External Load Research Articles

Modeling and Simulation of the Aging Behavior of a Zinc Die Casting Alloy

While zinc die-casting alloy Zamak is widely used in vehicles and machines, its solidified state has yet to be thoroughly investigated experimentally or mathematically modeled. The material behavior is characterized by temperature and rate sensitivity, aging, and long-term influences under external loads. Thus, we model the thermo-mechanical behavior of Zamak in the solid state for a temperature range from −40 °C to 85 °C, and the aging state up to one year. The finite strain thermo-viscoplasticity model is derived from an extensive experimental campaign. This campaign involved tension, compression, and torsion tests at various temperatures and aging states. Furthermore, the thermo-physical properties of temperature- and aging-dependent heat capacity and heat conductivity are considered. One significant challenge is related to the multiplicative decompositions of the deformation gradient, which affects strain and stress measures relative to different intermediate configurations. The entire model is implemented into an implicit finite element program and validation examples at more complex parts are provided so that the predicability for complex parts is available, which has not been possible so far. Validation experiments using digital image correlation confirm the accuracy of the thermo-mechanically consistent constitutive equations for complex geometrical shapes. Moroever, validation measures are introduced and applied for a complex geometrical shape of a zinc die casting specimen. This provides a measure of the deformation state for complex components under real operating conditions.

Rock exfoliation in the unstable formations during underground mine working driving and selection of efficient adhesive compositions for strengthening

Purpose is to identify factors favouring rock exfoliation in roof of underground mine workings while operating Akbakay deposit and determine optimum structure of adhesive reagents for the rock strengthening taking into consideration mineralogical composition of the formation. Methods. The research was carried out in a lab environment. Chemical and ultimate composition of the rock mass samples was determined through x-ray diffraction method; the x-ray phase identification approach helped define their mineralogical composition. The optimum composition of adhesive reagents has been determined based upon the ambient temperature and hardening time. Viscosity durability of the adhesive compounds was assessed using a technique of uniaxial crack of the immovable samples. Statistical data processing involved determination of the required number of the samples to achieve the preset accuracy degree. Findings. Exfoliation of the fragments of both fractured and unstable rocks from Akbakai deposit depends upon availabi-lity of such chemically and mechanically unstable salts as dolomite, albite, and mirror stone. Epoxide reagent in 9 to 1 ratio with polyethylenepolyamine catalyzer has been identified as the most effective adhesive compound. Epoxy adhesives have demonstrated higher cohesive resistance to compare with polyurethane analogues, and better compliance with requirements as for viscosity and hardening time. Originality. Use of epoxy to strengthen both fissured and unstable rocks of Akbakai deposit containing mineral salts, helps increase tensile properties up to three times. Moreover, epoxies also demonstrate high adhesive characteristics; and they are resistant to moisture and temperature attacks being typical for mine environment. New logarithmic dependencies have been identified describing rock mass stability while applying the modified polyurethane with polyethylenepolyamine catalyzer in 9 to 1 ratio. Practical implications. Various types of reagents have been considered for safe and effective strengthening of underground mine workings in the fractured rock masses having a tendency to caving. The proposed adhesive reagents resist efficiently the external share loads and stresses increasing structural stability and safety of rock masses.

An alternative stress boundary condition in small deformations and its application to soft elastic composites and structures

Linear elasticity theory has been used extensively in the study of the elastic behavior of various perforated structures and composite materials requiring the accompaniment of appropriate boundary conditions to derive qualitatively correct and quantitatively referential solutions. When incorporating conventional boundary conditions, however, linear elasticity theory fails to predict certain essential phenomena associated with perforate structures and composite materials even when they undergo small deformations. For example, a soft elastic porous medium is appreciably stiffened when inflated despite the fact that the internal air pressure is significantly lower than the modulus of the medium itself. In this paper, we propose an improved stress boundary condition by simply incorporating a small change in the normal to the boundary during deformation. We show via numerical examples that in the context of linear elasticity theory, the use of this improved boundary condition offers the possibility of predicting the influence of initial or residual stress in a perforated structure on the elastic response of the structure to external loadings (which can never be captured with the use of conventional boundary conditions). We perform also large-deformation-based finite element simulations to verify the accuracy of the closed-form results obtained from the improved boundary condition for a soft elastic perforated structure with initial internal pressure. We believe that the idea presented in this paper will extend the applicability of linear elasticity theory and yield more accurate referential analytic results for soft elastic structures and composites.

