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Metals exhibit diverse failure behavior under impact loading. In the context of fragment warheads, preformed fragments also undergo fracture and crushing behaviors when subjected to explosive loading, potentially diminishing the terminal effect and damage capability of the warhead. To address this issue, metal disks of varying impedance were applied to the far-exploding surface of the fragments, and their influence on fragment deformation behavior was examined. The experimental results revealed that when metal disks were attached to the far-exploding surface of the fragments, their fracture behavior changed, and the recovered fragments remained intact axially. Additionally, the axial length of the recovered fragments decreased as the impedance of the metal disk on the far-exploding surface increased. To elucidate the underlying mechanism of this experimental phenomenon, the variation in fragment pressure during the propagation process was calculated by employing theories of planar detonation waves and shock wave propagation in the study. The results indicate that when the impedance of the metal disks on the far-exploding surface is higher than that of the fragments, it leads to an increase in internal pressure and the formation of a compression zone within the fragments, thereby preventing fragment fracture. Conversely, lower impedance results in the formation of a tensile effect within the fragments. The theoretical and experimental results were consistent. Finally, based on the dimensional analysis, the dimensionless models were established to predict fragment deformation and internal pressure values influenced by the metal disk on the far-exploding surface. [ABSTRACT FROM AUTHOR]

Filters serve as core equipment to ensure the normal operation of micro-irrigation systems, with head loss and filtration efficiency serving as the two key indicators for evaluating performance. In this study, we used a pre-pump filter-pontoon mesh rotary filter as the research object and conducted physical model tests under the flow rate (798–1050 L1 h−1), sand content (0.5–2.5 g1 L−1), and aperture of the filter screen (0.125–0.180 mm). We then adopted range analysis, variance analysis (ANOVA), dimensional analysis, and the multiple linear regression (MLR) method to analyze the results. The results showed that the order of factors affecting the head loss of the assessment indices, from large to small, was as follows: flow rate, sand content, and aperture of the filter screen. The order of factors affecting the filtration efficiency of the assessment indices from large to small was as follows: sand content, flow rate, and aperture of the filter screen. Predictive models for head loss and filtration efficiency were developed, with coefficients of determination R2 of 0.969 and 0.954, and root mean square error (RMSE) values of 0.1041 and 0.0183. The model exhibited high accuracy and could be used to predict the head loss and filtration efficiency of the pontoon mesh rotary filter. In the test range, the optimal working condition of this filter was a flow rate of 930 L1 h−1, sand content of 2.0 g1 L−1, and 0.150 mm aperture of the filter screen. In addition, the head loss under this condition was 0.281 m, and the filtration efficiency was 84.01%. These results could serve as a reference for the further optimization and application of the pontoon mesh rotary filter, while also enriching the hydraulic performance and filtration performance of the pre-pump filter. [ABSTRACT FROM AUTHOR]

The widespread adoption of clear aligners in orthodontic treatments in recent years has necessitated a more precise examination of the mechanical properties of the devices currently available in orthodontics. Recent studies indicate that aligners, when exposed to the forces exerted during swallowing, undergo fatigue-like phenomena, leading to chip formation and cracks. The cumulative damage results in a compromised fit between the tooth and aligner, which is crucial for the effective execution of orthodontic treatment. Additionally, the formation of chips poses a potential risk to patients, as there is a possibility of inadvertently ingesting microplastics that become detached from the aligner over time. This study attempts to assess the release of microplastics from the aligners subjected to cyclic compressive loading. Three different aligners (Essix Ace, Ghost Aligner and Invisalign) are tested to simulate swallowing conditions over the aligner usage period. The mechanical performance is studied in terms of the energy absorbed by the aligner, which shows that the Essix Ace has a stable energy absorption behaviour, while the energy absorbed by the Invisalign is significantly higher than their counterparts. Ghost Aligner did not perform well in the cyclic compression tests. The microplastics (MPs) released by the aligners are examined under an optical microscope. A dimensional analysis based on k-means image segmentation and edge detection algorithm is developed to analyse the MPs. The dimensional analysis of the MPs revealed that the ingestion of the MPs released by all the three aligners does not pose a health risk. [ABSTRACT FROM AUTHOR]

