Search Results (41)

Multivariate control charts (MCC) are widely used to detect out-of-control (OOC) situations in interrelated processes; however, they do not directly provide information about the source(s) of these signals. Although various methods for signal decomposition and interpretation have been proposed in the literature, most of them are limited to statistical interpretation and do not support automated signal classification. To overcome this limitation, an intelligent decision-support approach combining MCCs and machine learning for OOC signal classification has been developed. Interrelated cost and schedule performance indicators obtained through earned value analysis (EVA) were monitored by a Hotelling T² control chart. When an OOC signal occurred, the associated variable(s) were identified using the Mason–Young–Tracy (MYT) decomposition method, and the resulting MYT classifications were used as class labels for supervised learning of an artificial neural network (ANN). The Box–Behnken experimental design was used to determine the optimal network architecture and training hyperparameters of the ANN. The findings showed that the optimized ANN model achieved 93.33% classification accuracy, and the optimization model explained 85.14% of the variation in Mean Squared Error (MSE). The main contribution of this study is the integration of statistical signal decomposition and machine learning into a learning-based decision-support mechanism for the automated interpretation of MCC signals. The developed approach provides a systematic, practical decision-support tool for identifying which EVA-based performance parameter(s) are associated with an OOC signal in the monitoring of complex processes. Full article

Internal defects cause significant fluctuations in the dispersion of low-cycle fatigue life of titanium–aluminum alloy specimens under fully reversed strain control ($R_{\epsilon }=-1$) at room temperature. To accurately analyze the relationship between internal defects and low-cycle fatigue behavior, this study adopts an energy-based approach to investigate the variation patterns of plastic strain energy density (PSE) during low-cycle fatigue testing of specimens. Research has revealed that the decline process of plastic strain energy dissipation is distinctly divided into two stages, and the low-cycle fatigue life exhibits a pronounced nonlinear relationship with the plastic strain energy dissipation rate (PSEDR) during the first stage. Based on internal defect characteristics obtained from X-ray scans, a defect intensity parameter $K_{t\_micro}$ was proposed to establish a life prediction interval under the influence of internal defects. By correcting the stable plastic strain energy using stress concentration factors, the prediction error of the stable plastic strain energy model was reduced from a 3× error band to a 1.5× error band. The maximum relative error decreased from 132% to 34.30%, significantly narrowing the overall prediction error. Compared with the Mason–Coffin (M-C) model and the stable plastic strain energy model, the prediction accuracy is significantly improved. Full article

Polyalphaolefin (PAO)-based magnetic fluids are widely used in precision transmission systems for their excellent rheological and lubricating properties, but their stability and magnetic controllability under high-temperature and high-shear conditions remain a key challenge. In this work, a PAO2-based magnetic fluid was prepared via coprecipitation using a sequential modification strategy involving oleic acid and alkenyl succinimide. An energy competition model under multi-field coupling was established using the magnetothermal energy ratio ($\lambda$) and Mason number ($Mn$) to elucidate the system’s rheological behavior. The fluid shows significant shear-thinning behavior under zero magnetic field; a 60 kA/m magnetic field increases the relative viscosity by over 4 times at 5 s⁻¹, while the magnetoviscous effect becomes weak at shear rates over 500 s⁻¹ (corresponding approximately to $Mn$= 1). With increasing temperature, the field-induced viscosity enhancement decreases progressively as thermal disturbance becomes increasingly important. This work reveals the multi-field coupling rheological mechanism, and the results suggest that the OA/T154 modification strategy is a feasible route for obtaining a PAO-based magnetic fluid that remains dispersible and magnetically responsive under the tested conditions. The study provides theoretical and experimental support for the design of intelligent lubricating materials. Full article