Fractional-Order Correlation between Special Functions Inspired by Bone Fractal Operators

In recent years, our research on biomechanical and biophysical problems has involved a series of symmetry issues. We found that the fundamental laws of the aforementioned problems can all be characterized by fractal operators, and each type of operator possesses rich invariant properties. Based on the invariant properties of fractal operators, we discovered that the symmetry evolution laws of functional fractal trees in the physical fractal space can reveal the intrinsic correlations between special functions. This article explores the fractional-order correlation between special functions inspired by bone fractal operators. Specifically, the following contents are included: (1) showing the intrinsic expression in the convolutional kernel function of bone fractal operators and its correlation with special functions; (2) proving the following proposition: the convolutional kernel function of bone fractal operators is still related to the special functions under different input signals (external load, external stimulus); (3) using the bone fractal operators as the background and error function as the core, deriving the fractional-order correlation between different special functions.

Evaluation of Residual Stress in Stir-squeeze Cast Aluminium – Fly Ash Composites Using X-Ray Diffraction Method

Determination of residual stresses in metals, subjected to secondary processing, is necessary from the point of view of their applications and is widely studied in literature. However, residual stresses induced during service is generally ignored when evaluating the performance of the component. The residual stress in a component could be tensile or compressive in nature and eventually affects its service life under external loading. In this regard, industries demand rapid, efficient, and easier methods of non-destructive testing to identify and control the residual stress in such components. The present work aims at evaluation of residual stress in an LM-25 aluminium alloy/fly Ash Metal Matrix Composites (AMC) after subjecting the specimen to dry sliding wear tests. X-ray diffraction technique was used to measure the residual stress in the “pin” specimen of the pin-on-disc set-up. The residual stress was ~ 24 % higher in the composite compared to the un-reinforced alloy after the wear test while the wear rate, measured in terms of weight loss of the pin, was lower by about 50%, under similar test conditions.

Mitigating inland waters’ greenhouse gas emissions: current insights and prospects

ABSTRACT Natural and constructed inland waters emit globally significant amounts of greenhouse gasses (GHGs) into the atmosphere. As a result of human-induced alterations in the landscape, these emissions tend to increase. While proper management of waterbodies is fundamental to reaching the global sustainable development goals as well as the Paris Agreement, insights on climate-smart inland water management are still underexplored. Here we review and discuss physical, chemical, and biological management measures applied in a wide range of inland waters to (1) reduce external loads of compounds fueling aquatic GHG emissions, (2) reduce the aquatic production of GHG-fueling compounds, and (3) minimize GHG production and stimulate GHG consumption. Some measures are well studied and others are in the exploration phase, resulting in a varying degree of confidence with respect to their effectiveness. Climate-smart water management (e.g., through the reduction of organic matter and nutrient loading) generally not only reduces GHG production and emission but also improves the ecological state of aquatic environments. Reductions in GHG emissions from 5% (fish effect) to ∼90% (salinization effect) were observed among the climate-smart measures discussed here. Certainly, the global effect of the different measures also depends on the application scale. Depending on the local context, the implementation of one or more of these measures can be considered in a GHG mitigation program.

Task-dependent coarticulation of movement sequences.

Combining individual actions into sequences is a hallmark of everyday activities. Classical theories propose that the motor system forms a single specification of the sequence as a whole, leading to the coarticulation of the different elements. In contrast, recent neural recordings challenge this idea and suggest independent execution of each element specified separately. Here, we show that separate or coarticulated sequences can result from the same task-dependent controller, without implying different representations in the brain. Simulations show that planning for multiple reaches simultaneously allows separate or coarticulated sequences depending on instructions about intermediate goals. Human experiments in a two-reach sequence task validated this model. Furthermore, in co-articulated sequences, the second goal influenced long-latency stretch responses to external loads applied during the first reach, demonstrating the involvement of the sensorimotor network supporting fast feedback control. Overall, our study establishes a computational framework for sequence production that highlights the importance of feedback control in this essential motor skill.

