Search Results (10,993)

Numerical simulations of (1) two aerosol types such as organic carbon (i.e., spherical) and dust (i.e., non-spherical) particles, and (2) their mixtures are carried out. Optical and microphysical parameters of these aerosols in our simulations are provided by MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2). The inversion routine is performed with TiARA (Tikhonov Advanced Regularization Algorithm) using the Lorenz–Mie (i.e., spherical) light-scattering model in unsupervised and automated, i.e., autonomous mode. The results of our numerical simulations show that the accuracy of the inversion results for the aerosol mixtures from synthetic optical data perturbed by ±10% random error is comparable to the accuracy observed for the inversion results of the “pure” spherical particles. In particular, the retrieval uncertainties of effective radius, and number, surface-area, and volume concentrations of these mixtures are ±30%, ±10%, between –50% and +100% and ±30%, respectively. However, we need to apply a modified version of the gradient correlation method (GCM) to stabilize the inversion results. The results of this study will form the baseline for future work, where we plan to apply TiARA to optical data products obtained from real lidar observations in the framework of the SCC (Single Calculus Chain) of EARLINET (European Aerosol Research Lidar Network). Full article

Epoxy–granite (EG) composites, comprising granite quarry waste and low-cost epoxy, present a sustainable alternative to cast iron for machine tool foundations. This study develops a data-driven simulation framework to enhance the mechanical properties of epoxy–granite systems by integrating published experimental data with Gaussian Process Regression (GPR) surrogate modeling and Bayesian optimization (BO). The objective is to maximize compressive strength and vibration damping—both critical factors for machining accuracy and dynamic stability. Experimental results from composites with 12–25 wt% epoxy and varied aggregate gradations demonstrate compressive strengths up to 76.8 MPa and flexural strengths reaching 35.4 MPa. The peak damping ratio of 0.0202 was observed at intermediate epoxy content. Mixtures enriched with fine particles also exhibited enhanced fracture toughness and low water absorption, outperforming cementitious concretes, polymer concretes, and natural granite. To address the limitations of experimental coverage, a GPR-based simulation model was employed to explore the four-dimensional design space defined by epoxy content and aggregate fractions. Integrated with BO under realistic manufacturing constraints, the framework identifies optimal formulations comprising 22–26 wt% epoxy and 55–70% fine aggregates. These compositions yield predicted compressive strengths of 78–85 MPa and damping ratios approaching 0.022, indicating significant improvement in overall mechanical properties. Bayesian Weibull analysis further quantifies reliability, revealing shape parameters α ≈ 2.4–2.9, which indicate consistent performance with moderate variability. This work presents the first reported application of an integrated GPR-BO-Bayesian Weibull simulation framework to epoxy–granite composites, enabling simultaneous optimization of conflicting objectives and probabilistic reliability assessment of key mechanical properties. The approach reduces experimental effort by over 70% and supports the circular economy through valorization of granite waste in high-value manufacturing. Nonetheless, predictive uncertainty remains high in under-sampled regions (e.g., damping with n = 2). Future experimental validation—comprising at least 10–15 data points across varied epoxy ratios and gradations—is essential to corroborate the predicted optimum. 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

To reduce random errors effectively and improve measurement precision in MEMS gyroscopes, we establish a dual-layer noise suppression method named EMD-SSA-VMD. The algorithm is grounded in empirical mode decomposition (EMD) and variational mode decomposition (VMD), incorporating the sparrow search algorithm (SSA) and entropy theory. The process starts by breaking down the signal into a series of intrinsic mode functions (IMFs) and a residual via EMD. By calculating the power spectral entropy (PSE) of IMFs, we can sort the signal components into three categories: noise signals, mixed signals, and effective signals. The mixed signals then undergo VMD processing, where SSA optimizes the key decomposition parameters. The sample entropy (SE) of the IMFs from VMD is computed to distinguish between actual signal components and noise. Finally, we combine all valuable signals to reconstruct the denoising signal. MATLAB(R2024b) simulation results show that this algorithm improves both the Signal-to-Noise Ratio (SNR) and the Root Mean Square Error (RMSE), demonstrating a more efficient removal of noise. Experiments on actual gyroscope data confirm these improvements, yielding higher SNR and a waveform that closely matches the original signal. This proves the algorithm’s practical value in engineering applications. Full article

