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Data-driven image mechanics (D2IM): A deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics

The recent advent of deep learning (DL) has enabled data-driven models to pave the way for the full exploitation of rich image datasets from which physics can be learnt. Here we propose a novel data-driven image mechanics (D2IM) approach that learns from digital volume correlation (DVC) displacement fields of vertebrae, predicting displacement and strain fields from undeformed X-ray computed tomography (XCT) images. D2IM successfully predicted the displacements in all directions, particularly in the cranio-caudal direction of the vertebra, where high correlation (R2=0.94) and generally minimal errors were obtained compared to the measured displacements. The predicted axial strain field in the cranio-caudal direction of the vertebra was also consistent in distribution with the measured one, displaying generally reduced errors in the regions within the vertebral body. The application of D2IM to lower resolution imaging in initial testing provides promising results indicating the future viability of integrating this technology into a clinical setting. This is the first study using experimental full-field measurements on bone structures from DVC to inform DL-based models such as D2IM, which represents a major contribution in the prediction of displacement and strain fields based only on the greyscale content of undeformed XCT images. In future, D2IM will incorporate a range of biological structures and loading scenarios for accurate prediction of physical fields, aiming at clinical translation for improved diagnostics. Data AvailabilityCode for preparing dataset, training D2IM model and visualising/analysing results has been hosted on GitHub: https://github.com/PeterSoar/D2IM_PrototypeThe dataset used for this study can be found on Figshare: https://doi.org/10.6084/m9.figshare.25404220.v1

Effect of Sextant Fixating Angle of Spiral Clavicle Plate on Biomechanical Stability-A Preliminary Finite Element Study.

A spiral clavicle plate has been accepted for its superior multidirectional compatibility in the treatment of midshaft clavicle fractures from a biomechanical perspective. However, the influence of the sextant angle (spiral level) definition on biomechanical performance has not been clarified. A conceptual finite element analysis was conducted to identify the advantages and drawbacks of spiral clavicle plates with various sextant angle definitions. Conventional superior and three different conceptual spiral plates with sextant angle definitions ranging from 45 to 135 degrees were constructed to restore an OTA 15-B1.3 midshaft clavicle fracture model. Three major loading scenarios (cantilever downward bending, axial compression, and axial torsion) were simulated to evaluate the reconstructed structural stiffness and the stress on the clavicle plate and bone screws. The spiral clavicle plate demonstrated greater capability in resisting cantilever downward bending with an increase in sextant angle and showed comparable structural stiffness and implant stress compared to the superior clavicle plate. However, weakened resistance to axial compression load was noted for the spiral clavicle plate, with lowered stiffness and increased stress on the clavicle plate and screws as the spiral level increased. The spiral clavicle plate has been reported to offer multidirectional compatibility for the treatment of midshaft clavicle fractures, as well as geometric advantages in anatomical matching and reduced skin prominence after surgery. The current study supports that remarkable cantilever bending strength can be achieved with this plate. However, users must consider the potential drawback of lowered axial compression resistance in safety considerations.

A binary-medium-based constitutive model for rocks under cyclic loading

The present study extends the existing three-scale constitutive model to investigate the mechanical response of mudstone under cyclic loading conditions. The research framework encompasses macro, meso, and micro scales, with the mudstone sample treated as a macro Representative Volume Element (RVE) at the macroscale, bonded and frictional elements with distinct mesostructures at the mesoscale, and three-phase composites with varying micro-component contents at the microscale. The transitions at micro, meso, and macro scales are realized through various homogenization methods and the refined binary medium framework.To enhance the model’s predictive capabilities under cyclic loading, isotropic and kinematic hardening effects are introduced to capture the elastoplastic behavior of the frictional elements. To further enhance the model’s numerical stability and convergence, the fixed-point iteration method is introduced to leverage the relationships among macroscopic strain, and the strains of the bonded and frictional elements within the binary-medium framework. Model verification against experimental data enables the prediction of stress and deformation patterns in mudstone samples subjected to cyclic loading, with a notable reduction in model parameters. The model’s enhanced capabilities in capturing material behavior and numerical stability make it a valuable tool for analyzing the response of mudstone structures to cyclic loading scenarios.

