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In order to solve the problems of the frequent lifting sluice gates, the high intensity and the low efficiency of hoists in hydropower stations, a method of path planning and trajectory generation of hoists suitable for the unmanned automation was proposed. Aiming at the basic problems of the loading and unloading sequence and the path planning of hoist lifting gates, the analysis model of lifting operations was established, the working space of the hoist and the movement direction of the three mechanisms of lift, trolley and gantry were defined, and the initial position and unloading position database of the gates were constructed. According to the loading and unloading sequence of the gates and considering the operating environment factors, the operation path planning of the lifting gates was carried out. Considering the gate swing, the underactuated coupling relation between the gate swing and the trolley acceleration was analyzed based on the phase plane, the motion parameters were determined, and the desired trajectory of the trolley was generated. In view of the phenomena such as the groove interference and the slot jamming, a stepwise deceleration planning method for the gate falling process was proposed. The simulation and test results show that the hoist completes the lifting gates operation according to the expected plan, and the swing angle of the gate swings within a reasonable range. The method is suitable for the unmanned automatic operation environment of the hoist of hydropower stations and lays a theoretical foundation for the realization of the intelligence of hoists.

Mutually exclusive products (such as liquids, hazardous chemicals, etc.) cannot be mixed into the same container. Logistics companies usually use multi-compartment trucks to deliver mutually exclusive products to customers. The loading and vehicle routing strategies are the key issues to determine the distribution efficiency and distribution costs. Considering the constraints of loading and unloading sequence and transportation time of mutually exclusive products, a joint optimization model of loading and distribution is constructed to minimize the distribution cost. This paper designs an improved genetic algorithm for solving the model, using the queen evolution and the edge reconstruction crossover operations based on probability to lift the ability of finding the optimal solution. Then we construct the testing examples based on the vehicle routing problem benchmark provided by Augerat to verify the running time and solving efficient of genetic algorithm. The simulation results show that, the solutions obtained by improved genetic algorithm are better than those of classical genetic algorithm, for small-scale examples, the improved genetic algorithm can obtains global optimal solution; for the medium-sized or large size examples with no more than 101 customers, the approximate optimal solution can be obtained in 130 seconds using genetic algorithm. The innovation of this paper lies in the establishment of a mathematical model for a new expended vehicle routing problem and the design of a fast and effective algorithm for solving the model. The mathematical model and algorithm of this paper provide a theoretical basis and algorithmic support for logistics companies to draw up distribution schedule of mutually exclusive products. [ABSTRACT FROM AUTHOR]

The lifting construction process of high-rise structure is very difficult, and the unloading and demolition of lifting equipment and temporary support pose a greater challenge to the construction safety of high-rise structure. With the Beijiang Pearl Tower Project as the background, the unloading process of the revolving restaurant after hoisting was studied by combining Abaqus life and death element technology with unloading process monitoring. Five unloading schemes were formulated to analyze and compare the influence of different unloading sequence on the internal force of the structure. The finite element simulation results are basically consistent with the monitoring data, indicating that the technology is effective and feasible, and the combination of the two can effectively ensure the safety of the construction unloading process. The analysis results show that: for the overall lifting construction of multi-layer frame convex structure of similar high-rise structure, when unloading the temporary support, it is appropriate to first remove the secondary components outside the floor where the lifting steel strand lifting point is located, then gradually remove the steel strand load, and remove the steel strand and equipment, and finally remove the main support components near the upper and lower lifting points of steel strand.