The Electro-Hydraulic Servo Actuator for Active Suspensions (ASEHSA) plays a decisive role in shaping the holistic performance of vehicle suspension systems through its dynamic response speed and control precision. However, achieving high-performance control of ASEHSA still faces challenges. On one hand, existing model-based control methods are highly sensitive to parameter uncertainties and unmodeled nonlinear hydraulic dynamics, which can easily lead to reduced robustness in practical applications. On the other hand, traditional model-free strategies have limited time-delay compensation capabilities and often struggle to balance overshoot and settling time under delayed and disturbed conditions. To resolve this challenge, this study proposes an improved model-free adaptive control method that incorporates the differentiation of the tracking error (DE-IMFAC). Within the framework of traditional model-free adaptive control (MFAC), this approach reconfigures the time-delay term from an explicit form in the control law to implicit management, substantially mitigating the influence of time delays on system control performance. At the same time, by refining the performance criterion function and integrating a tracking error differentiation term together with dynamic weighting factors, the dynamic performance and adjustment flexibility of the controller are significantly enhanced. Additionally, by leveraging the characteristic equation of discrete autonomous systems and compression mapping theory, the BIBO stability of the DE-IMFAC control system and the monotonic convergence of the tracking error are rigorously established through theoretical analysis. Simulation and experimental results demonstrate that, compared with PID and traditional MFAC methods, DE-IMFAC significantly reduces integral absolute error, overshoot, settling time, and maximum position tracking error, while improving disturbance rejection capability. This approach does not depend on an accurate mathematical model of the ASEHSA system and maintains robust dynamic performance under complex operating environments characterized by time delays and data disturbances, providing a practical solution for ASEHSA and related industrial control systems. Full article

The increasing size and complexity of wind turbines have intensified the need for reliable real-time condition monitoring and health assessment. However, conventional numerical models often involve high computational demand, limiting their applicability for real-time digital twin implementation. This paper proposes a physics-based digital twin framework for the real-time health monitoring of a 3 MW class wind turbine. A physics-based numerical model was developed using Modelica 4.0.0 to simulate the electrical and mechanical behaviors of the wind turbine based on supervisory control and data acquisition (SCADA) inputs. Data preprocessing and wind speed calibration strategies were applied to reconcile nacelle-measured SCADA data with the turbine design specifications. Furthermore, reduced-order models (ROMs) were integrated with the physics-based numerical model to predict the thermal states of the generator and gearbox. Key operational parameters were selected through correlation analysis to enable accurate temperature prediction. Validation results demonstrate that the proposed digital twin accurately reproduces the dynamic behavior of the wind turbine, with the ROM-based temperature predictions showing agreement with SCADA measurements. The overall framework achieves a computation time within one second, indicating its suitability for real-time diagnostic and predictive maintenance applications. Full article

Electrical Resistivity Tomography (ERT) has proven to be a highly sensitive geophysical method for characterizing the dynamics of seawater intrusion. This study uses tank experiments to simulate seawater intrusion, utilizing electrical resistivity tomography to monitor real-time changes in groundwater resistivity during the intrusion process. The objective is to quantitatively reveal the development and evolution mechanisms of seawater intrusion wedges in sandy aquifers, thereby establishing a real-time resistivity monitoring method for groundwater distribution and migration characteristics. This study improves resistivity imaging data processing methods, enhancing both efficiency and accuracy. The refined cross-hole ERT technique is applicable not only to meter-scale indoor experiments; its optimized forward and inverse algorithms can also be directly transferred to regional-scale field monitoring. Experimental results show that the average resistivity in the study area continuously decreases from 57 Ω·m in the initial freshwater state to 1.1 Ω·m at the intrusion stabilization point. Areas with resistivity values below 20 Ω·m corresponded exactly to the brine intrusion zone. The evolution of the freshwater-saltwater interface unfolded in three stages: Initially, the density difference (0.025 g/cm³) dominated, with the saltwater intrusion depth at the aquifer base reaching 0.45 m, significantly exceeding the 0.04 m penetration at the upper section. During the intermediate stage, the interface morphology differentiated into an “upper triangular, lower arc-shaped” configuration. The bottom intrusion distance increased to 1.65 m, and the thickness of the brackish-freshwater mixing zone expanded from 0.1 m to 0.3 m. In the final stage, the interface stabilized and began intruding toward the surface, establishing a new hydrodynamic equilibrium. In addition, the migration rate of saline water at the aquifer base gradually decreased from 6.25 × 10⁻⁴ cm/s initially to 1.16 × 10⁻⁵ cm/s at steady state. These results reflect the dynamic coupling process between seepage and dispersion and demonstrate that this method enables effective real-time monitoring of seawater intrusion development and conditions, as well as early warning capabilities. Full article