Novel computational model for the failure analysis of composite pipes under bending

This study presents a novel computational model to investigate the bending behaviour of thin- and thick-walled composite pipes made from fully bonded fibre-reinforced thermoplastic composite materials. The primary objective is to analyse the stress state and predict potential failure modes of these pipes, which have gained significant interest in the oil and gas industry due to their advantageous properties. The developed model is validated through comparisons with finite element analysis and published results, demonstrating its accuracy and adaptability. Utilising the validated computational model, safety zones for composite pipes with various stacking sequences are established, providing valuable insights into the optimal design of composite pipes under bending loads. Furthermore, the method is employed to determine the maximum bending moment and critical bendable radius of the pipe, revealing the direct correlation between maximum bending moment and bending stiffness, independent of the bending radius. The findings of this study offer practical guidance for the design and optimisation of composite pipes in the oil and gas industry, promoting their adoption as a viable alternative to traditional metal pipes. The developed computational model serves as an efficient and reliable tool for engineers to make informed decisions in the design and selection of advanced composite materials for pipe applications, enabling the optimisation of pipe performance under various bending load scenarios.

An integrated method and tool for telescopic beams design in extendable undercarriages

Earth-moving machine builders require innovative design methods and tool to optimize structural performance while reducing production and design costs, particularly in crucial phases like undercarriage frame design and structural verification. After an in-depth description of the design flow normally followed in industry, the paper presents a computationally efficient method and tool to aid designers in dimensioning extendable tracked undercarriages, aiming to drastically reduce design time and efforts to optimize resources. The proposed tool is based on an analytical model established from in-depth analyses of the undercarriage Computer Aided Design (CAD) assembly and the expertise of the industrial partner. To address the 3D structural problem, a planar system is employed with proper corrective coefficients. These coefficients are meticulously evaluated through direct comparison with Finite Element Method (FEM) models by seamlessly integrating SolidWorks and ANSYS Workbench. The tool accepts as inputs geometric and material data, as well as specific user-defined load scenarios, providing outputs in the form of the deflected configuration of the undercarriage and stress levels. Direct comparison with the results obtained from FEM for three industrial undercarriage models demonstrates the validity of the approach, with errors consistently within the 10% range in almost all cases. This enables designers with no advanced skills in FEM to efficiently validate diverse design variants with minimal effort. Once validated, the tool is integrated with an optimizer in Matlab to conduct computationally efficient design optimization studies. The optimization problem, focused on minimizing the beam’s vertical size while maintaining structural integrity and limiting deflections, has been successfully resolved within a limited computational time, showcasing the benefits of the proposed approach for undercarriage design.

Structural simulation of Ti–Ha–CaCO3 biocomposites using finite element analysis (FEA) for biomechanical stability of hip implant

AbstractThe structural integrity of new biocomposite implants is critical in ensuring the success of biomedical implants under physiological loading conditions. Studying the stress distribution, deformation, and potential failure modes under different loading scenarios is complex, expensive, and time-consuming, as it involves repeated surgery on clinical assessment. The present study aims to investigate the biomechanical stability of hip implants made of a Ti–Ha–CaCO3 biocomposite using finite element analysis. The Ti–Ha–CaCO3 biocomposite was modeled and simulated using Solidworks. The model mesh was generated to represent the implant’s geometry accurately, and normal human activities (standing and jumping) were considered the boundary conditions with the lower part of the femur fixed. The model was subjected to static loading following ISO 7206-4 with an equivalent load of 2300 N according to ASTM F2996-13 standard. The Ti–Ha–CaCO3 biocomposite demonstrated outstanding biomechanical stability under loading circumstances. The maximum von Mises stress (354.7 MPa) observed with the GSB-femur model in the implant was below the yield strength of the titanium implant, indicating that the implant can withstand applied loads without experiencing permanent deformation. However, 74.11 MPa was obtained as acceptable von Mises stress using GSB intramedullary rods for bone fixation. The most stable implant is DSB, with the lowest displacement value of 2.68 mm. Low equivalent strains were achieved for all the implants, as the highest strain (0.012) was obtained in the simulation of the stem DSB-femur model. Low-stress signals (SS) were obtained for the implant-femur models, indicating they are suitable for replacing bone for that loading. The DSB (7.19) is the most suitable among the studied stem-femur models, and GSB (0.87) remains the suitable intramedullary rod-femur model with the lowest SS.