Study on the evolution characteristics of coal mass spalling during coal and gas outbursts

The process of coal and gas outbursts (called outbursts for short) are commonly accompanied by coal mass spalling and fragmentation, but the formation mechanism of spalling is still unclear. To clarify this mechanism, this research constructs multi-layered combined coal-rock mass model. Based on the stress wave propagation mechanism, it’s found that outbursts initially start from ‘weak layer’. Besides, there are two significant results by analyzing the process of unloading waves formed by sudden pressure relief of the excavation face. Firstly, in the axial direction, due to the internal impact of the coal mass during the unloading wave propagation, the load shock wave is formed. The tensile stress is formed on the surface of the coal mass, resulting in rapid damage to the coal mass and even multi-layered spalling. Secondly, in the radial plane, permanent standing surfaces will be formed when the unloading wave catches up with the plastic load wave. Under effect of the unloading wave, internal impact will occur a series of load shock wave, resulting in the formation of multi-layered spalling in the radial plane. In addition, the attenuation law of the load shock wave generated by the internal impact in multi-layered coal mass is also analyzed, results showed that the thickness of coal mass spalling formed far away from the free surface will increase. Finally, the three-dimensional dynamic damage path and the spindle shape damage area formation mechanism in coal mass under external dynamic load are analyzed, which provides a new idea for elucidating the outbursts mechanism.

The influence of steep faults at various avoidance distances on the stability of hard rock caverns: Physical model experiments and DEM simulations

The influence of avoidance distances from steep faults on the stability of hard rock caverns is pivotal in deep engineering, yet research in this area remains scant. This study constructed 10 physical models of granite caverns, incorporating artificial cement-filled faults at various avoidance distances ranging from 0 to 2.4 cavern diameters. Biaxial compression experiments were conducted, utilizing acoustic emission and digital image correlation techniques for monitoring. Coupled with discrete element method simulations, the analysis explored the influence mechanisms of fault-cavern distance on the failure modes of hard rock caverns. The results reveal a positive correlation between the peak strength of specimens and fault-cavern distance. As the distance approaches 0.6 cavern diameters, the fault significantly influences the displacement field, crack number, distribution, and crack initiation location within the specimens. Furthermore, even at 1.2 cavern diameters, the fault still exhibits a notable influence on the stress field, external load transfer paths, cavern failure modes, and the size distribution of spalling debris. These findings can guide the selection of sites for deep hard rock caverns, ensuring a minimum fault-cavern distance of 1.2 cavern diameters to mitigate the risks posed by steep faults to such caverns.

Deep learning enabled in vitro predicting biological tissue thickness using force measurement device

Accurate perception of biological tissues (BT) thickness is essential for preliminary evaluation of medical diagnosis and animal nutrition. However, traditional thickness measuring approaches of BT require complex operation, high-cost, and trigger biological stress response. Herein this study, an novel in vitro BT thickness measuring approach integrated with force test system (FST) and the discrete multiwavelet transform convolutional neural network (DMWA-CNN) prediction model based on deep learning are proposed. Simultaneously, several comprehensive experiments and model comparisons are conducted to demonstrate the superiority of the proposed approach. By establishing a DMWA-CNN demonstrates higher estimation accuracy than other traditional algorithm, achieving 100 % accuracy for artificial BT. Moreover, the experimental results indicate that proposed approach is robust to elastic modulus variation (E), external load variation (F), and small thickness differences (Ts). In addition, four kinds of the pork’ thickness are experimentally measured, and the accuracy value is not less than 98.2 %. The thickness of BT determined using the FST and DMWA-CNN algorithm demonstrate potential application in the biomechanical parameter prediction.