This study analyzes the hydrodynamic characteristics of a short magnetorheological squeeze film damper, with emphasis on the fluid microstructure responsible for generating damping forces. The magnetorheological fluid contains non-Brownian spherical particles suspended in a non-magnetic Newtonian fluid. When exposed to a magnetic field, these particles form chain-like structures that restrict fluid motion. In this context, the Mason number characterizes the fluid microstructure and establishes the ratio of viscous to magnetic forces. The mathematical model for solving the flow field, which depends on the continuity and momentum laws, the Bingham rheological model, and boundary conditions at the interfaces, is solved analytically. The Reynolds equation determines the fluid pressure distribution and follows the Sommerfeld boundary condition. Mass imbalance induces chaotic rotor motion, resulting in lateral vibrations. As the journal squeezes the fluid, positive pressure develops, generating damping forces that dissipate vibration energy. The results in this research show that the Mason number significantly affects fluid pressure, which increases as magnetostatic forces exceed viscous forces. This increase in pressure produces damping forces that reduce rotor displacement. Additionally, both radial and tangential forces increase with particle volume fraction, in contrast to classical Newtonian behavior. These findings are relevant to the handling of magnetorheological fluids in vibration control mechanisms. Full article

With the increasing demand for high efficiency and high power density in photovoltaic power generation, triangular current mode (TCM) control has garnered significant attention due to its capability to achieve zero voltage switching (ZVS) for switches. However, TCM is inherently a variable-frequency control method. Traditional modeling approaches based on fixed-frequency assumptions neglect the non-linear characteristics and sideband effects introduced by frequency variations, failing to accurately describe the dynamic behavior of the system. This paper proposes a multi-frequency small-signal modeling method tailored for TCM inverters. Small-signal models characterizing the impact of duty cycle perturbations and frequency modulation perturbations on the output voltage are derived, and the joint effect of both the duty cycle and switching frequency is analyzed. On this basis, a loop gain expression incorporating sideband frequency components is derived using Mason’s gain formula. Finally, the proposed model is verified through simulation. The results demonstrate that, compared with the multi-frequency model, which only considers the effect of duty cycle control, the proposed multi-frequency model can more accurately predict the dynamic response of TCM inverters across a wide frequency range, providing a precise theoretical basis for the control system design of variable-frequency inverters. Full article

Interlocking Compressed Earth Blocks (ICEBs) offer a sustainable alternative to conventional fired-clay bricks but remain hindered by inconsistent geometric designs and limited standardization. This study develops a stakeholder-weighted Analytic Hierarchy Process (AHP) framework to evaluate and select the most suitable ICEB geometry for sustainable and seismic-ready construction in developing regions. Five evaluation criteria—size, weight, interlocking effectiveness, reinforcement/grout provision, and handling ergonomics—were prioritized based on expert input from masons, engineers, architects, and researchers. The synthesized results ranked the HiLo-Tec-type geometry highest, followed by Thai-Rhino, Auram, and Hydraform designs. Unit weight (0.289) and reinforcement capacity (0.261) emerged as dominant decision factors. Sensitivity analysis confirmed the robustness of rankings under varying weight perturbations. The AHP framework identifies the top-ranked geometry, whose structural performance was examined experimentally through a full-scale cyclic test on a grouted double-wythe ICEB wall, revealing enhanced ductility and residual strength compared with traditional brick masonry. The proposed framework demonstrates that selected ICEB geometry can balance ergonomic and structural performance while meeting seismic resilience demands. Beyond geometry selection, the model provides a replicable decision-support tool adaptable for regional material innovations in sustainable construction. Full article

Research has shown that attention plays a crucial role in developing mathematical problem-solving skills, particularly for students who struggle with non-routine tasks. Even basic operations require shifts in attention, underscoring the deep connection between attention and mathematical cognition. Attentional strategies are observable and can be developed with targeted scaffolding. This study aimed to enhance high school students’ attentional engagement in problem-solving through a structured intervention. Over an academic year, twelve struggling students in Grades 11 and 12 participated in three one-on-one sessions with a researcher, receiving focused instruction. These sessions encouraged reflection and attention by using the “CCRSRC” model: Connections (identifying similarity connections among the problems presented); Choice (the student deciding which problem to solve); Reflection (explaining the choice); Solving (an attempt is made); Repetition (repeating steps 1–4 as often as wished); and Choice (to end the repetition and move on). Mason’s theory of shifts of attention was used to examine learners’ attentional development. This article provides a detailed analysis of one intervention case, offering insight into how CCRSRC actions serve as catalysts for fostering learner attention. In addition to describing and characterizing a single case, the article summarizes the attention data of all learners involved in the individual intervention. Full article

