners, rather than system operators, with parameterization of EV penetration levels performed to look at how the choice of strategy may change over time. Counter to much of the existing literature, when the analysis is performed in this manner it is found that the benefits of implementing a V2G strategy in the U.S.—given current compensation schemes—do not outweigh the incurred costs to the vehicle owner. This result helps explain the gap in findings between the existing literature—which typically finds that a V2G strategy should be favored—and the real world, where V2G is rarely employed by EV owners. Full article

During electron beam cold hearth melting (EBCHM) of Ti-6wt%Al-4wt%V titanium alloy, aluminum volatilization causes compositional segregation in the ingot, significantly degrading material performance. Traditional methods (e.g., the Langmuir equation) struggle to accurately predict aluminum diffusion and compensation behaviors, while computational fluid dynamics (CFD), although capable of resolving multiphysics fields in the molten pool, suffer from high computational costs and insufficient research on segregation control. To address these issues, this study proposes a CFD-machine learning (backpropagation neural network, CFD-ML(BP)) approach to achieve precise prediction and optimization of aluminum segregation. First, CFD simulations are performed to obtain the molten pool’s temperature field, flow field, and aluminum concentration distribution, with model reliability validated experimentally. Subsequently, a BP neural network is trained using large-scale CFD datasets to establish an aluminum concentration prediction model, capturing the nonlinear relationships between process parameters (e.g., casting speed, temperature) and compositional segregation. Finally, optimization algorithms are applied to determine optimal process parameters, which are validated via CFD multiphysics coupling simulations. The results demonstrate that this method predicts the average aluminum concentration in the ingot with an error of ≤3%, significantly reducing computational costs. It also elucidates the kinetic mechanisms of aluminum volatilization and diffusion, revealing that non-monotonic segregation trends arise from the dynamic balance of volatilization, diffusion, convection, and solidification. Moreover, the most uniform aluminum distribution (average 6.8 wt.%, R² = 0.002) is achieved in a double-overflow mold at a casting speed of 18 mm/min and a temperature of 2168 K. Full article

Chip-level cooling has become a thermal bottleneck in next-generation data centers. Although previous studies have optimized evaporator wick structures, they are limited to a single condensation path and ignore the combined effects of the loop heat pipe (LHP) orientation on the capillary wick (CW) replenishment and reflux subcooling. To bridge this gap, this study successfully designed an innovative flat-plate evaporator water-cooled LHP with a parallel condensation pipeline. Experiments were conducted with a 20 °C coolant and at a 4 L/min flow rate across nine orientations. The heat transfer characteristics of LHPs with parallel and series condensation pipelines were compared. The analysis focused on the relationship between the working fluid (WF) replenishment of the CW and the WF reflux temperature in the compensating chamber (CC). The experimental results demonstrated that the parallel condensation LHP could sustainably dissipate 750 W without thermal runaway. At this power, the minimum junction temperature of 82.34 °C was measured at orientation 2 (+60°). For low power and at the nine orientations, the series LHP generally had lower temperatures. However, when the power exceeded 600 W, the parallel LHP showed lower temperatures at orientations 1 (+90°), 2 (+60°), and 3 (+30°). At orientation 9, the parallel LHP had lower temperatures when the power surpassed 200 W. Theoretical analysis indicated that the orientation changes affected the heat transfer via the WF reflux temperature, reflux resistance, and CW replenishment rate. Furthermore, the LHP system we developed in this study is capable of fully satisfying the cooling requirements of data center server chips. Full article

This study investigates the hot deformation behaviour and flow stress prediction of metastable β-Ti-15Mo alloy, a promising material for biomedical applications requiring strength–modulus optimisation and thermomechanical tunability. Isothermal compression tests were performed within the temperature range of 923–1173 K and at strain rates of 0.17, 1.72, and 17.2 ${\mathrm{s}}^{-1}$ to assess the material’s response under industrially relevant hot working conditions. The alloy showed significant sensitivity to temperature and strain rate, with dynamic recovery (DRV) and dynamic recrystallisation (DRX) dominating the softening behaviour depending on the conditions. A strain-compensated Arrhenius-type constitutive model was developed and validated, resulting in an apparent activation energy of approximately 234 kJ/mol. Zener–Hollomon parameter analysis confirmed a transition in deformation mechanisms. Although microstructural and diffraction data suggest possible contributions from nanoscale phase transformations, including ω-phase dissolution at high temperatures, these aspects remain to be fully elucidated. The model offers reliable predictions of flow behaviour and supports optimisation of thermomechanical processing routes for biomedical β-Ti alloys. Full article