Search Results (6,914)

This paper investigates an Organic Rankine Cycle (ORC) system for low-to-medium temperature heat recovery using comparative thermodynamic, exergoeconomic and economic modelling. A working-fluid study considering environmental and thermodynamic perspectives is conducted. A 20 kW ORC unit is tested and used as a feasibility and trend-consistency reference to support the modelling assumptions and practical operating bounds. A parametric study then examines the effects of evaporator pressure, condensation temperature, superheat, subcooling and heat-exchanger pinch-point temperature differences on net power output, first- and second-law efficiencies, total product cost and total capital investment under prescribed boundary conditions. Multi-objective optimization is applied to identify Pareto-optimal trade-offs and representative compromise solutions. Results show an intermediate evaporator pressure maximizes net power output, while lower condensation temperature generally improves efficiency; superheat has limited efficiency impact but should ensure safe operation, and a small subcooling margin (around 3 °C) mitigates cavitation risk. The best overall performance is obtained with an evaporator pinch of 3 °C and a condenser pinch of 5–9 °C; tightening pinch constraints increases required heat-transfer area and makes heat exchangers the main cost bottleneck for high-efficiency solutions. Full article

Current onboard hydrogen storage systems are volumetrically inefficient and represent a major constraint on the driving range of heavy-duty fuel cell vehicles. This work presents a conceptual model of an internally reinforced Type I rectangular-shaped pressure vessel as a solution to enhance the volumetric efficiency of hydrogen storage in heavy-duty vehicles. The pressure vessel’s geometry incorporates an internal reinforcing structure to ensure both the structural integrity of the vessel and compliance with the standards for onboard hydrogen storage. Initially, an analytical approach was employed to determine the base parameters of the wall and the internal structure of the reinforced pressure vessel. Finite element analysis was then conducted to validate the analytical solutions and assess the structural integrity of the pressure vessel under design pressure conditions. This was followed by a parametric optimisation study in which the design parameters were systematically varied to identify an optimal pressure vessel design. The 35 MPa reinforced titanium pressure vessel offers 29% more volumetric capacity than the conventional Type IV storage system. The gravimetric capacity of the titanium pressure vessel is low, 2.9 wt%; despite this, the mass of the vessel is applicable in HDVs. This design increases hydrogen storage capacity, offering a range increase of approximately 29% for the same design space. Full article

Electroencephalogram (EEG) has been the gold standard for measuring epileptic activity in rodent models of epilepsy. Manual scoring of seizures in EEG recordings lasting from days to months is laborious and prone to human error. The existing literature on automatic seizure detection in rodent models of epilepsy is limited, and the electrographic characteristics of induced epilepsy significantly differ from those of other epilepsy types. This study employed a Light Gradient Boosting Machine (LightGBM), with the dataset carefully partitioned into separate training and testing sets to ensure no data overlap. The model was trained using five-fold cross-validation to enhance robustness and generalisability. The training, validation, and independent test sets comprised 29,722 h of EEG recordings from 102 mice with pilocarpine-induced temporal lobe epilepsy. Following feature selection, model training, and post-processing, the lightGBM-based model exhibited a sensitivity of 80%, a specificity of 99%, and an F1-score of 0.71 on the independent test set. Multiple pairwise and non-parametric statistical tests indicated that envelope, skewness, and kurtosis, identified as the three most significant features in the feature importance ranking, exhibit statistically significant differences in their distributions (p-value < 0.05). The statistical analysis revealed significant differences across the three features and between seizure and non-seizure events for each feature, highlighting their relevance for discriminating epileptic activity. This study highlights the potential to support the automation of seizure event detection in preclinical rodent models of epilepsy. Full article