Background: Mammographic breast density (MBD), a strong predictor of breast cancer, is highly influenced by body mass index (BMI) in childhood and early adulthood, but the mechanisms underlying these associations are not fully understood. Our goal is to identify biomarkers that mediate the associations of BMI at ages 10 and 18 with MBD in premenopausal women. Methods: This study consists of 705 premenopausal women who had their screening mammogram at Washington University in St. Louis, MO, and provided a fasting blood sample. Our comprehensive metabolomic and lipidomic profiling yielded complete data for 828 metabolites and 857 lipid species after imputation. We used Volpara to determine volumetric measures of MBD. We performed high dimensional mediation analysis using the HIMA R package, adjusted for confounders, to determine whether lipid species and metabolites mediate the associations of BMI at 10 and 18 with MBD. We applied a false discovery rate (FDR) p-value < 0.1. Results: Four metabolites (glutamate, β-cryptoxanthin, cortolone glucuronide (1), phytanate) significantly mediated the association of BMI at 10 with volumetric percent density (VPD), and two (glutamate, β-cryptoxanthin) mediated the association of BMI at 18 with VPD. Glutamate was the strongest mediator across time points. Glutamate mediated 6.7% (FDR p-value = 0.06) and 9.3% (FDR p-value = 0.008) of the association between BMI at age 10 and 18, respectively. Four lipid species (CER(18:0), LCER(14:0), LPC(18:1), PC(18:1/18:1)), mediated the association of BMI at 10 with VPD, while five lipid species (CER(18:0), LCER(14:0), PC(18:1/18:1), TAG56:5-FA22:5, TAG52:2-FA16:0) mediated the association of BMI at 18 with VPD. The strongest mediator was PC(18:1/18:1), which mediated 9.7%, (FDR-p = 0.009) and 7.7%, (FDR-p = 0.04) of the association of BMI at age 10 and 18 with VPD, respectively. Conclusions: Metabolites in amino acid, lipid, cofactor/vitamin, and xenobiotic super-pathways as well as lipid species across the phospholipid, neutral complex lipid and sphingolipid super-pathways mediated the associations of BMI in early-life and MBD in premenopausal women. This study offers insight into the biological mechanisms underlying the link between early-life adiposity and MBD, which can support future research into breast cancer prevention. [ABSTRACT FROM AUTHOR]

Thermoelectric heat dissipation systems offer unique advantages over conventional systems, including vibration-free operation, environmental sustainability, and enhanced controllability. This study examined the benefits of incorporating a thermoelectric cooler (TEC) into conventional heat sinks and investigated strategies to improve heat dissipation efficiency. A theoretical model introducing a dimensionless evaluation index ( r q ) is proposed to assess the system's performance, which measures the ratio of the heat dissipation density of a conventional heat dissipation system to that of a thermoelectric heat dissipation system. Here, we subjectively consider 0.9 as a cutoff, and when r q < 0.9 , the thermoelectric heat dissipation system shows substantial superiority over conventional ones. In contrast, for r q > 0.9 , the advantage of the thermoelectric system weakens, making conventional systems more attractive. This analysis examined the effects of engineering leg length ( L * ), the heat transfer allocation ratio ( r h ), and temperature difference ( Δ T ) on heat dissipation capabilities. The results indicated that under a fixed heat source temperature, heat sink temperature, and external heat transfer coefficient, an optimal engineering leg length exists, maximizing the system's heat dissipation performance. Furthermore, a detailed analysis revealed that the thermoelectric system demonstrated exceptional performance under small temperature differences, specifically when the temperature difference was below 32 K with the current thermoelectric (TE) materials. For moderate temperature differences between 32 K and 60 K, the system achieved optimal performance when r h ≥ − 2.4 + 1.37 e 0.019 Δ T . This work establishes a theoretical foundation for applying thermoelectric heat dissipation systems and provides valuable insights into optimizing hybrid heat dissipation systems. [ABSTRACT FROM AUTHOR]

In 2D or 3D tolerance analysis, a dimension chain involves a complex propagation of random deviations from individual parts to the controlled assembly requirement. This can be calculated by setting up complex mathematical models, possibly with the help of CAD-based software tools. The paper studies the feasibility of an alternative approach, which uses measurements on assemblies of 3D printed parts to estimate the coefficients of a linearized error propagation model. The analysis is structured as a designed experiment, where each dimension is varied in two levels resulting in two different printed parts. The experimental plan consists of building assemblies from selected combinations of parts and measuring the assembly dimension on each combination. Among the possible designs of the plan, the paper compares two methods based on finite differences and least squares. The comparison includes both simulations with randomly generated dimension chains and physical tests on simple cases. The results show that a least squares plan allows a significant improvement in the accuracy on the estimation of model coefficients compared to a finite difference plan, with just a marginally higher number of assembly combinations. However, dimensional and geometric deviations in the 3D printing process are shown to play a critical role, and criteria are suggested to reduce or compensate them. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) systems are fundamental in numerous advanced engineering applications, from aerospace to telecommunications, where precise system identification is critical for optimal performance. However, the identification of such systems often faces significant hurdles due to data scarcity, with existing approaches typically requiring substantial amounts of data for effective training. Addressing this challenge, this paper introduces a novel transfer learning framework designed specifically for MIMO system identification under conditions of limited data and inherent uncertainties. The proposed framework is applied to two case studies: the first in metal additive manufacturing, specifically the laser-blown powder-directed energy deposition as the source domain and the laser hot wire-directed energy deposition as the target domain, and the second involving a nonlinear case study of a continuous stirred-tank reactor (CSTR) with a temperature-dependent reaction. The results underscore the framework's effectiveness in capturing the dynamics of the target systems, including the ability to effectively model nonlinear dynamics. Comparative analyses highlight the benefits of employing dimensionless numbers in dynamic system modelling, offering reduced dimensionality, more physical meaning, and increased model accuracy. Overall, the proposed framework presents a promising approach to enhance system identification in MIMO systems with limited data and uncertainties, with potential applications across diverse domains. [ABSTRACT FROM AUTHOR]