External Load of Different Length Microcycles and Relationships with Match Running Performance in Youth Football

ABSTRACT The purpose of this study was to investigate: a) the differences in external load (EL) during microcycles with four (MIC4) and five training (MIC5) sessions, b) to explore the ratio of weekly training load to the load of the subsequent match, and c) to explore possible correlations between the EL of the MIC4 or MIC5 with the running performance of football players in the following match. The study involved 20 elite youth football players from a team that won the championship in their category that year (age, 16.4 ± 0.3 years). The EL was tracked via GPS in 8 MIC4 and 10 MIC5. Running performance in subsequent matches was also recorded. Two by two ANOVA was employed to compare parameters between MIC5 and MIC4 and Pearson correlation test was applied to examine potential correlations between the training load parameters. The results showed that MIC5 had significantly greater external load in distance parameters in zones 4 & 5, total distance, and decelerations. Differences in running performance in matches were observed only for accelerations (p = .028) and decelerations (p = .02). The ratio of training/match load was lower in all parameters in MIC4 compared to MIC5 but exceeded the match load. Large negative correlations were observed for accelerations and decelerations. In conclusion, additional training in MIC5 increases the load without affecting running performance in the match. Attention should be given to accelerations and decelerations, as their volume can easily increase with the use of small-sided games in training.

Temperature compensation method for impedance signals of bolt loosening under temperature varying conditions using TransUnet

Abstract Piezoelectric transducer based electro-mechanical impedance technology is an effective and reliable detection method for bolt structure loosening under external load. However, temperature change usually causes some non-loosening factors to change the impedance spectrum of bolt structure. In order to reduce the misjudgment of loosening damage caused by temperature change, it is necessary to construct a temperature compensation model for impedance spectrum. In this paper, the convolutional structure in U-net and Transformer are effectively combined to form a TransUnet deep neural network structure suitable for input and output of one-dimensional data. Using impedance data between 10 °C and 50 °C and temperature as input to the network. After convolution operation, the convolutional block attention module is embedded in the U-net to optimize the encoder transmission characteristics and enhance the performance of the skip connection in the traditional U-shaped structure. The temperature compensation rate (TCR) is defined to measure the effect of temperature compensation. Then the lightweight convolutional neural network structure is used to recognize the bolt loosening damage of the compensated impedance signal. The generalization ability of the TransUnet was tested using impedance data that is not in the training dataset. The results show that the TransUnet proposed in the paper can realize the temperature compensation of multi-peak impedance signals. The TCR and recognition accuracy of bolt loose damage reaches reach 0.003 and 95.7%, respectively, which is 11% higher than that without temperature compensation. At 60 °C, the TCR and the identification accuracy of loosening damage can still reach 0.0055 and 90.2%, respectively, which show that the TransUnet has strong generalization ability.

Research on Rock Energy Constitutive Model Based on Functional Principle

The essence of rock fracture can be broadly categorized into four processes: energy input, energy accumulation, energy dissipation, and energy release. From the perspective of energy consumption, the failure of rock materials must be accompanied by energy dissipation. Dissipated energy serves as the internal driving force behind rock damage and progressive failure. Given that the process of rock loading and deformation involves energy accumulation and dissipation, the rock constitutive model theory is expanded by incorporating energy principles. By introducing the dynamic energy correction coefficient, according to the law of the conservation of energy, the total energy exerted by external loads on rocks is equal to the energy dissipated through the dynamic energy inside the rocks. A new type of energy constitutive model is established through the functional principle and momentum principle. To validate the model’s accuracy, a triaxial compression test was conducted on sandstone to examine the stress–strain behavior of the rock during the failure process. A sensitivity analysis of the parameters introduced into the model was conducted by comparing the model results, which helped to clarify the innate laws of significance of these parameters. The results indicated that the energy model more accurately captures the non-linear mechanical behavior of sandstone under high-stress loading conditions. The model curve fits the test data to a high degree. The fitting curve was basically consistent with the changing trend of the test curve, and the correlation coefficients were all above 0.90. Compared with other models, the model based on the energy principle not only accurately reflects the rock’s stress–strain curve, but also reflects the energy change law of rock. This has reference value for the safety analysis of rock mass engineering under loading conditions and aids in the development of anchoring and support schemes. The research results can fill in the blanks that exist in the energy method in terms of rock deformation and failure and provide a theoretical basis for deep rock engineering. Moreover, this research can further improve and extend the rock mechanics research system based on energy.