Aiming at the insufficient integration of real-gas effects and the unclear parameter influence mechanisms in predicting high-pressure hydrogen leakage flame length, this paper proposes a refined predictive model that systematically incorporates the real-gas critical flow factor ($C_r^{*}$). By dynamically correcting the mass flow rate calculation under high-pressure conditions, the model significantly improves prediction accuracy (relative error in mass flow rate < 3%). A parametric analysis reveals that the flame length is approximately three times more sensitive to the leakage orifice diameter than to the storage pressure ($L\propto D^{1.041}{P}_0^{0.347}$), providing a quantitative basis for inherent safety design. Validated by experimental datasets, the model demonstrates good accuracy. It can be employed for safety distance demarcation and risk assessment at hydrogen refueling stations and storage facilities. Full article

Gas ionization chambers face significant challenges in diagnosing laser-accelerated proton beams due to severe space charge effects induced by high peak currents and broad energy dispersion. These effects typically cause electric field distortion, signal saturation, and non-linear responses. In this study, we propose an optimized ionization chamber design that effectively mitigates space charge through a rigorous co-simulation approach. We combined ANSYS for macroscopic electrostatic field optimization with Garfield++ for microscopic charge transport modeling, explicitly incorporating ionization (Heed++) and electron drift/diffusion (Magboltz) processes. A systematic finite element modeling workflow—including gas volume meshing and the removal of dielectric components—was implemented to eliminate field non-uniformities and dielectric charging effects. Crucially, we validated the design’s performance against Boag’s theoretical recombination model. While theoretical calculations predict severe saturation (<80% efficiency) for standard chambers under high-flux conditions (10⁷ protons/pulse), our simulation results demonstrate a strictly linear response with charge collection efficiency consistently exceeding 99.85%. Parametric studies further confirm that the optimized geometry and operational parameters (high bias, low pressure) successfully suppress space charge accumulation, providing a robust solution for laser-driven beam diagnostics. Full article

This study investigates the development of a predictive model in simulations for assessing steel corrosion in determining corrosion-affected zones in reinforced concrete. A series of reinforced concrete cubes with varying degrees of corrosion were tested using a four-probe Wenner configuration. The experimental data showed a clear inverse relationship between ER and steel mass loss, with a strong negative correlation, highlighting the potential of ER as a corrosion indicator. A third-degree polynomial model was developed to predict the diameter of the corrosion-affected region based on steel mass loss and concrete cover, achieving high predictive accuracy. This model was validated using numerical simulation conducted in COMSOL Multiphysics, which replicated the experimental setup under steady-state conditions. Parametric studies further examined the effects of electrical conductivity ($\sigma$) and electrode spacing on the simulated results. The findings confirm that while $\sigma$ has a moderate impact, electrode spacing significantly influences the measured ER values. The study underscores the importance of incorporating variable parameters into simulation models to improve the accuracy and field applicability of ER-based corrosion assessments. Furthermore, the simulation framework developed in this study demonstrates how numerical modeling can enhance the interpretive value of ER measurements, supporting the advancement of non-destructive testing techniques aimed at improving corrosion monitoring and maintenance strategies. Full article

In large-scale medical data, the connection between hospital length of stay and medical expenses shows a complex and nonlinear relationship instead of a straightforward positive link. This study proposes a Cox–Log-Logistic–Copula joint modeling framework to describe the marginal distributions and latent dependence between the two variables. Specifically, a semi-parametric Cox proportional hazards model is used for hospitalization duration, while a Log-Logistic model handles medical costs. The two margins are flexibly coupled through a Copula function to capture dynamic variations in cost levels during different hospitalization stages. To address computational challenges in large datasets, this study also includes subsample correction and one-step adjustment algorithms, combined with parallel computing strategies, to enhance estimation efficiency and accuracy. Empirical results show that the length of hospital stays and medical costs are not always positively related. In some cases, higher medical expenses occur during shorter stays, suggesting possible over-treatment or uneven resource distribution. The proposed framework proves to have strong explanatory power in identifying nonlinear patterns in healthcare behavior and offers a new quantitative tool for optimizing medical resource allocation and controlling costs. Full article