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The use of carbon fiber-reinforced polymer (CFRP) rods offers a good solution for external strengthening of flexural reinforced concrete (RC) members. Limited data are available on the behavior of beams externally reinforced with CFRP rods under a loading–unloading protocol, which is of great importance for structural components subjected to vehicle loading. The embedment depth mandated by the majority of standards cannot always be acquired due to concrete cover limitations; the influence of embedment depth under this loading–unloading sequence needs to be investigated. This research studied the effects of rod embedment depth by comparing fully-embedded rods with half-embedded rods under a loading–unloading protocol and comparing the results with monotonic responses. An identical specimen without CFRP reinforcement functioned as the controlling element. The near-surface mounted technique (NSM) was used to integrate the rods with the concrete. The results show that CFRP rods positively affect the load-carrying capacity under a loading–unloading condition. The rods reduce the member's ductility under monotonic loading but have no negative impact under loading–unloading. Whereas the difference in embedment depth configuration slightly affected the enhancement under monotonic loading, the half-embedded rods drastically reduced the capacity improvement under the loading–unloading sequence. An embedment depth deviating from the advised depth, should not be implemented for members subjected to a loading–unloading condition. The CFRP placement method had an impact on the failure behavior of the elements. The half-embedded rod failed by debonding between the rod and the epoxy resin, while the fully-embedded members were characterized by concrete spalling. [ABSTRACT FROM AUTHOR]

The erection phase is the most vulnerable period in the life of a structure. However, no mature and effective method for optimizing the construction procedures of large-span steel structures is yet available. Thus, proposing an optimization method for constructing such structures is critical. A real-coded genetic algorithm (GA) was proposed in the present work, and the selection, crossover, and mutation operators were programmed. The proposed algorithm is effective in optimizing integer combinations and sequences, such as an unloading sequence. A series of problems that occurred during the erection of conchshaped complex large steel structures was optimized using the proposed method. Optimum analysis was conducted using MATLAB and the general finite element software ANSYS. The optimal layouts of the lifting points, false work, and unloading sequence were derived. The influence of the GA parameters on its convergence efficiency was also studied. Therefore, the proposed GA method is reliable and effective for optimizing the construction procedures of large-span steel structures. [ABSTRACT FROM AUTHOR]

• A formula is derived to estimate the expected number of rehandles. • An integer programming model is established for solving small-scale instances. • A two-stage search algorithm is designed to find an optimal solution in seconds. • The convergence and the time complexity of the algorithm are demonstrated. This study focuses on the inbound container unloading and stacking problem at container terminals and achieves both a reasonable unloading sequence and the optimal yard stacking distribution. A formulation is proposed as the relational expression between the expected number of rehandles and the stacking height. Based on the formulation, an integer programming model is established to both find the optimal stacking distribution and unloading sequence and attempt to minimize the expected number of rehandles. The model can be solved by the commercial solver for small-scale instances. To solve for large-scale instances in the real world, a two-stage search algorithm is designed, therein incorporating an initial stage for generating the feasible solution and a neighborhood search stage for finding the optimal solution. The algorithm can find an optimal solution in polynomial time, which is proved by theoretical methods and evidenced by numerical experiments. [ABSTRACT FROM AUTHOR]

New excavation or tunnelling affects the stress state of soils in ground. The change of stress state due to excavation may affect the cyclic behaviour of soils. Cyclic loading, such as traffic and earthquake loading, induced ground deformation may be greater than expected if such effect is not considered. A series of cyclic triaxial tests were performed on Sydney sand with different relative densities. The effect of unloading sequence on deformation of the sand under cyclic loading was simulated by reducing lateral stress in steps between loading cycles. The dependence of strain accumulation on the magnitude of confining pressure reduction and on unloading stress paths was studied. The results indicate that the sand has a memory of stress history and the stress history of such unloading enlarges the strain accumulation during the subsequent cycles, and the greater the reduction of lateral stress, the greater the accumulated strain. Under cyclic loading, the accumulated axial strain could increase nonlinearly or linearly with the ratio of unloading magnitude to initial mean effective stress, depending on the stress state before cyclic loading. The unloading stress paths have limited effects on the final accumulated strain if the initial and final stress states are the same. The variation of strain accumulation direction attributes to the change of average stress ratio resulting from lateral stress reduction, but hardly depends on relative density and unloading stress paths. The strain accumulation direction after unloading roughly agrees with the modified Cam Clay flow rule. [ABSTRACT FROM AUTHOR]