Differences in acute responses and chronic adaptations according to the exercise intensity reference method in previously inactive individuals

During prolonged continuous exercise, the relationship between external load (e.g., running speed) and internal load [e.g., heart rate (HR)] shifts. This means, for example, that at a given running speed, the HR will continuously increase, whereas if the goal of the exercise is to maintain a constant HR, the running speed will decrease over time. The time dependence of the internal/external load relationship could lead to different acute responses and chronic adaptations depending on the exercise intensity reference method. This hypothesis was tested in the present study. Forty-three previously inactive individuals were randomized into two groups: one group (SPEED-C) trained at a speed midway between the first and second lactate threshold (v ∆ 50LT), whereas the other group (HR-C) trained at a HR midway between the thresholds (HR ∆ 50LT). Both groups performed 30 min of continuous endurance exercise 3 times per week for 8 weeks. Maximal oxygen consumption (V̇O2max) and peak treadmill speed (Vpeak) were determined by an incremental treadmill test followed by a verification test before (PRE) and after (POST) the 8 weeks of training. V̇O2, HR, speed, and rate of perceived exertion (RPE; measured with the Borg CR10) were recorded during the first and last treadmill training sessions performed in the lab. After POST, an additional simulated session was performed with the intensity adjusted to the new training level. Thirty-four participants (9 women and 7 men in SPEED-C; 11 women and 7 men in HR-C) completed the study and were included in the analysis. v ∆ 50LT/HR ∆ 50LT occurred at 74 ± 5% of HRmax, 63 ± 4% of V̇O2max, and 60 ± 4% of V̇peak in SPEED-C and at 74 ± 5 % of HRmax, 63 ± 5% of V̇O2max, and 60 ± 6 % of V̇peak in HR-C. SPEED-C showed higher speed (+1.5 km/h, p < 0.001), V̇O2 (+6.3 mL/kg/min, p < 0.001), HR (+23 bpm, p < 0.001) and RPE (+1.9 points, p = 0.002) than HR-C during the first training session. These initial differences between groups were reduced after 8 weeks of training (speed: by -0.5 km/h, p = 0.006; V̇O2: by -2.6 mL/kg/min, p < 0.001; HR: by -14 bpm, p < 0.001; RPE: (-1.7 points, p = 0.002). However, statistically significant reductions were no longer observed when the intensity was adjusted to the new training level. V̇O2max (+1.0 mL/kg/min, p = 0.021) and Vpeak (+0.8 km/h, p < 0.001) improved more in SPEED-C than in HR-C. Among the secondary physiological characteristics investigated in this study, speed at the second lactate threshold (+1.1 km/h, p < 0.001) and v ∆ 50LT (+0.5 km/h, p = 0.008) improved more in SPEED-C than in HR-C, whereas HR at the second lactate threshold improved more in HR-C than in SPEED-C (-7 bpm, p = 0.008). The exercise intensity reference method (speed vs. HR) affects acute responses and chronic adaptations in previously inactive individuals. However, training conditioning may mitigate these differences if the intensity is not constantly adjusted to the new training level.

The interface dewetting process of particulate filled polymer composite

AbstractDewetting is one of the most common damage modes in particulate filled polymer composite, which greatly damages the structural integrity of the composite and leads to the deterioration of its mechanical properties. Studying the dewetting evolution process of composite is of great significance for evaluating the meso damage degree of composite and suppressing the development of dewetting damage. This article constructs an axisymmetric cylindrical cell model of a single particle inclusion matrix, derives the interface dewetting evolution process of the model under uniaxial tensile loading condition, and analyzes the influence of model geometric parameters and external loading conditions on the dewetting process. Subsequently, numerical models were constructed at both micro and meso scales, and dynamic tensile calculations were performed to analyze the correlation between the dewetting rate, porosity, and mechanical performance. Finally, a cylindrical cell specimen was designed to observe the interface dewetting evolution under uniaxial tensile conditions, confirming the conclusions of theoretical analysis and numerical simulation.Highlights Constructed a theoretical model for the dewetting process of interface. Conducted numerical analysis of dewetting process at both meso and micro scales. Designed interface dewetting experiment and analyzed the dewetting process.