Background/Objectives: To investigate and develop a non-invasive parametric radiomics model derived from dynamic contrast-enhanced MRI (DCE-MRI) time-intensity curve (TIC) kinetics for predicting breast cancer molecular subtypes (HR+/HER2−, HER2+ and triple-negative breast cancer). Methods: This multicenter retrospective study enrolled 935 female patients with histologically confirmed breast cancer who underwent pretreatment breast DCE-MRI from August 2017 to July 2022. Based on the wash-in rate (WIR) and the area under the TIC, the original multiphase DCE-MRI images were converted into two types of parametric images. Radiomics features were extracted from TIC-WIR and TIC-Area images and analyzed using low variance filtering, the elimination of highly correlated features, and the least absolute shrinkage and selection operator regression. The categorical boosting algorithm was employed to develop multiclass prediction models for breast cancer molecular subtyping. A TIC-Combined model was further established by integrating the calibrated probability outputs of the TIC-WIR and TIC-Area models using a decision-level fusion strategy. The discrimination, calibration, and interpretability of the models were evaluated in the study datasets. Results: The TIC-Combined model achieved superior predictive performance in both the internal validation set (micro-average AUC: 0.79, macro-average AUC: 0.77) and the external validation set (micro-average AUC: 0.77, macro-average AUC: 0.75). For subtype-specific classification by the TIC-Combined model, the highest one-vs-rest AUCs were 0.81 for triple-negative breast cancer in the internal validation set and 0.76 for HER2+ breast cancer in the external validation set. The TIC-Combined model also showed good calibration and high interpretability which ensured reliable predictions and provided clear insights into feature importance. Conclusions: Interpretable parametric radiomics from TIC-derived parametric maps links kinetic features to molecular phenotypes, enabling accurate and non-invasive classification of breast cancer molecular subtypes. Full article

This study presents a systematic investigation into the seismic performance of precast concrete shear walls using cold-extruded sleeve connections for reinforcement splicing. Quasi-static cyclic loading tests were conducted on a full-scale precast wall specimen and a cast-in-place reference wall to evaluate the influence of construction joint detailing on structural behavior. The experimental results show that the precast wall exhibited progressive crack propagation, stable energy dissipation, and slightly higher ultimate lateral load and deformation capacity compared to the cast-in-place counterpart. In contrast, the cast-in-place wall experienced abrupt failure due to concrete spalling and out-of-plane splitting, highlighting the critical importance of reinforcement continuity and joint configuration. To further investigate key design parameters, high-fidelity finite element models were developed in ABAQUS. Concrete was modeled using the Concrete Damaged Plasticity model, while steel rebars and sleeves were simulated with a bilinear constitutive law. The numerical simulations, validated against experimental data, achieved good agreement in terms of load-drift response, crack patterns, and stress distributions. A parametric study was conducted by varying the wall aspect ratio, axial compression ratio, and longitudinal reinforcement ratio in the boundary elements. The results indicate that both the aspect ratio and axial compression ratio have significant effects on lateral load capacity and drift capacity, whereas the reinforcement ratio in the boundary elements exerts a relatively minor influence. For walls with low shear-span-to-depth ratios and high axial compression, increasing both longitudinal and horizontal reinforcement leads to noticeable improvements in load-carrying capacity and ductility. These findings confirm the reliability of the cold-extruded sleeve connection system in precast shear wall applications. The study establishes a validated numerical framework for seismic performance prediction and provides practical guidance for optimizing the design of prefabricated walls. This contributes to enhancing structural safety and improving seismic ductility, thereby supporting the broader adoption of precast systems in sustainable construction. Full article