Determining the uplift pressure at key points including the junctions of the floor and the cutoff wall beneath hydraulic structures and estimating the uplift force in these structures are vital issues in water engineering projects. The purpose of this study is to present a series of explicit and highly accurate formulas for determining these quantities for three different cutoff wall locations (at the upstream end, at intermediate locations, and the downstream end). In practice, the materials related to some types of cutoff walls may not be completely rigid due to their low permeability. In this study, the impact of permeability is incorporated into the analysis, and this is the novelty of this study. In order to include the effect of permeability, the capabilities of the SEEPW2D-numerical model that utilizes the FEM to solve the governing equations are used. After generating data sets, nonlinear regression equations are developed in order to estimate the uplift pressure at key points and the uplift force exerted on the hydraulic structures. To validate the results of the FEM, Khosla's approach is used. Khosla's solution is usable only for rigid cutoff walls, while proposed equations can be used for both impervious and pervious cutoff walls as an initial estimate in designs. Also, the results indicate that the decrease in the permeability of the cutoff wall is proportional to the value of the uplift pressure at the key points after the cutoff wall. This reduction is inversely related to the value of the uplift pressure at the key points before the cutoff wall. Accordingly, material that constitutes the cutoff wall has a great effect on seepage characteristics, and it is necessary to consider this in the analysis. Therefore, the permeability of the cutoff wall in any design should be selected depending on the case-specific conditions related to seepage and the stability of the structure. [ABSTRACT FROM AUTHOR]

The development and maturation of TBM (tunnel boring machine) technology have significantly improved the accuracy and richness of excavation data, driving advancements in intelligent tunneling research. However, challenges remain in managing data noise and parameter coupling, limiting the interpretability of traditional machine learning models regarding TBM parameter relationships. This study proposes a cutterhead rotation speed prediction model based on dimensional analysis. By utilizing boxplot methods and low-pass filtering techniques, excavation data were preprocessed to select appropriate operational and mechanical parameters. A dimensionless model was established and integrated with elastic net regression to quantify parameters. Using TBM cluster data from a water diversion tunnel project in Xinjiang, the accuracy and generalizability of the model were validated. Results indicate that the proposed model achieves high prediction accuracy, effectively capturing trends in cutterhead rotation speed while demonstrating strong generalizability. [ABSTRACT FROM AUTHOR]

Over past few years, degradable biomedical implants have replaced permanent orthopaedic implants. The compatibility and functionality of biodegradable implants are greatly influenced by their degradation rate. Development of topologically-ordered functionally graded iron–hydroxyapatite–zinc (Fe–HAp–Zn) composite biomaterial with tailorable degradation rate could be a feasible solution to the problems associated with using any single biodegradable metal. However, in order to attain the desired degradation rate, a mathematical model needs to be developed for predicting the degradation rate. In this study, models for prediction of weight loss and corrosion rate have been suggested. For this, Fe–HAp–Zn composite samples were fabricated using 3D printing, microwave sintering, and casting. Static immersion tests and potentiodynamic polarisation studies were conducted to evaluate degradation characteristics. Then, mathematical models were developed for predicting weight loss and corrosion rate, utilizing this experimental data. The values predicted with developed models were found to be in strong concurrence with the experimental results. [ABSTRACT FROM AUTHOR]

To study the development of imbibition such as the imbibition front and phase distribution in shale, the Lattice Boltzmann Method (LBM) is used to study the imbibition processes in the pore-throat network of shale. Through dimensional analysis, four dimensionless parameters affecting the imbibition process were determined. A color gradient model of LBM was used in computation based on a real core pore size distribution. The numerical results show that the four factors have great effects on imbibition. The impact of each factor is not monotonous. The imbibition process is the comprehensive effect of all aspects. The imbibition front becomes more and more non-uniform with time in a heterogeneous pore-throat network. Some non-wetting phases (oil here) cannot be displaced out. The displacement efficiency and velocity do not change monotonously with any factor. The development of the average imbibition length with time is not smooth and not linear in a heterogeneous pore-throat network. Two fitting relations between the four dimensionless parameters and the imbibition velocity and efficiency are obtained, respectively. [ABSTRACT FROM AUTHOR]