Design of an Overhead Crane in Steel, Aluminium and Composite Material Using the Prestress Method

The present research describes a design of an overhead crane using different materials with a prestress method, which corresponds to an external compression force with the aim of reducing the displacement of the beam due to the external load. This study concerns a bridge crane with a span length of 10 m, with a payload equal to 20,000 N and an estimated fatigue life of 50,000 cycles. Three different materials are studied: steel S355JR, aluminium alloy 6061-T6 and carbon fibre-reinforced polymer (CFRP). These materials are analysed with and without the contribution of the prestress method. In reference to the prestressed steel solution (which has a weight equal to 79% of the non-prestressed configuration), this study designed an aluminium solution that is 50.7% of the weight of the steel one and a composite solution that is always 20.3% of the steel configuration. In combining the methods, i.e., the materials and prestress, compared to the non-prestressed steel solution with a weight evaluated to be 758 kg, the weight of the aluminium configuration is equal to 40% of the traditional one, and the composite value is reduced to 16%, with a weight of 121 kg.

Numerical Investigation of Fracture Behaviour of Polyurethane Adhesives under the Influence of Moisture.

The mechanical behaviour of polymer adhesives is influenced by the environmental conditions leading to ageing and affecting the integrity of the material. The polymer adhesives have hygroscopic behaviour and tend to absorb moisture from the environment, causing the material to swell without applying external load. The focus of the work is to investigate the viscoelastic material behaviour under ageing conditions. The constitutive equations and the governing equations to numerically investigate the fracture in swollen viscoelastic material are discussed to describe the numerical implementation. Phase-field damage modelling has been used in numerical studies of ductile and brittle materials for a long time. The finite-strain phase-field damage model is used to investigate the fracture behaviour in aged viscoelastic polymer adhesives. The finite-strain viscoelastic model is formulated based on the continuum rheological model by combining spring and Maxwell elements in parallel. Commercially available post-cured crosslinked polyurethane adhesives are used in the current investigation. Post-cured samples of crosslinked polyurethane adhesives are prepared for different humidity conditions under isothermal conditions. These aged samples are used to perform tensile and tear tests and the test data are used to identify the material parameters from the curve fitting process. The experiment and simulation are compared to relate the findings and are the first step forward to improve the method to model crosslinked polymers.

Analysis of spectra of external impacts, reactions to them and limit states under the non-stationary modes of loading

It is noted that under real operating conditions of technical systems the so-called non-stationary loading in which external loadings increase or decrease arbitrarily is realized most often. At the same time final ratios between strains and stresses are of practical interest to engineering calculations. It is shown that for simple cyclic loadings the state equations in final ratios which are based on the theory of small elastic-plastic strains can be used. In this case the existence of the uniform generalized deformation diagram assuming a final relation between the corresponding components of stresses and strains both for initial and cyclic stages of deformation is essential for the analysis of considered conditions of a non-stationary cyclic loading. The analysis of conditions of achieving limit states at all stages of the life cycle the criteria base and the system of the computation equations become more complicated and more saturated by the factors taken into account and among them first external and internal impacts of natural, technogenic, anthropogenous origin, load from these impacts, and the reactions of installations to such impacts and loads as well. At the same time a set of criteria defining a limit state is presented in the form of a functional dependence characterizing a set of force and deformation parameters of the state of technical system on the one hand, and, on the other hand, a complex of criterion characteristics of constructional materials taking into account their change during operation. The most important step of determining conditions for achievement of the limit state causing fracture is establishing the critical parts that determine risks of emergency and catastrophic situations in which processes of local and main fractures are initiated. In this case transition of the operated installation from design area to the area of initiation of refusals, accidents and disasters occurs when the parameters of damage, defectiveness and risk reach their critical values.