This paper develops classical and Bayesian inferential procedures for Weibull exponential lifetime models under joint progressive Type-II censoring, motivated by comparative reliability analysis of products manufactured across multiple production lines. The theoretical framework is formulated for a general setting involving k independent Weibull exponential populations, allowing for flexible modeling of heterogeneous lifetime behaviors under a common censoring scheme. Maximum likelihood estimators and their asymptotic confidence intervals are derived, and Bayesian estimation is conducted using Markov chain Monte Carlo methods under both squared-error and LINEX loss functions. For numerical illustration and practical interpretability, the primary emphasis of the simulation study, expected-failure analysis, and real-data applications is placed on the two-population case (k = 2), which commonly arises in comparative life-testing scenarios such as the evaluation of two production lines or systems. Explicit expressions for the expected number of failures are presented for two populations, and their performance is examined through Monte Carlo simulations under various censoring schemes. The proposed methods are further illustrated using real datasets, demonstrating their applicability and effectiveness in reliability assessment. Overall, the results show that the proposed inferential procedures perform well under joint progressive censoring and provide a useful statistical framework for comparative reliability analysis, with methodology that naturally extends to general k-population settings. Full article

This work aims to shorten the time of lager beer fermentation through a temperature profile determined by a model-based controller, as an exploratory proposal to reduce fermentation time while maintaining yeast viability and process performance, without compromising the fermentation dynamics or negatively affecting the yeast activity. This study was developed from an engineering perspective focused on the optimization of the beer fermentation process through model-based control, preserving the beer properties of the original process. This exploratory work was carried out in four stages: (1) performance of constant temperature fermentations of a lager-type beer where concentrations of yeast and ethanol were monitored along the process, (2) model parameters adjustment and validation of a beer fermentation mathematical model on the basis of data obtained from experiments, (3) outline of a temperature trajectory, in a simulation framework, from an ethanol controller of movable convergence rate constructed with a nonlinear technique and the mathematical model, (4) experimental implementation of the outlined temperature trajectory in the beer fermentation. Beer batches’ quality-control endpoints suggested by Mexican quality standards frameworks, such as fermentation time, alcoholic and caloric content, and fermentation efficiency, were analyzed. The lag stage was reduced when the temperature profile devised by the controller was employed, resulting in a reduction in the time required to reach the stationary stage. No significant final characteristic variations in bottled beers brewed at constant and variable temperatures were identified. The quality assessment of the analyzed variables was conducted in accordance with the measurement capabilities of the employed equipment and under the applicable Mexican quality standards framework. This proposal presents an alternative systematic strategy to reduce the fermentation time of lager beer, favoring the efficiency and profitability of craft beer production. Full article