Experimental study on the dynamic behavior of pile-anchor structures under impact loading of debris flow and rockfall

The pile-anchor structure is widely used in slope/landslide reinforcement, and is also applicable to debris flow and rockfall barriers in mountainous areas. However, the impact behavior of this structure has not been studied. To promote the use of this retaining structure in the prevention of slope geological disasters, this study investigated the dynamic responses and impact behavior of pile-anchor structures through a set of impact experiments, wherein dry granular materials with different particle size and sliding blocks with different masses were adopted to simulate different impact loading scenarios of granular flow and rockfall. The impact pressure on the pile-anchor structure, the seismic signals induced inside the slope during the sliding and impact processes, and the deformation characteristics and failure modes of the piles and anchors were systematically investigated. The results indicate that the peak impact force and intensity of the seismic signal are affected by the particle size of the impact granular materials. As the impact loading of sliding blocks increased, the tensile force of the anchor increased nonlinearly, the distribution pattern of the pile's impact dynamic moment changed, and anchor prestress loss was observed. The preliminary results obtained by this study are expected to provide the theoretical basis for designing relevant barriers in areas prone to debris flow and rockfall, and promote the inclusivity of the impact behavior of slope retaining structures in existing design codes pertaining to retaining structures.

Modelling and simulation of natural hydraulic fracturing applied to experiments on natural sandstone cores

Under in-situ conditions, natural hydraulic fractures (NHF) can occur in permeable rock structures as a result of a rapid decrease of pore water accompanied by a local pressure regression. Obviously, these phenomena are of great interest for the geo-engineering community, as for instance in the framework of mining technologies. Compared to induced hydraulic fractures, NHF do not evolve under an increasing pore pressure resulting from pressing a fracking fluid in the underground but occur and evolve under local pore-pressure reductions resulting in tensile stresses in the rock material. The present contribution concerns the question under what quantitative circumstances NHF emerge and evolve. By this means, the novelty of this article results from the combination of numerical investigations based on the Theory of Porous Media with a tailored experimental protocol applied to saturated porous sandstone cylinders. The numerical investigations include both pre-existing and evolving fractures described by use of an embedded phase-field fracture model. Based on this procedure, representative mechanical and hydraulic loading scenarios are simulated that are in line with experimental investigations on low-permeable sandstone cylinders accomplished in the Porous Media Lab of the University of Stuttgart. The values of two parameters, the hydraulic conductivity of the sandstone and the critical energy release rate of the fracture model, have turned out essential for the occurrence of tensile fractures in the sandstone cores, where the latter is quantitatively estimated by a comparison of experimental and numerical results. This parameter can be taken as reference for further studies of in-situ NHF phenomena and experimental results.

Tribological investigations on fibre-reinforced composites: a comprehensive review considering variable velocity and load scenarios

Tribological investigations on fibre-reinforced composites: a comprehensive review considering variable velocity and load scenarios

Capability identification for new charging station into distribution system with electric, economic and traffic considerations

The shift of conventional vehicles to electric vehicles (EVs) is on pace nowadays. Increment in EVs adoption eventually results as increment of load on the existing power distribution system. This increment can adversely affect the performance of the distribution system. Location of electric vehicles charging station (EVCS) in the distribution system requires more technical finding before moving on into it. Implementation needs attention for several aspects like electric profile, economics, and traffic management and so, this work considers all of them. The impact of charging stations (EVCS) on operating parameters of the distribution network such as voltage stability, reliability and power losses are investigated by the proposed formulation of a Voltage Stability-Reliability-Power Loss (VRP) indices in this work. This index has the capabilities of considering voltage stability, reliability, and power loss under a single frame. The capabilities of the system with random load changes are compared with the base system without increments in load. This presented work gives assurance about the EV based load increment capabilities in the existing system without compromising with distribution system constraints. The main contribution of the proposed work is to examine the impact of voltage sensitivity, system stability, power losses, reliability measures, and a complex VRP index on choosing locations for EV charging stations and its effects on the existing system. Also, to ensure accurate results, these factors are assessed across seven distinct load scenarios, contributing significantly to the ongoing research in this field.

