Load State Research Articles

PARAMETRIC DESIGN AND ADAPTIVE SIZING OF LATTICE STRUCTURES FOR 3D ADDITIVE MANUFACTURING

The present research is developed into the realm of industrial design engineering and additive manufacturing by introducing a parametric design model and adaptive mechanical analysis for a new lattice structure, with a focus on 3D additive manufacturing of complex parts. Focusing on the land-scape of complex parts additive manufacturing, this research proposes geometric parameterization, mechanical adaptive sizing, and numerical validation of a novel lattice structure to optimize the final printed part volume and mass, as well as its structural rigidity. The topology of the lattice structures exhibited pyramidal geometry. Complete parameterization of the lattice structure ensures that the known geometric parameters adjust to defined restrictions, enabling dynamic adaptability based on its load states and boundary conditions, thereby enhancing its mechanical performance. The core methodology integrates analytical automation with mechanical analysis by employing a model based in two-dimensional beam elements. The dimensioning of the lattice structure is analyzed using rigidity models of its sub-elements, providing an evaluation of its global structural behavior after applying the superposition principle. Numerical validation was performed to validate the proposed analytical model. This step ensures that the analytical model defined for dimensioning the lattice structure adjusts to its real mechanical behavior and allows its validation. The present manuscript aims to advance additive manufacturing methodologies by offering a systematic and adaptive approach to lattice structure design. Parametric and adaptive techniques foster new industrial design engineering methods, enabling the dynamic tailoring of lattice structures to meet their mechanical demands and enhance their overall efficiency and performance. Keywords: Computer-Aided Design, Industrial Design, Innovative Design, Additive Manufacturing, FEM Simulations

A novel load-sensing sliding hip screw to aid in the assessment of intertrochanteric fracture healing.

Bone healing after sliding hip screw internal fixation of intertrochanteric hip fractures is difficult to monitor with radiography. In this study, we describe and evaluate a device to non-invasively determine the loading on the screw implant as a possible qualitative indicator of bone healing. A novel load-sensing sliding hip screw (LS-SHS) was fabricated containing a radio-dense tungsten indicator rod that moves and can be measured within the screw cannulation when the screw bends under load via plain radiography. Screw bending was assessed in intact femurs and unstable A1 intertrochanteric fractures using experimental axial loading of femoral composite Sawbones® and femoral human cadaveric specimens. Sensor readings were visually tracked using plain radiographs at each load state. The sensor exhibited linear response to implant strain in the unstable fracture indicating that the implant supported the major component of the applied load. This was consistently measurable using radiography throughout loading cycles across the mechanical and cadaveric fracture models. Sensor readings indicated that the implant was mostly unloaded in the intact models. The slope of the curve was approximately equal in the composite and cadaveric models (1.0µm/N and 0.08µm/N, respectively). Sensor noise levels were sufficient to detect 10% of the applied load of 80kg, which has the potential to qualitatively assist clinicians in tracking fracture healing progression. Clinicians must carefully monitor their patients for signs of SHS implant failure after surgery. This device quantitively measures implant loading which could qualitatively assist clinicians in the assessment of fracture healing.

Two-stage Non-Intrusive Load Monitoring method for multi-state loads.

The loads that have several working states cannot be accurately distinguished by the conventional Non-Intrusive Load Monitoring (NILM) methods. This paper proposed an improved NILM method based on the Resnet18 Convolutional Neural Network (CNN) and Support Vector Machine (SVM) algorithm to address the misidentification of multi-state appliances. The V-I trajectories of loads are at first classified with Resnet18. Then, load features with low redundancy is obtained through the Max-Relevance and Min-Redundancy (mRMR) feature selection algorithm from various operating states of loads that were not successfully classified. The SVM algorithm is developed for two-stage identification to achieve high accuracy of classification for identifying the multi-state appliances quickly. This proposed NILM method can significantly improve the accuracy of identification for multi-state loads. Finally, the Plaid dataset is acquired to validate the effectiveness and accuracy of the proposed method.