Background: In many inpatient settings, physician coverage is organized around single-attending responsibility, which can create challenges in supervision and workload distribution, particularly in procedurally intensive environments. To address these issues, our department introduced a junior–senior inpatient team model in which multiple physicians jointly share responsibility for hospitalized patients. This study examined physicians’ perceptions of how this restructuring influenced clinical workflow, supervision, and workload. Methods: We performed a mixed-methods cross-sectional survey two months after implementation. Twenty-two physicians (13 junior, 9 senior) completed five-point Likert-scale items and open-ended questions. Responses were analyzed using non-parametric group comparisons. Qualitative comments were examined thematically to identify recurring perspectives on supervision and workload. Results: Junior physicians reported more favorable perceptions across several domains. Significant differences between junior and senior physicians were observed for reassurance during off-site duties (p = 0.013) and perceived reduction in burden when managing critically ill patients (p = 0.002). Qualitative findings indicated that junior physicians experienced greater shared responsibility and easier access to consultation, whereas senior physicians described increased supervisory demands, responsibility extending beyond subspecialty areas, and heavier weekend or holiday duties. Both groups emphasized the importance of flexible patient redistribution during staffing variability. Conclusions: The junior–senior inpatient team model was associated with improved perceived accessibility of supervision and collective support for junior physicians while increasing supervisory demands on senior staff. These findings suggest the potential importance of workload-sensitive implementation strategies and explicit role definition when introducing physician team–based coverage in high-acuity inpatient settings. Full article

Background/Objectives: Robotic-assisted radical prostatectomy (RARP) is a standard treatment for localized and locally advanced prostate cancer; however, optimizing oncologic control while preserving urinary continence and erectile function remains challenging. Advances in preoperative imaging, molecular diagnostics, artificial intelligence (AI), and intraoperative assessment have the potential to refine surgical planning and execution. This review summarizes contemporary evidence on advanced imaging and intraoperative technologies used to optimize RARP outcomes. Methods: A narrative literature review was conducted of English-language studies published between 2015 and 2025 using PubMed/MEDLINE, Scopus, and Google Scholar. Studies evaluating multi-parametric and bi-parametric MRI, prostate-specific membrane antigen-based positron emission tomography/computed tomography (PSMA PET/CT), AI-assisted tumor modeling, and intraoperative histologic or molecular imaging techniques in the context of robotic-assisted radical prostatectomy were included. Evidence from randomized controlled trials, prospective and retrospective studies, technical feasibility reports, and expert consensus statements was reviewed. Results: MRI remains central to anatomic mapping and local staging but consistently underestimates true tumor extent, with implications for margin control. AI-assisted platforms improve tumor contouring accuracy and may meaningfully influence surgical decision-making. PSMA-based imaging enhances detection of extra-prostatic extension and nodal disease and shows early promise for ex vivo and intraoperative guidance. Intraoperative margin assessment techniques are supported by randomized evidence demonstrating improved functional outcomes without compromising short-term oncologic safety and emerging digital histologic technologies offer scalable alternatives for real-time margin evaluation. Conclusions: Integration of advanced anatomic, molecular, and intraoperative imaging technologies represents an evolving multimodal paradigm in RARP. Combined use of MRI, PSMA-based imaging, AI-assisted modeling, and rapid histologic assessment may enable more precise, individualized surgery that balances oncologic control with functional preservation. Further validation is required to define optimal implementation in routine clinical practice. Full article

Aluminum alloy tube–concrete composite columns have received increasing attention owing to their high strength-to-weight ratio and superior corrosion resistance compared with conventional steel–concrete composite columns. In this study, a refined finite element model is established to investigate the axial compression behavior of aluminum alloy tube–concrete long columns. The results indicate that the axial bearing capacity and deformation characteristics are strongly governed by the confinement effect provided by the aluminum alloy tube, which varies significantly with different cross-sectional configurations. Circular and square aluminum alloy tubes exhibit distinct confinement mechanisms, leading to different stress distributions and damage evolution patterns in the core concrete. Enhanced confinement effectively improves the utilization of concrete strength and delays local buckling of the aluminum alloy tube, thereby contributing to an increase in axial bearing capacity. Furthermore, parametric analyses clarify the combined influence of material properties and geometric parameters on the confinement efficiency and overall axial compression performance of the composite columns. Full article