Simulation-based Optimal Sensor Placement in Tunnel Structures considering Uncertain in-situ Conditions and Multiple Loading Scenarios

The expansion of the underground infrastructure and the necessity to maintain the full functionality of the existing tunnels highlights the role of structural health monitoring in keeping track of the behaviour of the structure over time. In the study, the focus is on segmental tunnel lining for deep and long tunnels. The aim of this research is to investigate the best position for sensor placement based on the potential loading scenarios that might insist on the tunnel structure. Since for the evaluation of the lining safety we are interested in the maximum stresses reached in the structure, which might lead to durability critical cracking or crushing of concrete, a method is presented to suggest optimal positions for strain gauges. Due to uncertain geological conditions, multiple loading configurations acting on the tunnel structure are simulated using a finite element model. The results are employed to better identify the sensor locations, on the basis of where damage is prone to occur and where maximum information about the stress state in the structure can be inferred. The results obtained by the framework are discussed in light of a practical engineering perspective and the advantages as well as the limitations of the proposed approach are expounded.

Laser powder bed fusion of bio-inspired metamaterials for energy absorption applications: A review

A significant amount of research has been done in the last few decades to reduce the risk of injury for occupants and the structures that are subjected to impact loading. Metamaterials have been proven to be useful in energy-absorbing structures to improve a structure's crashworthiness performance by reducing the negative impacts during collision. The metal additive manufacturing industry, especially Laser Powder Bed Fusion (LPBF), has made it easier to produce complex metamaterials with remarkable mechanical characteristics like lightweight, high specific strength, and effective energy absorption. This review paper investigates the transformative potential of bio-inspired metamaterial designs, which are additively manufactured using LPBF machines, for use in protective energy-absorbing structures. First, biomimicry in engineering is briefly discussed. The review focuses on the energy absorption performance of different designs, like thin-walled structures and different bio-inspired metamaterials. It discusses the effects of base metal, process conditions, and manufacturing defects. Optimization methods to enhance the design and crashworthiness of these bio-inspired energy absorbers are investigated. Various characterization methodologies including experimental techniques and numerical simulations, are highlighted, with a particular emphasis on integrating manufacturing defects into simulations. Finally, possible applications and future trends in aerospace, automotive, construction, and medical applications are reviewed. Despite decades of research into energy absorbers, there remains a lack of a comprehensive review on the use of additively manufactured metamaterials as energy absorbers, particularly those inspired by nature. This review paper addresses this gap by examining recent studies in the field, assessing the effectiveness of various bio-inspired metamaterial designs, their crashworthiness, and the associated characterization methods under different loading scenarios.

Lateral-Torsional Buckling Modification Factors in Steel I-Shaped Members: Recommendations Using Energy-Based Formulations

Lateral torsional buckling (LTB) is of concern in long-span flexural members, particularly in the negative flexure regions of continuous-span, steel I-shaped members and during construction. While the elastic critical LTB capacity of a simply supported I-shaped member subjected to uniform moment has a closed-form solution, most LTB modification factors for beams subjected to moment gradients in the literature are empirical and work well only for specific loading and boundary conditions. This paper investigates the suitability of the different LTB modification factors in literature and design specifications for various loading and boundary conditions, accomplished via comparisons with analytical solutions using the Rayleigh-Ritz method and numerical solutions from finite element analyses. The analytical LTB modification factors are derived for doubly symmetric I-shaped members with different combinations of ideal flexural and torsional boundary conditions (simply supported and fixed) and subjected to different loading scenarios. The validity of the LTB modification factors determined using the Rayleigh-Ritz method and other formulae in the literature are also assessed for realistic intermediate restraint conditions, which are neither fully pinned nor fixed, by examining laterally continuous beams. Demonstrating that current design specifications for elastic critical LTB modifications are overly conservative

Application of an improved simulated annealing algorithm in satellite network routing

Abstract Satellite communication is integral to modern communication systems, yet navigating the intricacies of routing in networks characterized by high loads and dynamic evolution poses a significant challenge. This research is dedicated to enhancing satellite communication routing algorithms, with the goal of bolstering network efficiency and amplifying the success rate of business transmissions. Our approach introduces an improved simulated annealing algorithm incorporating adaptive temperature control and innovative path neighborhood exploration strategies. This novel algorithm is adept at adjusting to ever-shifting network topologies and meeting various business requirements. Our simulation results reveal that this refined algorithm outperforms traditional annealing methods in several critical aspects. It elevates the success rate of business transmissions, reduces the average number of forwardings by 6.546% across various load scenarios, and diminishes system response time by 15.05%, thereby marking a substantial improvement in network performance.