Illness perceptions (IP), as measured by the Brief Illness Perception Questionnaire (BIPQ), and adverse childhood experiences (ACE) have been shown to affect the physical and psychological well-being in different patient populations. However, little is known about IP and ACE in patients with an implantable cardioverter-defibrillator (ICD). Our objectives were to investigate the dimensional structure and to evaluate correlates of the BIPQ in ICD patients. 423 patients with an ICD were prospectively recruited. We conducted a principal component analysis to determine the dimensional structure of the BIPQ. Associations between ACE, other sociodemographic and clinical variables, and IP were analysed using a multivariable linear regression. We identified a two-factor structure (I = Consequences, II = Control) of the BIPQ. Among others, a higher number of ICD shocks in the past (0.21, 95% CI = 0.01–0.41, p = 0.036), low physical activity (-2.16, 95% CI = -4.37 to -0.37, p = 0.045), more frequent ACE (0.56, 95% CI = 0.08–1.22, p = 0.030), ICD shock-related concerns (0.75, 95% CI 0.62–0.89, p < 0.001), and primary ICD indication (-2.29, 95% CI -4.47 to -0.11, p = 0.039) were significantly associated with more threatening IP. The identification of those variables might lead to more precise interventions targeting maladaptive IP in this vulnerable patient population. [ABSTRACT FROM AUTHOR]

This study analyzes the calculation of the critical current density Jc,mag by means of Bean's critical state model, using the equation formulated by Gyorgy et al. and other similar equations derived from it reported in the literature. While estimations of Jc,mag using Bean's model are widely performed, improper use of different equations with different magnetic units and pre-factors leads to confusion and to significant errors in the reported values of Jc,mag. In this work, a SINGLE general equation is proposed for the calculation of Jc,mag for a rectangular parallelepiped sample in perpendicular field using Bean's critical state model, underlying how the simple conversion of magnetic units can lead to a Jc,mag in the desired units, without the need to introduce any other correction or use other specific equations depending on the units of Jc,mag. In this equation, the numerical pre-factor is dimensionless, independent of the unit system used. A comparison between the expression reported in the literature is done, showing how they can lead to different results depending on the used units, and that these results can be at least one order of magnitude different from the correct results obtained with the general equation proposed in this work. This resolves all ambiguities and aligns with the correct dimensional analysis, eliminates discrepancies in the calculated Jc,mag, and will avoid further propagation of errors in the literature. [ABSTRACT FROM AUTHOR]

Altered gaze in social settings is a hallmark of social anxiety; however, little research directly examines gaze in anxiety-provoking contexts among youth with anxiety disorders, limiting mechanistic insight into pediatric anxiety. The present study leveraged mobile eye-tracking technology to examine gaze behavior during a naturalistic stressor in a clinical developmental sample. Sixty-one youth (ages 8–17 years; 28 with anxiety disorders, 33 non-anxious controls) completed a naturalistic social stress task (public speaking in front of a videotaped classroom audience) while wearing eye-tracking glasses. Gaze behavior and state anxiety were quantified in each group during two task conditions: while giving a speech and while passively viewing the audience. Anxiety-related differences emerged in state anxiety and gaze behavior. First, a significant interaction between diagnostic group and task condition on state anxiety indicated that while anxiety increased among non-anxious controls following the speech, youth with anxiety disorders reported persistently elevated anxiety across all assessments. Second, a significant interaction emerged between social anxiety symptom severity and task condition on gaze time on the audience. While youth overall showed low dwell time on the audience during speech delivery, individuals with greater social anxiety showed longer gaze on the audience during the passive viewing condition. This pattern was specific to dimensional analyses of social anxiety symptom severity. The current study was not sufficiently powered to examine age-related differences. These findings highlight anxiety-related differences in gaze behavior in youth, providing new mechanistic insight into pediatric anxiety using mobile eye-tracking. • We leverage eye-tracking glasses to measure gaze during a naturalistic speech task. • Across the sample, this paradigm induced state anxiety and gaze avoidance. • Anxiety-related differences emerged in state anxiety and gaze behavior. • State anxiety was persistently elevated for anxious youth. • Social anxiety tended to positively correlate with dwell time during passive viewing. [ABSTRACT FROM AUTHOR]