In the cold and arid regions of northern China, efficient water and nitrogen (N) management is critical for the sustainable production of leafy vegetables. Simplified models that estimate crop N and water transpiration demands using simple inputs based on climate parameters become an important method for making precise suggestions on N and irrigation application at a regional scale. This study developed and validated a regionally adapted version of the VegSyst model, named VegSyst-CH, based on a multi-year open-field experiment from 2021 to 2023. Model parameters were calibrated using data from the 2021 growing season and validated with independent datasets from 2022 and 2023. A critical N concentration (CNC) curve was established to describe the relationship between biomass accumulation and N content. VegSyst-CH, with a radiation use efficiency of 1.94 g MJ⁻¹, demonstrated high simulation accuracy for crop growth. The model showed a good predictive performance of N uptake under medium (N1) and high (N2) N treatments, with coefficients of determination (R²) above 0.80 across years and normalized root mean square error (NRMSE) values generally below 30%. The VegSyst-CH model also showed high accuracy in simulating crop evapotranspiration (ETc) over three consecutive growing seasons (2021–2023), with the dynamic trends of cumulative ETc closely aligning with measured values and the coefficients of determination (R²) consistently exceeding 0.90. These results validate the model’s robustness and applicability across different years. In conclusion, the VegSyst-CH model has strong spatiotemporal regulation capacity and climatic responsiveness, offering a robust decision support tool for precision fertilization and irrigation in open-field lettuce production in cold and arid regions. Full article

Profile conveyor belts are used in operational applications where the transport of bulk materials is required at high inclinations on conveyor belts, typically in the range of 30–40°. This paper deals with the analytical determination of the critical angle of inclination of a homogeneous transverse profile (protrusion), beyond which relative movement of bulk material occurs on the surface of the conveyor belt. The compressive forces induced by the known gravity component of the bulk material acting on a 20. mm high transverse protrusion were experimentally measured on a specially designed laboratory apparatus. The measurements were performed at different inclination angles of the folding plate, which simulated the working surface of the conveyor belt. During the experiments, the investigated bulk material—river gravel with a grain size of 4 ÷ 8 mm—was placed in a plastic frame with a width corresponding to the defined loading width of the conveyor belt. On the basis of the measured values of compressive forces, the static coefficient of shear friction in contact with grains of bulk material with two types of surfaces, namely plastic and rubber, was analytically determined. From the experimental data, the mean values of the static shear friction coefficient were determined, which were 0.33 for the plastic surface and 0.48 for the rubber surface, with the orientation of the protrusion perpendicular (90 deg) to the longitudinal axis of the conveyor belt. The experimental investigation also included the determination of the internal friction angle of the river gravel. The results show that when bulk material is conveyed by a profile conveyor belt, it is possible to safely convey material with a cross-sectional height greater than the height of the transverse protrusion, provided that the conveyor inclination angle does not exceed the internal friction angle of the bulk material. Full article

In clinical studies such as ophthalmologic or otolaryngologic research, bilateral correlated data frequently arise when outcomes are collected from paired organs or body parts. Since the measurements from such paired observations are usually highly correlated, appropriate data analysis requires accounting for the intra-class correlation. Methodological developments for analyzing bilateral data have been extensively studied over the past several decades, including both inferential procedures and computational strategies. In some analyses, the center effect or confounding effect could lead to imbalance among treatment arms, making it necessary to adjust for stratification/confounding factors in the data analysis. In this article, we develop three testing procedures for assessing the homogeneity of odds ratios in stratified bilateral correlated data under the assumption of a common correlation structure. Monte Carlo simulation studies are conducted to evaluate the performance of the proposed methods. The results indicate that the Wald-type test based on a log-linear hypothesis and the score test maintain robust type I error rates and achieve high power across a range of scenarios, and are therefore recommended for practical application. The proposed methodologies are further illustrated using two real data examples. Full article

Background/Objectives: Losartan, an angiotensin II receptor blocker (ARB) used to treat hypertension and heart failure, shows significant variability in pharmacokinetics (PK) and pharmacodynamics (PD) among individuals. Methods: In this study, we developed a physiologically based pharmacokinetic/ pharmacodynamic (PBPK/PD) model of losartan and its active metabolite, E3174, using curated data from 25 clinical trials. The model mechanistically describes the processes of absorption, hepatic metabolism, renal and fecal excretion, and pharmacodynamic blood pressure regulation. Simulation studies examined the effects of dose, hepatic and renal impairment, and genetic polymorphisms in cytochrome p450 2C9 (CYP2C9) and P-glycoprotein 1, also known as multidrug resistance protein 1 (MDR1) or ATP-binding cassette sub-family B member 1 (ABCB1), on the model. Results: The model successfully reproduced key PK/PD observations, including dose-dependent receptor blockade, attenuated responses with hepatic impairment, modest enhancement with renal impairment, and substantial variability in E3174 formation dependent on CYP2C9; the effects of ABCB1 were minimal. Specifically, dose dependency simulations confirmed the saturable nature of CYP2C9 metabolism, predicting a decreasing E3174-to-losartan ratio and a stronger, sustained suppression of blood pressure and aldosterone at higher doses. Hepatic impairment was predicted to lead to elevated losartan plasma concentrations (increased AUC) and attenuated metabolite formation, confirming the clinical need for dose reduction. Renal impairment simulations predicted stable losartan AUC but showed an overestimation of E3174 accumulation compared to observed data, where E3174 exposure remained stable. Genetic variability (CYP2C9) was the major determinant of response, with simulations confirming that reduced-function alleles lead to a 1.6- to 3-fold increase in losartan AUC and diminished blood pressure reduction. ABCB1 variability resulted in only minor modulation of systemic exposure and blood pressure effects. Conclusions: This mechanistic digital twin framework provides a quantitative basis for understanding variability in losartan therapy and supports its application in individualized dosing strategies. Full article