Parametric simulation is an effective engineering tool for addressing sustainability challenges, yet small-scale thermal comfort assessment remains limited by plugin-hybridizing complexities and workflow inefficiencies. To address these limitations, here we propose a novel comparative workflow that integrates Lands Design and Dragonfly with the assistance of Ladybug-only (LB) and Honeybee (LB&HB) in the Grasshopper model to predict the Universal Thermal Climate Index (UTCI) as the primary indicator. A playground was selected as a sample site to provide a comprehensive training dataset for the extremely hot summer period. Sensitivity analysis was conducted to assess the impact of input uncertainties on model predictions, and the simulation model’s performance was validated against urban–rural microclimate parameters and the calculated UTCI. Among the microclimate results tested, the wind speed and air temperature predictions achieved the highest accuracy (STDE: 0.10 m/s, 0.20 °C). The UTCI simulation of the LB workflow exhibited a strong correlation between calculated UTCI values (R² = 0.90; p = 0.03). Moreover, the agreement between the LB and LB&HB workflows was strong, with simulated UTCI showing good consistency (R² = 0.70–0.80; r = 0.85–0.88). This framework successfully enables real-time UTCI heatmap analysis in simplified cubic neighborhoods. Additionally, it improves the temporal and spatial resolution of thermal predictions, providing designers with critical insights into the algorithms implemented in new workflows to facilitate urban simulation and parametric sustainability. Full article

This work presents a high-performance piezoelectric MEMS yaw gyroscope fabricated on a single-crystal silicon platform, which achieves a quality factor of 75 k—the highest reported to date among silicon-based piezoelectric gyroscopes. The device employs a wide annular resonator that operates at 132 kHz in the in-plane wineglass mode. To maximize transduction efficiency, we develop an analytical model that relates output charge to the area-integrated in-plane stress under modal deformation, and we use this model to guide parametric optimization of the annular width. The resulting geometry simultaneously enhances the mechanical quality factor and the piezoelectric coupling. A back-etching fabrication process is used to eliminate front-side release holes, thereby preserving structural continuity and suppressing thermoelastic damping. In open-loop rate mode operation with a native frequency split of 28 Hz, the gyroscope demonstrates an angle random walk of 0.34°/√h and a bias instability of 8.19°/h. These performance metrics are comparable to those of state-of-the-art lead zirconate titanate (PZT)-based annular gyroscopes, while the use of lead-free aluminum nitride as the transduction material ensures compliance with RoHS environmental regulations. Full article

This study addresses the problem of traffic congestion in large cities caused by long-term repairs of underground utility networks. An innovative mobile overpass is considered, which combines the functions of a vehicle and a temporary bridge, allowing passenger cars up to 3.5 t to pass directly over repair trenches without detours. The research focuses on optimizing the placement of overpass supports relative to the trench edge to reduce soil deformation and prevent trench wall instability. A numerical methodology is developed in ANSYS Workbench that integrates finite element analysis of the soil-support system with parametric optimization using the nonlinear Drucker–Prager elastoplastic model. The soil parameters are obtained from oedometer compression tests (KPr-1M) and direct shear tests (PSG-2M) on clayey soils and then used to calibrate the numerical model. The optimization results show that the optimal distance from the trench wall to the overpass support is L_min = 2.78 m, which is 13.5% greater than the initial design value. This modification reduces the maximum horizontal displacement of the trench wall by more than a factor of two and ensures compliance with the displacement criteria. Comparison between experimental and numerical compression curves yields an average deviation of 37.55%, with errors below 5% at higher stress levels, confirming that the Drucker–Prager model is suitable for engineering optimization of mobile overpass support placement on similar soils. The proposed methodology can be applied to the design and verification of temporary bridge systems operating above utility trenches in urban environments. Full article