Religion is one of the most important factors in architectural shaping. The concepts or sub-concepts that make up religion have a different language that each designer wants to explain. This language is presented semantically and syntactically through the architect and the user interprets this fiction mostly with its syntactic dimension. The findings of this study provide valuable insights into modern mosque design by establishing a connection between belief systems and architectural expressions. Moreover, the study contributes to heritage preservation efforts by proposing a framework that links historical values to contemporary practices. In this study, it is aimed to analyze the effects of the belief concepts in the Islamic religion by analyzing the semantic and syntactic dimensions in rural wooden mosque architecture. Starting from the assumption that abstract values have a language in shaping, the principle of semiotics was utilized to reach concrete results. How the concepts and principles are determined in the semantic and syntactic dimensions of semiotics are explained. In the examination of the semantic dimension, 5 concepts from the concepts of belief in the Islamic religion, namely wahdaniyet, survival, knowledge, powerand hereafter, were discussed. The syntactic dimension was analyzed under basic design principles. The semantic and syntactic dimensions of the sample wooden mosques were analyzed, interpretedand analyzed through architectural drawings, interiorand exterior visuals. These analyses provide practical strategies for translating abstract religious principles into tangible design elements, enhancing their applicability in both educational and professional contexts. As a result, the concepts that emerged in the analyzed examples and the indicators of the sub-concepts belonging to these concepts were presented. It is suggested that the determined analysis model can contribute to design education in design departments and provide convenience to designers and researchers. The model also serves as a tool for creating mosque designs that respect cultural identity while addressing contemporary needs. This research is important in terms of being a reference for the concrete expression of the concepts that we cannot see in architectural formations but we can feel that they exist. [ABSTRACT FROM AUTHOR]

Spiral bevel gears are widely used in automobile transmission systems, and their performance plays a crucial role in driveline safety and transmission efficiency. However, studies on the lubrication performance and churning power loss of spiral bevel gears under an injection lubrication system are still insufficient. In this study, a numerical simulation model consisting of a nozzle, a spiral bevel gear pair, and a box was developed. The effects of different injection velocities, nozzle diameters, oil temperatures, and injection angles on the lubrication performance were simulated and analyzed. In addition, a churning loss prediction model was established by constructing an orthogonal scheme, dimensional analysis, and multiple linear regression, and a spiral bevel gear churning loss test rig was built to verify the accuracy of the prediction model. The results show that the injection velocity and nozzle diameter have a more pronounced effect on the oil volume fraction on the gear surface, while the lubricant temperature has little effect on it; the relative error between the predicted and experimental values of the established model is within 10%, which meets the industrial requirements. This work helps scholars to understand the lubrication mechanism of spiral bevel gears and provides a method to predict the churning power loss of spiral bevel gears under oil injection systems. [ABSTRACT FROM AUTHOR]

In the design of structures involving quasi-brittle materials such as concrete, it is essential to consider the scale dependence of the mechanical properties of the material. Among the theories used to describe the phenomenon of size effect, the fractal theory proposed by Carpinteri and colleagues has attracted attention for its results in the last three decades of research. The present study employs the fractal perspective to examine the scale effect in three-point bending tests conducted on expanded polyethylene (EPS) beam specimens. The influence of size on flexural strength, fracture energy, and critical angle of rotation is investigated. Additionally, numerical simulations based on peridynamic (PD) theory are performed based on the experimental tests. The global behavior, brittleness, failure configuration, and fractal scale effect obtained numerically are evaluated. The numerical results show a good correlation with the experimental ones and, moreover, both the experimental and numerical results are in agreement with the fractal theory of scale effect. More precisely, the error of the sum of the fractal exponents, computed with respect to the theoretical one, is equal to −1.20% and −2.10% for the experimental and numerical results, respectively. Moreover, the classical dimensional analysis has been employed to demonstrate that the scale effect can be naturally described by the PD model parameters, allowing to extend the results for scales beyond those analyzed experimentally. [ABSTRACT FROM AUTHOR]

The current study builds a model of the link between the image-based weights of Indian Potatoes extracted using the built computer vision system using a dimensional analysis integrated with the adaptive neuro-fuzzy inference system. An atomized sorting system must be developed to enhance the exportation quality. A soft computing method is applied to nonlinear data training. The features include size (dimensions, area, and volumes), shapes, and gravimetric properties were chosen. As per standards and export criteria, potatoes should be divided into three groups (small, medium, and big) based on their estimated weight. A self-build image-based system was designed for capturing an image. The experimental outcomes were contrasted with the presented integrated predicted outcomes. A respectable level of agreement is noted with good competency and dependability by the strong correlation coefficient (0.9975). Hence, the presented approach is strongly recommended for image-based weight estimation and classification. Code: [ABSTRACT FROM AUTHOR]