To improve the efficiency of mobile robot movement, this paper investigates the fusion of the A* algorithm with the Dynamic Window Approach (DWA) algorithm (IA-DWA) to quickly search for globally optimal collision-free paths and avoid unknown obstacles in time. First, the data from the odometer and the inertial measurement unit (IMU) are fused using the extended Kalman filter (EKF) to reduce the error caused by wheel slippage on the mobile robot’s positioning and improve the mobile robot’s positioning accuracy. Second, the prediction function, weight coefficients, search neighborhood, and path smoothing processing of the A* algorithm are optimally designed to incorporate the critical point information in the global path into the DWA calculation framework. Then, the length of time and convergence speed of path planning are compared and simulated in raster maps of different complexity. In terms of path planning time, the algorithm reduces by 23.3% compared to A*-DWA; in terms of path length, the algorithm reduces by 1.8% compared to A*-DWA, and the optimization iterations converge faster. Finally, the reliability of the improved algorithm is verified by conducting autonomous navigation experiments using a ROS (Robot Operating System) mobile robot as an experimental platform. [ABSTRACT FROM AUTHOR]

To address the shortcomings of traditional bionic algorithms in path planning, such as inefficient search processes, extended planning distances and times, and suboptimal dynamic obstacle avoidance, this paper introduces a fusion algorithm called NRBO-DWA. This algorithm is specifically applied to plan the path for a tube-changing robot in a knitting workshop. The process begins with spatial modeling based on the actual parameters of the workshop, followed by the development of a comprehensive, objective function for the robot in line with the relevant constraints. The NRBO algorithm is then integrated with the DWA algorithm to boost its dynamic obstacle avoidance capabilities, while a path correction mechanism is introduced to minimize unnecessary detours. Finally, a comparative experiment is designed to evaluate the algorithm against the GA, PSO, and SSA algorithms. Simulation results demonstrate that in a dynamically complex 3D environment, the NRBO-DWA algorithm outperforms in terms of higher 3D search efficiency, shorter total path length, and faster planning times. [ABSTRACT FROM AUTHOR]

(1) Background: This paper presents the results of a study on developing a hybrid evaluation model for air cargo handling systems, combining fuzzy logic and reliability theory. (2) Methods: The research methodology consisted of two stages: the first used reliability analysis to calculate the performance of individual processes in the cargo handling system. In contrast, the second used fuzzy logic to integrate these metrics and generate an overall system evaluation. Statistical metrics, including mean and standard deviation, were used to construct adaptable membership functions for the fuzzy logic model. (3) Results: 27 test scenarios were built, in which the impact of individual compositions of operator teams (depending on their experience) implementing individual air cargo handling processes on the final assessment of the entire system was examined. Configurations with experienced operators consistently achieved the highest performance evaluations, although the strategic integration of less experienced personnel in noncritical roles was shown to maintain system functionality. (4) Conclusions: The results confirm that the proposed model is a practical decision-support tool for air cargo terminal management. It enables precise process evaluation, supports resource optimization and increases air cargo operations' overall reliability and efficiency. [ABSTRACT FROM AUTHOR]

Quay cranes (QCs) play a vital role in automated container terminals (ACTs), and once a QC malfunctions, it will seriously affect the operation efficiency of ships being loaded and unloaded by the QC. In this study, we investigate an integrated scheduling problem of quay cranes (QCs), yard cranes (YCs), and automated guided vehicles (AGVs) under QC faults, which is aimed at minimizing the loading and unloading time by determining the range of adjacent operational QCs of the faulty QCs and reallocating unfinished container handling tasks of QCs. A mixed integer programming model is formulated to dispatch QCs, YCs, and AGVs in ACTs. To solve the model, an adaptive two-stage NSGA-II algorithm is proposed. Numerical experiments show that the proposed algorithm can significantly reduce the impact of faulty QCs on productivity while maintaining its synchronous loading and unloading efficiency. The sensitivity analysis of ship scale, location, and number of faulty QCs indicates that the number of faulty QCs has a greater influence on the loading and unloading efficiency than their locations, and the impact of faulty QCs on the efficiency of small-scale ships is greater than that of large-scale ships. [ABSTRACT FROM AUTHOR]