Fillet weld strength analysis for cantilever loading: an investigation of single-sided fillet weld strength in bending applications

Theoretical calculations for assessing the strength of a welded connection in design rely on two parameters: the tensile strength of the weld filler metal and the effective area. It is important to note that the type of load applied can significantly affect the theoretical strength of the weld. According to the AWS Structural Welding Code D1.1, when the load is applied parallel to the weld in a welded member, a reduction of 70% is recommended. This remaining factor of 0.30 has been determined through well-accepted tests to provide factors of safety between 2.2 for shearing forces parallel to the longitudinal axis of the weld and 4.6 for forces normal to the axis under service loading. When a load is applied perpendicular to the weld in a welded member, the entire value of the tensile strength of the weld filler metal is used to calculate the strength. However, there are no similar considerations for a load applied in a bending configuration. While it is not recommended for structural design, fillet welded members can experience loading that causes material deflection, resulting in a bending scenario. This is particularly relevant in repairs. The configuration of a cantilevered beam creates a different loading scenario with additional stresses on the weld, which differ from those of a perpendicular or parallel load. This research experiment was conducted to initially understand and analyze the strength of a GMAW weld under cantilevered bending and to derive a mathematical equation that provides a factor of safety in the range of 2.2-4.6, similar to the previous findings.

Agricultural watershed conservation and optimization using a participatory hydrological approach.

Maximizing the impact of agricultural wastewater conservation practices (CP) to achieve total maximum daily load (TMDL) scenarios in agricultural watersheds is a challenge for the practitioners. The complex modeling requirements of sophisticated hydrologic models make their use and interpretation difficult, preventing the inclusion of local watershed stakeholders' knowledge in the development of optimal TMDL scenarios. The present study develops a seamless modeling approach to transform the complex modeling outcomes of Hydrologic Simulation Program Fortran (HSPF) into a simplified participatory framework for developing optimized management scenarios. The study evaluates seven conservation practices in the Pomme de Terre watershed in Minnesota, USA, focusing on sediment and phosphorus pollutant load reductions incorporating farmers' opinions to guide practitioners toward implementing cost-effective CPs. Results show reduced tillage and filter strips are the most cost-effective practices for non-point source pollution reduction, followed by conservation cover perennials. The integration of SAM with HSPF is crucial for sustainable field-scale implementation of conservation practices through enhanced involvement of amateur-modeling stakeholders and farmers directly connected to fields.

Short-term stochastic multi-objective optimization scheduling of wind-solar-hydro hybrid system considering source-load uncertainties

Uncertainties in energy outputs (source side) and load side are simultaneously present and cannot be ignored in the actual operation of multi-energy systems. Adopting a reasonable uncertainty modeling method and understanding the impact of source-load uncertainties on optimization scheduling are key to formulating accurate and effective multi-energy scheduling plans. To address the uncertainties on both the source side and the load side in wind-solar-hydro hybrid systems, this paper proposes a multi-objective optimization scheduling model based on stochastic programming theory. The model aims to maximize the net profit of the system's power generation and minimize the fluctuation of the remaining load. It employs Vine-Copula coupled with Monte Carlo simulation and the deep learning method TimeGAN to generate joint wind and solar power output and load scenario sets. The generated source-load uncertainty scenarios are then reduced to representative scenarios using the K-Means clustering method, which are used as inputs for the scheduling model. The proposed model is applied to a wind-solar-hydro energy base in China, and the results show that: 1) The Vine-Copula-based source-side scenario generation method can quantitatively consider the correlations among meteorological factors. The relative errors of the generated scenarios' statistics compared to the original data are all less than 5%, and the relative errors of the correlation coefficients are less than 10%. 2) The TimeGAN-based load-side scenario generation method avoids the presupposition of the load probability distribution. Compared to the original data, the generated scenarios have R2 and Pearson correlation coefficients of 0.77 and 0.87, respectively. Additionally, TimeGAN shows significant advantages over traditional random sampling methods in simulating extreme scenarios. 3) Both source-side and load-side uncertainties significantly impact the optimization scheduling results of multi-energy systems, leading to increased fluctuation of the remaining load and decreased net profit. 4) The combined source-load uncertainties have a synergistic negative impact on the multi-objective optimization scheduling results. 5) The Pareto front of the optimization results is a concave function with low marginal benefits. Decision-makers should adopt a compromise solution as a guide for the operation of multi-energy systems.