Background: Since residual stresses can affect the mechanical performance of in-service engineering structures, accurate evaluation of biaxial residual stresses is of great significance to service safety. Previous indentation methods for evaluating biaxial residual stresses usually require a stress-free sample as a reference, which is difficult to obtain in engineering. Objective: In present work, a spherical indentation method for evaluating biaxial residual stresses without using stress-free sample was established. Methods: To avoid using stress-free sample, a method for deriving the loading work in unstressed state from the load-depth curve in stressed state, was established. Through dimensional analysis and finite simulations, biaxial residual stresses were quantitatively correlated to the fractional change in loading work between stressed and unstressed states, and the flattening factor of residual imprint. Based on such correlations, biaxial residual stresses can be evaluated without using stress-free sample. A biaxial stress-generating jig was used to validate the method experimentally. Results: Finite element analyses and experimental results demonstrate that the proposed method could evaluate biaxial residual stresses with reasonable accuracy. Conclusions: Combined with portable micro-indentation device, the proposed method has broad application prospects in evaluating biaxial residual stress of in-service engineering structures. [ABSTRACT FROM AUTHOR]

Characteristics of interface between rock layers significantly affect the stability of the support structure in underground excavation. However, there is a lack of in-situ test to probe underground rock interface characteristics. Measurement-while-drilling (MWD) technique is a cost-effective in-situ test to determine supplementary ground information. This study proposes a novel method for identifying rock interface location and bedding plane dip angles using MWD drilling parameters. Drilling test is conducted using sand-stone-limestone combination specimens with varying interface angles using a self-developed digital drilling system instrumented on a real hydraulic rotary drilling machine from underground two boom face drilling rig. Displacement–time data during drilling were processed using the local weighted regression (LOESS) method to reveal the change in drilling speed as the drill bit encountered different interface angles. A comprehensive evaluation index of the drilling process (IMWD) was established, integrating multiple drilling parameters through dimensional analysis. An intelligent identification method for rock interface characteristics was proposed, employing the Bayesian estimator of abrupt change, seasonality, and trend (BEAST) algorithm along with IMWD. Experimental results demonstrate that the smoothed displacement–time data effectively reflect the drill bit's passage through the rock interface, delineated into three stages: non-penetration, partial penetration, and complete penetration. IMWD exhibits clear responses to rock layer interfaces, manifesting abrupt changes upon contact with the interface. By combining the BEAST algorithm with IMWD, displacement information at each changepoint of the IMWD sequence is rapidly obtained, facilitating the determination of interface location and rock layer interface angle. Based on this method, the calculation errors for the specimens with interface angles designed at 0°, 30°, and 60° are + 1.96°, − 1.14°, and + 0.67°. The proposed method can be potentially an in-situ method to accurately determine the location of interface and bedding plane dip angles from drilling parameters. Highlights: A rock interface angle calculation method based on MWD data is proposed. Use dimensional analysis to establish the comprehensive evaluation indexes for MWD. The BEAST algorithm is introduced to detect and calculate the rock layer interface position and angle. A valuable reference is provided for achieving the coal mine geologic transparency technology. [ABSTRACT FROM AUTHOR]

Sediment entrainment formulations developed for noncohesive materials have been widely applied to determine suspended loads in fluvial environments. Most relations were developed based on laboratory experiments and field measurements taken in sand-rich environments. Due to the accidental discharge of mine tailings in riverine systems, it is imperative to develop new approaches to predict sediment entrainment and resulting near-bed concentrations, as field observations show that the primary mode of transport for tailings once they are eroded is in suspension. Based on laboratory experiments conducted with poorly sorted iron tailings samples in an annular flume, we found that existing sand-based relations predict relatively well equilibrium near-bed concentrations when treated as well-sorted material. However, to predict entrainment rates into suspension for the tested poorly sorted iron tailings samples, sand-based entrainment relations require adding two functions accounting for the relative roughness of the bed material and the Reynolds particle number for the effect of viscous sublayer thickness on entraining fine grains. This innovative approach, combining dimensional analysis, similarity parameters, and experimental observations in an annular flume, provides a general framework for developing formulations to estimate the flow conditions necessary to entrain into suspension and then transport tailings either accidentally released into riverine environments or resuspended during dredging operations in watercourses. [ABSTRACT FROM AUTHOR]