To improve the operational efficiency of automated container terminals and the coordination between multiple operations, this article studies the integrated scheduling optimization problem of automated guided vehicles (AGVs) and yard cranes. The impact of charging constraints on AGV task allocation and scheduling is considered. With the goal of minimizing the maximum completion time of all tasks, a mixed integer programming model is proposed. A solution method based on a dynamic programming algorithm is designed, where a heuristic algorithm is used to assign tasks to the yard cranes, and the dynamic programming method is used to assign tasks to the AGVs based on the task assignment results of the yard cranes. Finally, the validity of the model and algorithm is tested by numerical experiments. Furthermore, the influence of the quantity of AGVs on the terminal operational efficiency and the impact of AGV charging strategies on AGV scheduling are analysed. [ABSTRACT FROM AUTHOR]

The current literature mainly uses hub capacity or transport route selection to manage the congestion of emergency multimodal transport and pays less attention to transshipment scheduling. This paper proposes an integrated optimization problem of transport routes and transshipment sequences (ITRTSP) and constructs a hybrid flow shop scheduling model to describe it. Based on this model, a recursive method is proposed to calculate the minimum waiting times that cargoes consume in queues at hubs, given the transport routes and transshipment sequences. Furthermore, a memetic algorithm is designed with route selection as the outer layer and transshipment sequence selection as the inner layer for solving ITRTSP. Compared with existing achievements, the model and algorithms can quantify the dependency between transshipment sequence selection and emergency transport time in multimodal transport network settings. The model and algorithms are applied to solve some real-scale examples and compared with the first-come-first-served (FCFS) rule commonly used in the current literature. The results indicate that the makespan is reduced by up to approximately 4.2%, saving 33.68 h. These findings demonstrate that even with given hub capacities and transport routes, congestion can still be managed and the schedule optimized through transshipment scheduling, further improving emergency transport efficiency. [ABSTRACT FROM AUTHOR]

This study presents an optimized container-stowage plan using reinforcement learning to tackle the complex logistical challenges in maritime shipping. Traditional stowage-planning methods often rely on manual processes that account for factors like container weight, unloading order, and balance, which results in significant time and resource consumption. To address these inefficiencies, we developed a two-phase stowage plan: Phase 1 involves bay selection using a Proximal Policy Optimization (PPO) algorithm, while Phase 2 focuses on row and tier placement. The proposed model was evaluated against traditional methods, demonstrating that the PPO algorithm provides more efficient loading plans with faster convergence compared to Deep Q-Learning (DQN). Additionally, the model successfully minimized rehandling and maintained an even distribution of weight across the vessel, ensuring operational safety and stability. This approach shows great potential for enhancing stowage efficiency and can be applied to real-world shipping scenarios, improving productivity. Future work will aim to incorporate additional factors, such as container size, type, and cargo fragility, to further improve the robustness and adaptability of the stowage-planning system. By integrating these additional considerations, the system will become even more capable of handling the complexities of modern maritime logistics. [ABSTRACT FROM AUTHOR]