Ultrahigh Piezoelectricity in Truss‐Based Ferroelectric Ceramics Metamaterials

AbstractConventional porous ferroelectric materials sacrifice their piezoelectric constants for improving various figures of merit due to a rapidly decreased dielectric constant. Here, novel truss‐based ferroelectric metamaterials that simultaneously offer ultrahigh piezoelectric constants and ultralow dielectric constants, originating from the unique combination of truss loading states and polarization direction, are discovered. The homogenization method alongside an analytical model is proposed to predict and elucidate their extraordinary properties, while a customized ferroceramic additive manufacturing platform is resorted to fabricate them. Unlike porous ferroelectrics, ultrahigh piezoelectric constants at low relative densities (ρr ≈0.1) are attained. For example, with appropriate scaling, the experimental values of d31, d33, and d42 for a ferroelectric octet truss with ρr = 0.1, can reach 849, −659, and 836 pC N−1, respectively, which are 3.14, 6, and 2 times higher than the counterpart of bulk BaTiO3 ceramics. Combined with the ultralow dielectric constant, extremely high ferroelectric figures of merit, e.g., piezoelectric voltage constant of 11.098 Vm N−1, piezoelectric energy harvesting figure of merit 9422 × 10−12 m2 N−1, and pyroelectric voltage sensitivity of 56.7 × 10−3 m2 C−1, are also observed. The multifunctional ferroelectric metamaterials open new avenues for their applications in self‐powered ultrasensitive accelerometers, high‐performance noncontact sensors, and wearable input devices.

Experimental Assessment of Energy-Ecological Parameters of Biogas-Powered Tractor Within Circular Economy

One of the solutions contributing to the development of energy independence is the utilization of biogas as an alternative fuel for agricultural tractors. Biogas is recognized as a renewable energy source, and its usage aids in the reduction in greenhouse gas emissions on a global scale. The reuse of this material/waste exemplifies the concept of a circular economy. Several models of agricultural tractors designed explicitly for biogas utilization or adaptable for its use are available in the market. This study aimed to evaluate the energy-ecological parameters of the MP tractor (T6.180 Methane Power) powered by Compressed Natural Gas (CNG) in comparison to its structurally identical counterpart fueled by Diesel (T6.180 Electro Command). Based on the Air–Fuel Ratio (AFR) coefficients for diesel and methane, as well as values of air excess ratios (λ) and the proportions of CO and CO2 emissions determined for various engine load states, the mass emission of selected exhaust components for the examined tractors was estimated. This research highlights that biogas-powered tractors hold the potential to contribute to the sustainable development of agriculture through the reduction in greenhouse gas emissions, improvement in farm energy autonomy, and optimal resource utilization, closely aligned with the principles of a circular economy.

Intelligent process migration in heterogeneous distributed systems

In distributed processing environments, multiple groups of processes are found sharing resources and competing for access. These processes may or may not require synchronization and it is essential to reach a consensus to manage access to resources in a way that establishes a strict order, thus ensuring mutual exclusion. The proposal presented is an innovative and effective solution for the management of shared resources in distributed systems, which allows solving problems related to overload and workload balancing. The evaluation of the state of computational loads and the final comparison using standard deviation are useful tools to detect and correct imbalances in the system. In addition, the possibility of establishing initial configurations of the algorithm for each particular situation allows adapting the solution to the specific needs of each system.

In-Situ Experimental Study of Closed-Diaphragm Wall Foundations for Cross-Sea Suspension Bridges

This study examines the in-situ lateral static load behavior of a closed-diaphragm wall foundation, aiming to better understand its load–displacement response, structural behavior, and soil interaction under horizontal loading. An in-situ static load test was conducted with a maximum applied load of 70 MN, revealing that the diaphragm wall initially exhibits a linear load–displacement response, which becomes increasingly nonlinear as the load increases. The horizontal displacement of the lateral walls is nearly identical to the overall displacement of the diaphragm wall, making it a reliable indicator of the wall’s load state, particularly when it is challenging to measure total displacement. The wall behaves as a rigid body with minimal relative displacement between sections, and overturning failure is identified as the primary failure mode. Earth pressure distribution varies around the wall: passive earth pressure is observed at the front edge, while active and passive pressures alternate at the rear edge. These findings provide valuable insights into the design of diaphragm wall foundations, emphasizing the importance of lateral displacements.

Optimized operation of AC–DC microgrid cluster with modified PLL and socket protocol

AbstractMicrogrids integrating inverter based resources face challenges like stability issues during voltage fluctuations and reliance on diesel generators in islanded mode. This paper presents a novel control strategy for photovoltaic and wind‐integrated microgrids to enhance reliability and efficiency. The strategy utilizes a modified phase‐locked loop with droop control for seamless synchronization in grid‐connected and islanded modes. Central to this approach is the localized autonomous controller with a socket protocol interfaced communication layer, dynamically managing operations based on real‐time conditions such as generation, load, and battery state of charge. By integrating battery storage systems, the strategy reduces diesel generator dependency during grid outages. Comprehensive simulations and controller hardware‐in‐the‐loop testing validate its effectiveness, demonstrating improved stability and decreased reliance on diesel generators. The socket protocol enhances real‐time communication, monitoring, and optimization of microgrid operations, ensuring optimal battery storage system utilization and minimal diesel usage. The proposed strategy addresses critical microgrid challenges, offering significant advancements in enhancing system resilience.