A more generalized approach for predicting the steady‐state creep rate of ceramic fibers under extensive stress ranges is proposed. Creep rate equations derived from dimensional analysis, such as Almeida's creep equation and Arrhenius' creep equation, were evaluated using Buckingham's method, and the corresponding π groups were determined. Subsequently, a new equation is proposed using the usual semi‐empirical constants for the diffusional and power law creep phenomena, along with an additional power law exponent to account for changes in creep mechanisms at higher stresses. The proposed equation was used to fit the creep rate data of the fiber Nextel 720 at various temperatures and constant stress, which demonstrated a good fit with an adjusted R‐squared of.96. Subsequently, the equation was used to predict the creep rate at constant temperature and various stresses, exhibiting an adjusted R‐squared of.77 and.85, depending on the scatter of the used data. The predictive results of the proposed equation were then compared to those obtained using the Arrhenius creep equation, which tends to higher rates at high stresses. In summary, the novel equation can be more efficiently applied in predicting the creep rate of ceramic fibers across a broader spectrum of stress. [ABSTRACT FROM AUTHOR]

This paper investigates the residual stresses induced by metal inert/active gas (MIG/MAG) welding in normal strength steel box sections, focusing on the validity of uniaxial residual stress assumption. Advanced manufacturing simulations are conducted using deterministic uncoupled transient thermomechanical analysis with a double-ellipsoidal heat source model, employing 8-node solid elements and material models calibrated for extreme temperatures per EN 1993-1-2. A comprehensive parametric analysis investigates the effects of primary welding variables, such as heat source power and welding speed, alongside geometric parameters of the heat source model using random Latin hypercube sampling technique in the analyzed parameter set. The relationship between the size and shape of the characteristic isotherms, i.e., the aspect ratio and the Rosenthal number, underscores that the analyzed welding heat sources are in the fast regime with the validity of uniaxial residual stresses based on the analytical assumption (minimal values are AR = 9.94 and Ro = 30.47). The validity and limitations of uniaxial residual stress assumptions for 59 welded and 51 heated box sections are critically evaluated by using the finite element model-based stress triaxiality parameter. Results confirm that longitudinal residual stresses dominate typical MIG/MAG welding applications, supporting the application of uniaxial residual stress models in advanced structural design by neglecting in-plane and through-thickness residual stresses. Conversely, three-dimensional residual stress state dominates under conditions such as preheating or thermal straightening. [ABSTRACT FROM AUTHOR]

The precise bending of sheet metal structures is crucial in various industrial and scientific applications, whether to modify deformation in an existing component or to achieve specific shapes. Laser peen forming (LPF) is proven as an innovative forming process for sheet metal applications. LPF involves inducing mechanical shock waves into a specimen that deforms the affected region to a certain desired curvature. The degree of deformation induced after LPF depends on numerous experimental factors such as laser energy, the number of peening sequences, and the thickness of the specimen. Consequently, comprehending the complex dependencies and selecting the appropriate set of LPF process parameters for application as a forming or correction process is crucial. The main objective of the present work is the development of a data-driven approach to predict the deformation obtained from LPF for various process parameters. Artificial neural network (ANN) was trained, validated, and tested based on experimental data. The deformation obtained from LPF is successfully predicted by the trained ANN. A novel process planning approach is developed to demonstrate the usability of ANN predictions to obtain the desired deformation in a treated region. The successful application of this approach is demonstrated on three benchmark cases for thin Ti-6Al-4V sheets, such as deformation in one direction, bi-directional deformation, and modification of an existing deformation in pre-bent specimens via LPF. [ABSTRACT FROM AUTHOR]

By virtue of applying small tidal volumes, high-frequency ventilation is advocated as a method of minimizing ventilator-induced lung injury. Lung protective benefits are established in infants, but not in other patient cohorts. Efforts to improve and extend the lung protection potential should consider how fundamental modes of gas transport can be exploited to minimize harmful tidal volumes while maintaining or improving ventilation. This research investigates different models of gas transport during high-frequency ventilation and discusses the extent to which the gas transport mechanisms are considered in each. The research focuses on the rationale for current ventilation protocols, how they were informed by these models, and investigates alternative protocols that may improve gas transport and lung protection. A review of high-frequency ventilation physiology and fluid mechanics literature was performed, and dimensional analyses were conducted showing the relationship between clinical data and the model outputs. We show that contemporary protocols have been informed by resistor-inductor-capacitor, or network, models of the airway-lung system that are formulated around a ventilation pressure cost framework. This framework leads to clinical protocol selection that ventilates patients at frequencies that excite a resonance in the lung. We extend on these models by considering frequencies that are much higher than resonance which further optimize gas transport in the airway via alternative gas transport mechanisms to bulk advection that operate for very low tidal volumes. Our findings suggest it is unlikely that gas transport is optimally exploited during current approaches to high-frequency ventilation and protocols that differ significantly from those currently in use could achieve ventilation while using very low tidal volumes. [ABSTRACT FROM AUTHOR]