Optimizing order-picking systems (OPSs) while considering human factors and integrating key decisions is a major challenge for warehouse managers. This study presents a two-stage framework based on multi-attribute decision-making (MADM) and multi-objective decision-making (MODM) models to integrate decisions on picker selection, order batching, batch assignment, picker routing, and scheduling. In the first stage, the human factors affecting picker selection are considered as the problem's criteria and the available pickers are treated as alternatives. The fuzzy entropy method and fuzzy COmplex PRoportional ASsessment (COPRAS) are used to weight the factors and rank the pickers, respectively. In the second stage, a three-objective mathematical model is formulated to minimize makespan and the operating costs of picking while maximizing the total scores of the selected pickers. The improved augmented epsilon constraint method (AUGMECON2) and the non-dominated sorting genetic algorithm II (NSGA-II) are applied to solve the proposed model. The performance of the two methods is tested on well-known benchmark instances and a real-world case study. The NSGA-II algorithm can generate optimal results using only about 6.58% of the CPU time required by AUGMECON2 to solve the problem. Our computational experiments show that increasing the number of pickers from 2 to 8 and doubling their capacity reduces the makespan by 2.61% and 2.74%, respectively. [ABSTRACT FROM AUTHOR]

The aim of the work presented in this paper was development of a thermodynamically consistent constitutive model for orthotopic metals and determination of its parameters based on standard characterisation methods used in the aerospace industry. The model was derived with additive decomposition of the strain tensor and consisted of an elastic part, derived from Helmholtz free energy, Hill's thermodynamic potential, which controls evolution of plastic deformation, and damage orthotopic potential, which controls evolution of damage in material. Damage effects were incorporated using the continuum damage mechanics approach, with the effective stress and energy equivalence principle. Material characterisation and derivation of model parameters was conducted with standard specimens with a uniform cross-section, although a number of tests with non-uniform cross-sections were also conducted here. The tests were designed to assess the extent of damage in material over a range of plastic deformation values, where displacement was measured locally using digital image correlation. The new model was implemented as a user material subroutine in Abaqus and verified and validated against the experimental results for aerospace-grade aluminium alloy 2024-T3. Verification was conducted in a series of single element tests, designed to separately validate elasticity, plasticity and damage-related parts of the model. Validation at this stage of the development was based on comparison of the numerical results with experimental data obtained in the quasistatic characterisation tests, which illustrated the ability of the modelling approach to predict experimentally observed behaviour. A validated user material subroutine allows for efficient simulation-led design improvements of aluminium components, such as stiffened panels and the other thin-wall structures used in the aerospace industry. [ABSTRACT FROM AUTHOR]

Transporting harvested vegetables in the field or greenhouse is labor-intensive. The utilization of small harvest-aid vehicles can reduce non-productive time for farmers and improve harvest efficiency. This paper models the process of harvesting vegetables in response to non-productive waiting delays caused by the scheduling of harvest-aid vehicles. Taking into consideration harvesting speed, harvest-aid vehicle capacity, and scheduling conflicts, a harvest-aid vehicle scheduling model is constructed to minimize non-production waiting time and coordination costs. Subsequently, to meet the collaborative needs of harvesters, this paper develops a discrete multi-objective Jaya optimization algorithm (DMO-Jaya), which combines an opposition-based learning mechanism and a long-term memory library to obtain scheduling schemes suitable for agricultural environments. Experiments show that the studied model can schedule harvest-aid vehicles without conflicts. Compared to the NSGA-II algorithm and the MMOPSO, the DMO-Jaya algorithm demonstrates a better diversity of solutions, resulting in a shorter non-productive waiting time for harvesters. This research provides a reference model for improving the efficiency of vegetable harvesting and transportation. [ABSTRACT FROM AUTHOR]