A Power Extraction Approach with Load State Modification for Energy Disaggregation

A Power Extraction Approach with Load State Modification for Energy Disaggregation

The relationship between crack front twisting, plastic zone and [formula omitted] curve of fatigue cracks in AA2024-T3

While fatigue crack growth is inherently a three-dimensional challenge, it is often modelled in two dimensions for simplicity. This study explores the relationship between the two-dimensional primary plastic zone (PPZ) on the surface of specimens and the three-dimensional twisting of the crack front leading to a slanted crack front. Fatigue crack growth experiments were conducted using 2-mm-thick MT-160 AA2024-T3 sheet specimens in both L-T and T-L crack orientations. High-resolution digital image correlation (HR-DIC) was employed to capture the PPZ within the surface displacement data and correlate its morphology with the twisting angle of the slanted crack front.Further, this study investigates how the twisting of the crack front affects the crack propagation curve, represented as da/dN−ΔK, by examining its influence on the mixed-mode I/II/III loading state along the crack front. Here, we utilize finite element simulations to derive a mapping function that adjusts ΔK to ΔKeqv, accounting for the twisted crack front caused mixed-mode loading conditions. The modified da/dN−ΔKeqv curves for both L-T and T-L orientations demonstrated similar behaviour, suggesting that differences in their crack front twisting may explain the discrepancies observed in their traditional da/dN−ΔK crack propagation curves.

Power-controllable variable refrigerant flow system with flexibility value for demand response

With the increase of renewable energy sources in the power supply, the issues of balancing power supply and demand are becoming severe. Demand response, by altering the demand-side load state, has been proven as a good method to solve the supply and demand balance problem. Variable refrigerant flow system has great potential in demand-side loads and is poised to become the mainstay of demand response. However, the traditional temperature or compressor state control of variable refrigerant flow systems does not allow for better power regulation for the power system. To address this problem, this paper proposes a power-controllable variable refrigerant flow system with demand response flexibility value for power regulation. The demand response flexibility value is designed as a subjective indicator to satisfy the heterogeneous customer comfort requirement. The predictive mean vote as an objective indicator of customer comfort coordinates with the demand response flexibility value. A fuzzy control strategy for variable refrigerant flow systems is designed to balance power system requirements and customer comfort requirements. The experiment result demonstrates that the power-controllable variable refrigerant flow system can provide power regulation service to the power system with a maximum power regulation deviation of 3.67%. By guaranteeing consumer comfort, the higher the flexibility value, the shorter the consumer’s participation time in demand response. The demand response flexibility values can provide regulation configuration for demand response in practical engineering.

Biomechanical conditions of subtalar joint arthrodesis with calcaneal locking nail: A probabilistic numerical study.

Subtalar joint arthrodesis is primarily indicated for advanced osteoarthritis, hindfoot deformity, and/or instability. During the first 6-10 weeks after surgery, there is an intermediary structurally weaker state before complete bony fusion of the calcaneus and talus occurs. Loading of the foot can lead to mechanical stresses and relative movements in the former joint gap, which can impede the fusion process. The objective of this study was to examine the mechanical healing conditions for a subtalar arthrodesis with a calcaneal locking nail. A probabilistic finite element model of the subtalar joint with a calcaneal locking nail was created to represent the foot post-surgery that accounts for the uncertainty of the material properties. The model differentiates between cortical and cancellous bone and includes non-linear contact definitions in the subtalar joint. Multiple loading scenarios, including hindfoot inversion/eversion, were simulated to determine bone and implant stresses. Utilizing local articular coordinate systems, a displacement analysis was established to separate normal and tangential components and account for their separate effects. The loading of the locking nail was assessed through section moments. Under inversion/eversion loading, the area near the locking screws and upper end of the nail experienced the highest stresses. The maximum stresses in cortical and cancellous bone were 112±8.3 MPa and 2.1±0.2 MPa, respectively. The comparison of the von Mises and maximum principal stresses for the bones showed a load case dependency with strong effect on tensile loading states. The proposed method for the analysis of relative displacement in the local articular coordinate systems showed joint regions exhibiting normal and tangential movements that changed with the considered loading states. It was found that tangential displacements of up to 0.19 mm are related to the torsional loading of the calcaneal locking nail, which is connected to the corresponding torsional stiffness of the implant and its fixation in the calcaneus and talus. Normal displacements in the joint gap of up to -0.18 mm can be shown to be governed by the bending moments acting on the calcaneal locking nail, which are linked to the nail's bending stiffness. The ratio of tangential and normal displacement in the critical inversion configuration was determined to be -1.1. Inversion and eversion loads can lead to significant mechanical loading of the bones and to bending and torsional loading of the locking nail. The bending leads to normal displacements in the articular gap. Torsions can lead to significant tangential displacements that have been shown to promote non-union instead of bony fusion.