Due to the sensitivity of the shaped charge jet to standoff and the complexity of its impact under lateral disturbances, this study aims to investigate the dynamic impact evolution of the jet influenced by standoff and lateral disturbances. A finite element model for the dynamic impact of shaped charge jets was established. Dynamic impact experiments were designed and conducted to validate the effectiveness of the numerical simulations. Utilizing dimensional analysis, a predictive model was developed for jet dynamic impact considering the combined effects of target plate strength, standoff and lateral disturbances. The results indicate that as the standoff varies between 90 mm and 225 mm, the dynamic impact depth of the jet decreases approximately linearly with increasing standoff. Meanwhile, for lateral disturbance velocities ranging from 100 m/s to 400 m/s, the impact depth decreases exponentially with increasing lateral relative velocity of the target. The lateral disturbance velocity is identified as the primary factor influencing jet impact, while the standoff is a secondary factor. The agreement among computational results, numerical simulations, and experimental outcomes confirms the accuracy and effectiveness of the predictive model and simulations, providing a basis for evaluating the dynamic impact potential of shaped charges. [ABSTRACT FROM AUTHOR]

Mechanical ventilation contributes to diaphragm atrophy and muscle weakness, which is referred to as ventilator-induced diaphragmatic dysfunction (VIDD). The pathogenesis of VIDD has not been fully understood until recently. The aim of this study was to investigate the effects of 24 h of mechanical ventilation on fibro-adipogenic progenitor (FAP) proliferation, endothelial-mesenchymal transition (EndMT), and immune cell infiltration driving diaphragm fibrosis in a rabbit model. The rabbits were anaesthetized and randomly divided into two groups (n = 3 each group): a control group and an experimental group. Diaphragm nuclei for sequencing were prepared by dissociating and filtering muscle tissue. 10X Genomics Platform for single-nucleus RNA sequencing (snRNA-seq) was used to profile the cells. Normalization and clustering were performed by Seurat, and clusters were manually annotated as different cell types. In this study, we performed differentially expressed genes (DEGs) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, pseudotime analysis and high dimensional weighted gene coexpression network analysis (hdWGCNA) to identify the key genes and signaling pathways related to the pathogenesis of VIDD. We further performed quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting to verify the results of snRNA-seq. The snRNA-seq results showed that acute postmechanical ventilation diaphragm cell changes included an increase in the proportion of fibroblasts and a decrease in the proportion of myofibres. The DEGs, KEGG, hdWGCNA and pseudotime analyses demonstrated that fibro-adipogenic progenitor (FAP) proliferation, endothelial-mesenchymal transition (EndMT) and immune cell infiltration are the three main processes involved in early stage of fibrosis development, among which Pdgfd, Sema3a, Cxcr2, are the corresponding regulatory genes. Glycolysis and the gene Pfkfb3 are also important metabolic factors for fibrosis formation. Negr1 and Mef2c are involved in phrenic nerve ending loss and diaphragm fibre atrophy. The qRT-PCR data showed that the mRNA levels of the genes Pdgfd, Cxcr2, Pfkfb3 and Negr1 were significantly greater in the experimental group than in the control group (P < 0.01), and the expression levels of Sema3a and Mef2c were significantly lower (P < 0.01). Despite limitations, including the lack of functional evaluations to confirm ventilator-induced diaphragm dysfunction (VIDD) and the absence of data validating diaphragm unloading during ventilation, our findings suggest that FAP proliferation and immune cell infiltration may play a role in the early stage of driving diaphragm fibrosis during mechanical ventilation. However, future studies are needed to confirm these findings and investigate the potential mechanisms underlying them. [ABSTRACT FROM AUTHOR]

Dynamic oriented wrinkling especially on arbitrary film materials is highly desirable yet remains a great challenge. Here, fabrication of programmable aligned wrinkling patterns on different film/substrate systems via a laser‐direct‐writing (LDW) method is reported, regardless of photofunctionality and transparence of the target films. The key is related to smart introduction of photothermal materials (PTMs) into compliant substrates and even as an independent attachable/detachable layer assembled underneath the film/substrate systems. Experiments and theoretical modeling reveal that with the help of the photothermal effect of PTMs, in situ LDW‐induced localized dynamic anisotropic stress field is responsible for the intriguing LDW path‐parallel aligned wrinkling. Furthermore, dimensional analysis is carried out and explicit solutions quantifying the connection of wrinkling morphology parameters with the LDW conditions are derived for the first time, which enables theoretical pattern designing. It is highlighted that the attachable/detachable assembly strategy for the independent PTMs layer endows arbitrary film/substrate systems with on‐demand photosensitivity when needed, which has been inaccessible previously. As demonstrated, these dynamic oriented wrinkling systems have found broad applications especially in smart soft photonics, e.g., information storage, anticounterfeiting, and responsive optical devices. [ABSTRACT FROM AUTHOR]