Acrylic substrates made from polymethylmethacrylate (PMMA) are anticipated to develop craze and scratches owing to their continual wear. In this study, novel silane modified acrylic resin based organic-inorganic hybrid coating materials have been formulated to provide protection to PMMA substrates against wear. Varied amounts (5, 10 and 15 % wt./wt.) of tetraethoxysilane (TEOS) were added to the acrylic resin solution (containing xylene and 10% ammonia) and the resultant hybrid coating materials were then coated on PMMA substrates through the dip coating method. The hybrid coating materials were transformed into hard coats upon hydrolysis, condensation and cross-linking. The coated samples were characterized to assess the effect of TEOS addition on optical and mechanical properties as well as abrasion resistance of the hybrid coatings. Hardness, stiffness and reduced elastic modulus of the dry coatings obtained through the instrumented indentation technique were observed to increase (up to ca. 56%, 28% and 65% respectively) whereas their viscous nature and plasticity decreased with the addition of TEOS. The hybrid coatings also demonstrated improved wet abrasion resistance which augurs well with their physico-mechanical properties. These observations can be ascribed to the combined contributions of organic-inorganic phase interactions in the coating materials via hydrogen bonding and the formation of cross-linked silica structures as observed through infrared spectroscopy and microscopy. [ABSTRACT FROM AUTHOR]

We consider the scheduling of truck arrivals at an air cargo terminal. By coordinating arrivals of cargo delivery trucks with outbound flight departure schedules, some of the shipments can be transferred directly to the departing flights, while others will be stored at the terminal's storage facility and incur extra handling and storage costs. The objective is to obtain a feasible schedule so as to minimize the total cost of operations. We formulate the problem as a time-indexed integer program and show that, even with limited number of unloading docks at the terminal, the problem is non-trivial (NP-hard in the strong sense). Our solution method includes an exact solution procedure to determine an optimal unloading sequence for the shipments carried by each truck, together with a Lagrangian relaxation-based heuristic for assigning trucks to truck docks and determining truck arrival times. We conducted computational experiments to test the performance of our solution method. Computational results show that our method can generate near-optimal solutions efficiently. Our simulation results indicate that the scheduling approach proposed in this paper has the potential to generate significant cost savings over a first-come, first-served approach currently used at the air cargo terminal that we observed. [ABSTRACT FROM AUTHOR]

Market trends such as globalisation, increasing customer expectations, expensive industrial land and high labour costs cause a need for efficient order picking systems in practice. However, managers often do not implement findings from academic research on order picking planning into practice because researchers hardly account for practical factors (e.g. high-level storage, human factors, pick vehicle properties) or make unrealistic assumptions in their solution algorithms. A state-of-the-art review of the scientific literature on order picking planning (1) identifies and classifies highly influential practical factors, (2) shows the impact of these practical factors on order picking performance, and (3) illustrates how existing order picking planning models should be elaborated to account for practical factors. This study contributes to close the gap between research and practice by guiding future researchers to further increase the practical applicability of their research results. [ABSTRACT FROM AUTHOR]

A customized digital image correlation (DIC) system was implemented to monitor the strain produced in a cold-rolled AL-6XN stainless steel plate, 3.0 mm thick, subjected to quasi-static and cyclic loading tests. A comparison of the DIC strain measurements was made against those provided by conventional extensometers. Furthermore, the DIC system was used to monitor the fatigue crack initiation in low-cycle fatigue tests. The true stress–strain behavior for the AL-6XN material was properly captured by the DIC measurements. For low-cycle fatigue tests (strain control), the strain mapping generated by DIC allowed for identifying zones with higher strain than the nominal strain amplitude applied ( ε a ) since the first stages of the fatigue life (FL). These zones become potential fatigue crack initiation sites. [ABSTRACT FROM AUTHOR]

Damage to parcels reduces customer satisfaction with delivery services and increases return-logistics costs. This can be prevented by detecting and addressing the damage before the parcels reach the customer. Consequently, various studies have been conducted on deep learning techniques related to the detection of parcel damage. This study proposes a deep learning-based damage detection method for various types of parcels. The method is intended to be part of a parcel information-recognition system that identifies the volume and shipping information of parcels, and determines whether they are damaged; this method is intended for use in the actual parcel-transportation process. For this purpose, 1) the study acquired image data in an environment simulating the actual parcel-transportation process, and 2) the training dataset was expanded based on StyleGAN3 with adaptive discriminator augmentation. Additionally, 3) a preliminary distinction was made between the appearance of parcels and their damage status to enhance the performance of the parcel damage detection model and analyze the causes of parcel damage. Finally, using the dataset constructed based on the proposed method, a damage type detection model was trained, and its mean average precision was confirmed. This model can improve customer satisfaction and reduce return costs for parcel delivery companies. [ABSTRACT FROM AUTHOR]