This work analyzes the hydrodynamic behavior of a magnetorheological valve, considering the microscopic fluid characteristics to generate a damper force. The magnetorheological fluid is composed of ferromagnetic particles dispersed in a non-magnetic carrier fluid, whose mechanical resistance depends on the magnetic field intensity. In the absence of a magnetic field, the magnetorheological fluid behaves as a liquid whose viscosity depends on the particle volume fraction. Conversely, the presence of a magnetic field generates particle chain-like structures that inhibit fluid motion, thereby regulating flow in the control valve. The mathematical model employs the continuity and momentum equations, the Bingham model, and the boundary conditions at the solid–liquid interfaces to determine the flow field. The results show the fluid hydrodynamic response under different flow conditions depending on dimensionless parameters such as the pressure gradient, the field-independent viscosity, the yield stress, the particle volume fraction, the Bingham number, the Mason number, and the critical Mason number. For a pressure gradient of $\Gamma =-10$, the flow rate inside the valve (with particle volume fraction $\varphi =0.2$) results in ${\overline{Q}}_{T,x}=0.34$, $0.06$, and 0 when the magnetic field is 80, 120, and 160 kA m⁻¹, respectively. Likewise, when the magnetic field increases from 80 to 160 kA m⁻¹, the damping capacity increases by $88\%$ when $\varphi =0.2$ and $128\%$ when $\varphi =0.3$ compared to the Newtonian viscous damping. This work contributes to our understanding of semi-active damping devices for flow control. Full article

Products with complex structures are structurally intricate and involve multiple professional fields and engineering construction elements, making it difficult for a single contractor to independently develop and manufacture such complex structural products. Therefore, during the research, development, and production of complex products, collaboration between manufacturers and suppliers is essential to ensure the smooth completion of projects. In this process, a complex supply chain network is often formed to achieve collaborative cooperation among all project participants. Within such a complex supply chain network, issues such as delayed delivery, poor product quality, or low resource utilization by any participant may trigger the bullwhip effect. This, in turn, can negatively impact the delivery cycle, product cost, and quality of the entire complex product, causing it to lose favorable competitive positions such as quality advantages and delivery advantages in fierce market competition. Therefore, this paper firstly explores the mechanism of complex product manufacturing and the supply network of complex product manufacturing, in order to grasp the inherent structure of complex product manufacturing with a focus on identifying symmetrical properties among supply chain nodes. Secondly, a complex product supply chain network model is constructed with the Graphical Evaluation and Review Technique (GERT), incorporating symmetry constraints to reflect balanced resource allocation and mutual dependencies among symmetrical nodes. Then, from the perspective of supply chain, we focus on identifying the shortcomings of supply chain suppliers and optimizing the management cost of the whole supply chain in order to improve the quality of complex products, delivery level, and cost saving level. This study constructs a Restricted Grey GERT (RG-GERT) network model with constrained outputs, integrates moment-generating functions and Mason’s Formula to derive transfer functions, and employs a hybrid algorithm (genetic algorithm combined with non-linear programming) to solve the multi-objective optimization problem (MOOP) for joint optimization of delivery time, quality, and cost. Empirical analysis is conducted using simulated data from Y Company’s aerospace equipment supply chain, covering interval parameters such as delivery time [5–30 days], cost [40,000–640,000 CNY], and quality [0.85–1.0], validated with industry-specific constraints. Empirical analysis using Y Company’s aerospace supply chain data shows that the model achieves a maximum customer satisfaction of 0.96, with resource utilization efficiency of inefficient suppliers improved by 15–20% (p < 0.05) after secondary optimization. Key contributions include (1) integrating symmetry analysis to simplify network modeling; (2) extending GERT with grey parameters for non-probabilistic uncertainty; (3) developing a two-stage optimization framework linking customer satisfaction and resource efficiency. Full article