The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market

In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in the wider economic development. Electricity load and price forecasting have been a key focus of researchers in the last decade due to the substantial economic implications for both producers, aggregators and end consumers. Many forecasting techniques and methods have emerged during this period. This paper conducts a extensive and analytical review of the prevailing load and electricity price forecasting methods in the context of the modern wholesale electricity market. The study is separated into seven main sections. The first section provides the key challenges and the main contributions of this study. The second section delves into the workings of the electricity market, providing a detailed analysis of the three markets that have evolved, their functions and the key factors influencing overall market dynamics. In the third section, the main methodologies of electricity load and price forecasting approaches are analyzed in detail. The fourth section offers a comprehensive review of the existing literature focusing on load forecasting, highlighting various methodologies, models and their applications in this field. This section emphasizes the advances that have been made in all categories of forecasting models and their practical application in different market scenarios. The fifth section focuses on electricity price forecasting studies, summarizing important research papers investigating various modeling approaches. The sixth section constitutes a fundamental discussion and comparison between the load- and price-focused studies that are analyzed. Finally, by examining both traditional and cutting-edge forecasting methods, this review identifies key trends, challenges and future directions in the field. Overall, this paper aims to provide an in-depth analysis leading to the understanding of the state-of-the-art models in load and price forecasting and to be an important resource for researchers and professionals in the energy industry. Based on the research conducted, there is an increasing trend in the use of artificial intelligence models in recent years, due to the flexibility and adaptability they offer for big datasets, compared to traditional models. The combination of models, such as ensemble methods, gives us very promising results.

Advanced Design of Naval Ship Propulsion Systems Utilizing Battery-Diesel Generator Hybrid Electric Propulsion Systems

As advanced sensors and weapons require high power, naval vessels have increasingly adopted electric propulsion systems. This study aims to enhance the efficiency and operability of electric propulsion systems over traditional mechanical propulsion systems by analyzing the operational profiles of modern naval vessels. Consequently, a battery-integrated generator-based electric propulsion system was selected. Considering the purpose of the vessel, a specification selection procedure was developed, leading to the design of a hybrid electric propulsion system (comprising one battery and four generators). The power management control technique of the proposed propulsion system sets the operating modes (depending on the specific fuel oil consumption of the generators) to minimize fuel consumption based on the operating load. Additionally, load distribution control rules for the generators were designed to reduce energy consumption based on the load and battery state of charge. MATLAB/Simulink was used to evaluate the proposed system, with simulation results demonstrating that it maintained the same propulsion performance as existing systems while achieving a 12-ton (22%) reduction in fuel consumption. This improvement results in cost savings and reduced carbon dioxide emissions. These findings suggest that an efficient load-sharing controller can be implemented for various vessels equipped with electric propulsion systems, tailored to their operational profiles.

On-demand routing algorithm for multipath selection based on node load states in mobile ad hoc networks

On-demand routing algorithm for multipath selection based on node load states in mobile ad hoc networks

Approaches and Challenges in FEED and Detailed Design Process of Floating Substructures

Abstract In the FEED or detailed design phases, the floating foundation designers have to deal with complex structural design aspects and meet certification or class requirements for structural verifications, such as yield and buckling checks as well as fatigue checks for steel structures. The designer faces several challenges during the structural verification process, starting with the accurate definition of the complex external load state with the simultaneous action of aerodynamic, hydrostatic and hydrodynamic loads, inertia and mooring loads, followed by the processing and handling of very large load case tables required for the analysis of floating wind turbines, down to time efficient post-processing of the analysis results compatible with typical commercial project schedules. The paper discusses some of the currently existing and applied methodologies on how the structural checks are typically performed in these circumstances, and addresses their advantages and shortcomings. In addition, a new Global Influence Superposition (GIS) methodology that has been developed by Ramboll is presented, which is able to address many of the existing challenges in an efficient manner.