Port development is a critical component in constructing a resilient transportation infrastructure. The burgeoning integration of automated guided vehicles (AGVs) within container terminals, in conjunction with the orchestrated scheduling of unmanned container trucks (UCTs), is essential for the sustainable expansion of port operations in the future. This study examined the influence of AGVs in automated container terminals and the synergistic scheduling of UCTs on port operations. Comparative experiments were meticulously designed to evaluate the feasibility of integrated scheduling schemes. Through the development of optimization models that consider conflict-free paths for both AGVs and UCTs, as well as strategies for conflict resolution, a thorough analysis was performed. Advanced genetic algorithms were engineered to address task-dispatching models. In contrast, the A* optimization search algorithm was adapted to devise conflict-free and conflict-resolution paths for the two vehicle types. A range of scaled scenarios was utilized to assess the impact of AGVs and UCTs on the joint-scheduling process across various configuration ratios. The effectiveness of the strategies was appraised by comparing the resultant path outcomes. Additionally, comparative algorithmic experiments were executed to substantiate the adaptability, efficacy, and computational efficiency of the algorithms in relation to the models. The experimental results highlight the viability of tackling the joint-scheduling challenge presented by AGVs and UCTs in automated container terminals. When juxtaposed with alternative scheduling paradigms that operate independently, this integrated approach exhibits superior performance in optimizing the total operational costs. Consequently, it provides significant insights into enhancing port scheduling practices. [ABSTRACT FROM AUTHOR]

In this work, a numerical study is conducted to investigate the improvement of in-plane behavior of weak brick masonry walls through assimilation of partially confining horizontal and vertical reinforced concrete (RC) bands. The bands are considered to be assimilated with the existing walls by cutting grooves over the partial thickness of the wall in a easy-to-construct manner. For numerical modeling of the wall width and without partially confining elements, a three-dimensional (3D) macro-modeling approach is utilized as it is computationally efficient compared to other modeling approaches while representing the global behavior reasonably well. The components of macro-models are discretely modeled. The concrete damage plasticity (CDP) model is considered to describe the non-linear behavior of the concrete and masonry for crushing and cracking failures. Steel reinforcements are considered as bilinear with hardening and modeled with perfect adhesion with the surrounding concrete using embedded constraints. Experimental results obtained from the full-scale tests at the Structural Engineering laboratory of IIT Kanpur have been utilized to validate the numerical model. The responses obtained from the numerical model of both with and without RC bands demonstrate that the models reasonably capture the experimental behavior such as initial stiffness, peak loads and post-peak behavior. The initial peak load from the numerical model of without and with RC bands was found to be 3.2% and 6.9% lower than the experimental value, respectively. Although post-yield trends of numerical and experimental results show similar behavior for walls without and with RC bands, the numerical model underestimates the post-yield strength for the wall without RC bands. This deviation can be attributed to the masonry dominated post-peak behavior coupled with modeling assumptions and values of model parameters used for the numerical analysis. Finally, to understand the influence of various parameters on lateral strength, a parametric study has been conducted. From the parametric study, it has been found that the compressive strength of masonry and band aspect ratio are the two most important parameters governing the strength of the wall. Finally, it is noted that a wall with band aspect ratio close to unity provides superior ductile behavior. [ABSTRACT FROM AUTHOR]

Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model's potential to transform open-pit mining operations by using intelligent planning. [ABSTRACT FROM AUTHOR]