Force-velocity profiling in elite luge athletes during the simulated luge start

Introduction & Purpose The idea of some athletes having high strength levels but being too slow for a particular movement while others are fast but not strong enough for the demands of their sport exists among many coaches. Therefore, planning decisions are often based on the measurement results of speed and force capabilities and the interest in the relationships between additional load, force, velocity and power during the required movement is high. The luge start is a ballistic movement that requires both high forces and velocities to reach maximal performance (i.e. fast starting times). Examining the load, force, velocity and power capabilities of elite luge athletes during the luge start could deliver insights for training prescription to improve individual weak points and improve performance. This study investigated the relationship between the calculated maxima of force-velocity (FV), load-velocity (LV) and power-velocity (PV) profiles during a simulated luge start and on-ice start times in elite luge athletes. Methods Eleven Austrian national luge team athletes (1 female, 10 male, 25 [4.4] y, 182.4 [7.3] cm, 86.65 [10.4] kg) participated in this study. Measurements were conducted during a single testing session on a specially designed start simulator. Each athlete performed starts against 5 increasing resistances relative to their bodyweight (0%, 25%, 50%, 75%, 100%). For each pull, relative maximum force (Fmax), maximum power (Pmax) and maximum velocity (Vmax) were calculated using the measurements of a linear position transducer (GymAware PowerTool). An experimental approach was used to create the FV-, LV- and PV-profiles showing the highest R2. On-ice start times [s] were measured by photoelectric sensors (ALGE). A correlation matrix (p < 0.05) was used to analyze the relationships between the theoretical Pmax, Fmax (i.e. theoretical isometric maximum force), theoretically unloaded Vmax (Vmax(F0)), theoretical relative maximum loads (Lmax(V0)) and starting times obtained from the profiles. Results Ten linear FV profiles and 11 exponential LV were created (Figure 1; FV: R2mean = 0.9532 ± 0.06; LV: R2mean = 0.9918 ± 0.01). There were significant negative relationships between Vmax(F0) and on-ice starting times (r(9) = -.74, p < .05; r(9) = -.71, p < .05; r(9) = -.74, p < .05) and significant positive correlations between Lmax(V0) and ice start times (r(9) = .71, p < .05; r(9) = .71, p < .05; r(9) = .72, p < .05). Discussion The FV relationship during a simulated luge start can be represented mostly through a linear regression line, supporting the findings of former studies which showed a quasilinear relationship between force and velocity in multi-joint movements (Bobbert, 2012; Jaric, 2015). In line with earlier approaches, PV relationships could be represented quite accurately by use of second-degree polynomial regressions (Allison et al., 2013; Padulo et al., 2017). Contradictory to the linear LV relationships found in other movements (García-Ramos et al., 2018), the luge start LV profile can be better represented by exponential regression curves which could be due to the minimized friction in the luge start setup. Conclusion The abilities of accelerating high external loads and producing high velocities both affect luge start time.

Physically Guided Estimation of Vehicle Loading-Induced Low-Frequency Bridge Responses with BP-ANN

The intersectional relationship in bridge health monitoring refers to the mapping function that correlates bridge responses across different locations. This relationship is pivotal for estimating structural responses, which are then instrumental in assessing a bridge’s service status and identifying potential damage. The current research landscape is heavily focused on high-frequency responses, especially those associated with single-mode vibration. When it comes to low-frequency responses triggered by multi-mode vehicle loading, a prevalent strategy is to regard these low-frequency responses as “quasi-static” and subsequently apply time-series prediction techniques to simulate the intersectional relationship. However, these methods are contingent upon data regarding external loading, such as traffic conditions and air temperatures. This necessitates the collection of long-term monitoring data to account for fluctuations in traffic and temperature, a task that can be quite daunting in real-world engineering contexts. To address this challenge, our study shifts the analytical perspective from a static analysis to a dynamic analysis. By delving into the physical features of bridge responses of the vehicle–bridge interaction (VBI) system, we identify that the intersectional relationship should be inherently time-independent. The perceived time lag in quasi-static responses is, in essence, a result of low-frequency vibrations that are aligned with driving force modes. We specifically derive the intersectional relationship for low-frequency bridge responses within the VBI system and determine it to be a time-invariant transfer matrix associated with multiple mode shapes. Drawing on these physical insights, we adopt a time-independent machine learning method, the backpropagation–artificial neural network (BP-ANN), to simulate the intersectional relationship. To train the network, monitoring data from various cross-sections were input, with the responses at a particular section designated as the output. The trained network is now capable of estimating responses even in scenarios where time-related traffic conditions and temperatures deviate from those present in the training data set. To substantiate the time-independent nature of the derived intersectional relationship, finite element models were developed. The proposed method was further validated through the in-field monitoring of a continuous highway bridge. We anticipate that this method will be highly effective in estimating low-frequency responses under a variety of unknown traffic and air temperature conditions, offering significant convenience for practical engineering applications.