Deformation-fractional change in resistance model of SMA fiber reinforced mortar beams

Superelastic shape memory alloys (SMA) are metallic alloys that can enable components with self-recovery of cracks and deformation when combined with cement-based materials. Meanwhile, the monitoring method based on fractional change in resistance (FCR) can achieve self-monitoring of components throughout the entire loading process. In this study, the relationship between crack recovery characteristics and FCR of SMA fiber reinforced mortar beams subjected to flexural cyclic loading was analyzed. The beams with SMA fiber volume fractions of 0.1 %, 0.3 %, 0.5 %, and 1.0 % were tested under three-point bending loads. During the loading process, the FCR of the specimens were monitored by the four-electrode method. Finally, the deformation-FCR model for the whole process of the specimens was established to realize the real-time monitoring of the loading state of mortar beams. The results show that SMA fibers can enhance the flexural strength of mortar beams by a maximum of about 64 %, reduce residual deformation, and improve deformation self-recovery ability. The mid-span deflection recovery rate and crack size recovery rate generally increase with higher fiber volume fraction, which can maintain a better deformation recovery effect at the early stage of cracking and gradually decrease with the expansion of cracks. There is a close relationship between the FCR and the degree of crack development that the FCR increases with crack expansion and the magnitude of FCR decreases with increasing fiber content. The established first-order logarithmic fitting model can well describe the relationship between the FCR and cracking, which can provide reference for crack monitoring.

Microvoiding and constitutive damage modeling with artificial neural networks

Continuum models of porous media have revolutionized computational fracture mechanics for traditional ductile materials, but the inherent assumptions have limited generalizability to other target materials or loading conditions. Here, we adopt a series of artificial neural networks (ANNs) to predict both the microscopic voiding characteristics (void shape, porosity) and macroscopic stress–strain constitutive response of porous elasto-plastic materials under various deformation states. We train the ANNs on a dataset generated from finite element models of 3D representative volume elements (RVEs), each containing a discrete spherical void, subjected to combinations of loading states. Results show that the data-driven model is capable of interpolative predictions as well as some levels of extrapolative predictions across a wide range of initial porosities (0–20%) and loading states outside of the training dataset, even at high deformation strains which induce extensive material softening and void growth. Through transfer learning, we further demonstrate that the ANNs, originally trained on a specific porous material dataset, can be readily adapted to other porous materials with substantially different properties through a significantly reduced training dataset. We discuss the implications of this machine learning approach vis-à-vis the extensively-developed Gurson model for porous material damage and failure predictions.

Cavitation damage in rubber-like silicone adhesives

In this work, the failure of rubber-like materials by cavitation is investigated. Under local triaxial loading states, as they can occur in confined geometries of adhesive bonds, the instantaneous formation of voids can be observed. Analytical results of cavitation in a commercial silicone adhesive are provided. The results show that cavitation voids can be distinguished from manufacturing voids by the inner surface of the void. The surface of the cavitation void is rugged and shows a complex fracture pattern. Pancake experiments have been conducted for different ratios of radius and thickness. To assess the fracture process of cavitation onset one macroscopic and two asymptotic solutions of the energy release rate of cavitation voids are proposed. The solutions are compared and their limitations for the analysis of cavitation onset are discussed.

Application of SWAT to assess peatland forestry impacts on water quality

ABSTRACT Peatland drainage can affect the natural state of hydrological conditions and nutrient loading but is rarely included in catchment-scale models. To understand the gap, we aimed to use the soil and water assessment tool (SWAT) to observe drained peatlands and their properties to predict nutrients and suspended solids (SS) in the peatland-dominated Simojoki catchment. We integrated drainage networks in SWAT to (i) identify drainage parameters; (ii) determine annual loads and mean concentrations of SS, organic phosphorus (Org-P), total phosphorus (TP), organic nitrogen (Org-N), and total nitrogen (TN); (iii) understand spatial variation of nutrients and SS; and (iv) investigate uncertainty ranges for the estimates. The calibrated model showed a 9.6 per cent bias between the simulated flow and the observations with low-to-medium loading variations for the water quality parameters. For Org-N and TN, the highest loading per year was at the downstream outlet, whereas for SS, Org-P, and TP, it was higher at the upstream outlet of the catchment. This approach of representing the drained peatland in SWAT indicated maximum spatial distributed load in the peat soil in the clear-cut area and can be beneficial in future hydrological modelling efforts in identifying the status of nutrients or SS.