This paper presents a comprehensive study of statistical tests for comparing temporal point processes in general, with a particular focus on Poisson processes. We explore three key approaches: (1) an intensity-based test specifically for Poisson processes, (2) general parametric tests using the notion of maximum likelihood estimation, and (3) a general nonparametric test using the Isometric Log-Ratio (ILR) transformation. The first approach adopts a three-step procedure for comparing inhomogeneous Poisson processes by testing total and normalized intensities separately and then combining the corresponding p-values using Fisher’s method. The second method proposes a likelihood-based parametric test to examine the conditional intensity functions in point processes, emphasizing the application to Hawkes processes. Lastly, the third approach introduces a nonparametric test for general point processes, by transforming inter-event times into a Euclidean space via the ILR transformation, followed by conventional depth-based methods on multivariate data. We then conduct thorough studies on simulations as well as real-world data to illustrate these testing procedures and demonstrate their effectiveness. Full article

The wind and wave-induced Doppler shift (WDS) significantly affects the accuracy of ocean surface current fields retrieved from synthetic aperture radar (SAR). Understanding how different factors affect WDS is therefore essential for improving current inversion accuracy. Existing studies have predominantly focused on single-band WDS, mainly in the C-band, while investigations across other radar bands remain limited. In this study, we simulate the dynamic ocean surface height field and velocity field, and the radar backscatter from the ocean surface that includes the effect of breaking waves. Based on the Doppler shift theory of ocean surface motion proposed by Chapron, we develop a WDS simulation model with potential applicability to multiple radar bands. The performance of the model is verified by comparing its results with those from the CDOP, KaDOP and KuMOD models. The correlation coefficient between the proposed model and the CDOP model reaches 0.97, with mean deviation (MD), mean absolute error (MAE), and root-mean-square error (RMSE) not exceeding −2.07 Hz, 3.35 Hz, and 4.49 Hz, respectively. For comparisons with the KaDOP model, the correlation coefficient is 0.93, and the MD, MAE, and RMSE are within −21.23 Hz, 42.37 Hz, and 52.20 Hz. For comparisons with the KuMOD model, the correlation coefficient is 0.98, and the MD, MAE, and RMSE are within −2.60 Hz, 7.13 Hz, and 9.08 Hz. These results demonstrate that the proposed model can effectively predict the WDS for both C-, Ka-, and Ku-band radar returns. Furthermore, we investigate the impacts of radar parameters, including frequency band, polarization, and incidence angle, as well as wind field forcing on WDS, showing the model’s applicability across multiple radar bands. Finally, the proposed model is applied to current retrieval using Sentinel-1 ocean (OCN) data, and the inversion accuracy is assessed against collocated high-frequency (HF) radar observations. The MD, MAE, and RMSE of the current retrieval using the proposed model are −0.04 m/s, 0.26 m/s, and 0.32 m/s, which are close to those from the CDOP-based retrieval (MD, MAE, and RMSE of −0.02 m/s, 0.25 m/s, and 0.30 m/s). These results demonstrate that the proposed model performs well in ocean surface current inversion and shows potential for further application to ocean current retrieval based on radar data across different frequency bands. Full article