The value of real-time adjustable remedial action schemes

Remedial action schemes (RAS) are often seen as an inexpensive way to relieve contingency-related grid congestion without building new transmission infrastructure. However, RAS settings often remain fixed during real-time operation and do not adapt to variation in operating conditions due to renewable and distributed generation. This lack of adaptability may cause suboptimal settings and possibly insecure operations. To assess the value of allowing RAS settings to vary real time and the benefit of considering multiple load and generation scenarios, we propose a mixed integer optimization framework which identifies optimal RAS actions while incorporating multiple load and renewable energy scenarios. We also propose an iterative algorithm that efficiently solves the optimization problem, leveraging the fact that only a few scenarios and contingencies are binding at optimality. We demonstrate the benefits of (i) updating RAS more frequently and (ii) considering multiple load scenarios by performing case studies on the RTS-GMLC system.

Pre-Construction predictions of the Loads from large Ice Ridges Interacting with the Confederation Bridge Piers

During the design phase of the Confederation Bridge in Canada, the Canadian government Public Works and Government Services Canada asked the National Research Council (NRC) of Canada to provide information on ice loads from large ridges using a wide range of predictive technologies. The NRC put together a team that looked at loads from several sources including analytical models, physical model tests, finite element models, discrete particle models, and full-scale data. The ice loading scenario was an extreme first-year ridge loading one of the bridge piers. A large number of analytical models were used and the load components were separated into those from the consolidated layer, the sail, and the keel. An upper bound prediction from this approach gave a value of 16 MN on a pier, but the assumptions that were used to arrive at this value did not match observed behavior in the physical and numerical studies of the program. Physical model tests indicated that the loads could be 10.5 MN with a load of 7.3 MN from the keel and 3.2 MN from the consolidated layer and sail. A finite element analysis indicted a range of predicted values of 10 MN to 12 MN depending upon the assumptions used. A discrete particle analysis predicted load values from 2.2 MN to 9.5 MN depending upon the assumptions used in describing the stiffness of the ridge. A review of full-scale measurements on lighthouses and ships suggested that the loads could range from 7.3 MN to 10.4 MN. These predicted values compare to the highest load measured on the Confederation Bridge over a twenty-year span of just over 8 MN. This paper outlines the approaches used for this prediction study and their resulting predictions. It shows the value of using multiple approaches for load predictions for offshore structures in ice-covered waters.

Near real-time calculation of the critical plane in all surface nodes of large metallic structures under multiaxial fatigue loading by visualization of the solution space

Applications of critical-plane-based fatigue criteria on large FE meshes remain uncommon, primarily due to the absence of a search scheme capable of identifying the critical plane for multiaxial loading scenarios in a way that is both reliable and fast enough. To address this gap, we introduce a three-module optimization scheme based on the Maximum Variance Method (MVM), guided by insights learned from visualizing the solution space. These visualizations not only validate the MVM strategy but also reveal a symmetry axis, which in turn assists in selecting the most critical among reciprocal solutions. Through iterative refinement of optimization parameters on automatically generated loading signals, our algorithm achieves a significant speedup over existing methods, while improving accuracy. The potential that comes with a processing speed of 10k nodes per CPU minute is demonstrated on a design challenge involving an additively manufactured Ti–6Al–4V bearing house subjected to non-proportional loading. A full critical-plane-based fatigue analysis on the 100k surface nodes takes 75 s with C++ PPL across 16 threads, which is fast enough to enable integration into iterative procedures such as topology optimization, promising substantial advancements in both academic research and engineering practices.