Vibration energy harvesting based on piezoelectric transducers is an attractive choice to replace single-use batteries in powering Wireless Sensor Nodes (WSNs). As of today, their widespread application is hindered due to low operational bandwidth and the conventional use of lead-based materials. The Restriction of Hazardous Substances legislation (RoHS) implemented in the European Union restricts the use of lead-based piezoelectric materials in future electronic devices. This paper investigates lithium niobate ($LiNb{O}_3$) as a lead-free material for a high-performance broadband Piezoelectric Energy Harvester (PEH). A single-clamped, cantilever beam-based piezoelectric microgenerator with a mechanical footprint of 1 cm², working at a low resonant frequency of 200 Hz, with a high piezoelectric coupling coefficient and broad bandwidth, was designed and microfabricated, and its performance was evaluated. The PEH device, with an acceleration of 1 g delivers a maximum output RMS power of nearly 35 μW/cm² and a peak voltage of 6 V for an optimal load resistance at resonance. Thanks to a high squared piezoelectric electro-mechanical coupling coefficient ($k^2$), the device offers a broadband operating frequency range above 10% of the central frequency. The Mason electro-mechanical equivalent circuit was derived, and a SPICE model of the device was compared with experimental results. Finally, the output voltage of the harvester was rectified to provide a DC output stored on a capacitor, and it was regulated and used to power an IoT node at an acceleration of as low as 0.5 g. Full article

This study explores the critical determinants impacting labor productivity in brickwork operations within the construction industry—a matter of academic and practical significance, particularly in the era of increasing human–robot collaboration. Through an extensive literature review on construction labor productivity, this study identifies factors affecting brickwork productivity. Data were collected from active construction sites during brick wall construction through on-site measurements and participatory observation, and the relative importance of these factors is determined using Principal Component Analysis (PCA)-factor analysis. The validity of the analysis is established through the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity, with a KMO value of 0.544 and significance at the 0.05 significance level. The analysis reveals four principal components explaining 75.96% of the total variance. Notably, this study identifies the Euclidean distances for the top factors: weather (0.980), number of helpers (0.965), mason competency (0.934), and number of masons (0.772). Additionally, correlation coefficients were observed: wall area had the highest correlation (0.998), followed by wall length (0.853) and height (0.776). Interestingly, high correlations did not necessarily translate to high factor importance. These identified factors can serve as a foundation for predictive modeling algorithms for estimating production rates and as a guideline for optimizing labor in construction planning and scheduling, particularly in the context of human–robot collaboration. Full article

In this work, the influence of gas–solid drag and heat transfer coefficient models on the prediction capacity of the Euler–Euler approach to simulate reactive bubbling fluidized bed flows is studied. Three different cases are considered, a non-reactive bidisperse bubbling fluidized bed flow (Case 1), and two reactive polydisperse flows in bubbling fluidized beds, one for biomass gasification (Case 2), and the other for biomass pyrolysis (Case 3). The Gidaspow, Syamlal–O’Brien, and BVK gas–solid drag models and the Gunn, Ranz–Marshall, and Li–Mason gas–solid heat transfer correlations are investigated. A Eulerian multiphase approach in a two-dimensional Cartesian domain is employed for the simulations. Computational results for the three cases are compared with experimental data from the literature. The results obtained here contribute to a better understanding of the impacts of such closure models on the prediction ability of the Euler–Euler approach to simulate reactive flows. The results indicate that, for the simulation of reactive flows in bubbling fluidized bed reactors, the kinetic modeling of the reactions has a global effect, which superposes with the influence of the drag and heat transfer coefficient models. Nevertheless, local parameters can be noticeably affected by the choice of the interface closure models. Finally, this work also identifies the models that lead to the best results for the cases analyzed here, and thus proposes the use of such selected models for gasification and pyrolysis processes occurring in bubbling fluidized bed reactors. Full article

Contrails are responsible for a significant proportion of aviation’s climate impact. This paper uses data from the European Centre for Medium-Range Weather Forecasts to identify the altitudes and latitudes where formed contrails will not persist. This reveals that long-lived contrails may be prevented by flying lower in equatorial regions and higher in non-equatorial regions. Subsequently, it is found that the lighter fuel and reduced seating capacity of hydrogen-powered aircraft lead to a reduced aircraft weight, which increases the optimal operating altitude by about 2 km. In non-equatorial regions, this would lift the aircraft’s cruise point into the region where long-lived contrails do not persist, unlocking hydrogen-powered, low-contrails operation. The baseline aircraft considered is an A320 retrofitted with in-fuselage hydrogen tanks. The impacts of the higher-altitude cruise on fuel burn and the benefits unlocked by optimizing the wing geometry for this altitude are estimated using a drag model based on theory proposed by Cavcar, Lock, and Mason, and verified against existing aircraft. The weight penalty associated with optimizing wing geometry for this altitude is estimated using Torenbeek’s correlation. It is found that thinner wings with higher aspect ratios are particularly suited to this high-altitude operation and are enabled by the relaxation of the requirement to store fuel in the wings. An example aircraft design for the non-equatorial region is provided, which cruises at a 14 km altitude at Mach 0.75 with a less than 1% average probability of generating long-lived contrails when operating at latitudes more than 35° from the equator. Compared to the A320, this concept design is estimated to have a 20% greater cruise lift–drag ratio, due to the 33% thinner wings with a 50% larger aspect ratio, enabling just 5% more energy use per passenger-km, despite fitting 40% fewer seats. Full article

The objective of this study was to examine the effect of pulling angle on time-zero mechanical properties of intact infraspinatus tendon or infraspinatus tendon repaired with the modified Mason-Allen technique in a canine model in vitro. Thirty-six canine shoulder samples were used. Twenty intact samples were randomly allocated into functional pull (135°) and anatomic pull (70°) groups (n = 10 per group). The remaining sixteen infraspinatus tendons were transected from the insertion and repaired using the modified Mason-Allen technique before being randomly allocated into functional pull or anatomic pull groups (n = 8 per group). Load to failure testing was performed on all specimens. The ultimate failure load and ultimate stress of the functional pulled intact tendons were significantly lower compared with anatomic pulled tendons (1310.2 ± 167.6 N vs. 1687.4 ± 228.2 N, p = 0.0005: 55.6 ± 8.4 MPa vs. 67.1 ± 13.3 MPa, p = 0.0334). For the tendons repaired with the modified Mason-Allen technique, no significant differences were observed in ultimate failure load, ultimate stress or stiffness between functional pull and anatomic pull groups. The variance of pulling angle had a significant influence on the biomechanical properties of the rotator cuff tendon in a canine shoulder model in vitro. Load to failure of the intact infraspinatus tendon was lower at the functional pulling position compared to the anatomic pulling position. This result indicates that uneven load distribution across tendon fibers under functional pull may predispose the tendon to tear. However, this mechanical character is not presented after rotator cuff repair using the modified Mason-Allen technique. Full article

To solve the problem of filter bandwidth in 5G communication, it is urgent to develop an acoustic resonator with a large effective electromechanical coupling coefficient (K_eff²). In this paper, the dependence between the resonance area and the performance of the bulk acoustic wave (BAW) resonator is studied. The solidly mounted resonators (SMRs) based on 43° Y cut lithium niobate (LN) were fabricated by the wafer transfer technique. The on-chip inductor was integrated with the BAW resonator through a pad electrode. Resonators with different resonant areas were fabricated and tested. Finite element modeling (FEM) simulation of acoustic resonators and electromagnetic (EM) simulation of layout were carried out, respectively. The Modified Butterworth Van Dyke (MBVD) model was used to analyze the results, and simulation of the Mason model was adopted. The results show that the dependency relationship between the resonant area and the effective electromechanical coupling coefficient can be induced by on-chip inductance. In the resonant area range of 20 × 20 μm²~160 × 160 μm², the K_eff² increases from 11.97% to 43.28%. Full article