Machine learning technologies are being integrated into robotic systems faster to enhance their efficacy and adaptability in dynamic environments. The primary goal of this research was to propose a method to develop an Autonomous Mobile Robot (AMR) that integrates Simultaneous Localization and Mapping (SLAM), odometry, and artificial vision based on deep learning (DL). All are executed on a high-performance Jetson Nano embedded system, specifically emphasizing SLAM-based obstacle avoidance and path planning using the Adaptive Monte Carlo Localization (AMCL) algorithm. Two Convolutional Neural Networks (CNNs) were selected due to their proven effectiveness in image and pattern recognition tasks. The ResNet18 and YOLOv3 algorithms facilitate scene perception, enabling the robot to interpret its environment effectively. Both algorithms were implemented for real-time object detection, identifying and classifying objects within the robot's environment. These algorithms were selected to evaluate their performance metrics, which are critical for real-time applications. A comparative analysis of the proposed DL models focused on enhancing vision systems for autonomous mobile robots. Several simulations and real-world trials were conducted to evaluate the performance and adaptability of these models in navigating complex environments. The proposed vision system with CNN ResNet18 achieved an average accuracy of 98.5%, a precision of 96.91%, a recall of 97%, and an F1-score of 98.5%. However, the YOLOv3 model achieved an average accuracy of 96%, a precision of 96.2%, a recall of 96%, and an F1-score of 95.99%. These results underscore the effectiveness of the proposed intelligent algorithms, robust embedded hardware, and sensors in robotic applications. This study proves that advanced DL algorithms work well in robots and could be used in many fields, such as transportation and assembly. As a consequence of the findings, intelligent systems could be implemented more widely in the operation and development of AMRs. [ABSTRACT FROM AUTHOR]

In this paper, we consider the pickup and delivery traveling salesman problem with multiple stacks in which a single vehicle must serve a set of customer requests defined by a pair of pickup and delivery destinations of an item. The vehicle contains a fixed number of stacks, where each item is loaded at a pickup location and unloaded at the corresponding delivery location. Each stack has finite capacity, and its loading and unloading sequence must follow the last-in-first-out (LIFO) policy, that is, for each stack, just the last item loaded can be unloaded at its corresponding delivery location. We propose a new integer programming formulation for this problem with a polyhedral representation described by exponentially many inequalities and a branch-and-cut algorithm for solving the proposed formulation. Computational results show that our approach is competitive with the best algorithm in the literature. Also, three new certificates of optimality are provided and several optimality gaps are reduced. [ABSTRACT FROM AUTHOR]

Distributors are faced with loading constraints in their route planning, e.g.,multi-dimensional packing constraints, unloading sequence constraints, stability constraints and axle weight limits. Ignoring these constraints impairs planning and induces last-minute changes resulting in additional costs. Developing vehicle routing models incorporating loading constraints is critical to more efficient route planning. The last couple of years has seen a huge increase of contributions to this field of research with almost 60 % of these being published after 2009. Our contribution is twofold. First, we overview the recent developments in the literature on all vehicle types in which loading constraints play a key role (trucks, airplanes, ships, and automated guided vehicles), using a state-of-the-art classification scheme to identify the loading constraints considered in each article. Second, we identify research gaps and opportunities for future research. [ABSTRACT FROM AUTHOR]

Background: Microgravity, a condition experienced in a spatial environment, poses unique challenges to the skeletal system, particularly in juvenile organisms. This study aimed to investigate alterations in bone biomechanics of juvenile mice due to unloading – that simulates microgravity in the laboratory—and the effects of a bone-loading intervention. We compared bone compositional and mechanical properties between 21-six-week-old C57Bl/6 from a control group (wild type) and a group that underwent a tail-suspension unloading protocol to mimic microgravity (MG). The second group (MG) experienced additional in vivo loading protocol (MG + LDG) on the right hind leg, where dynamic compressive loading was applied to the right knee using a custom-built loading device. Results: Our results show that after two weeks, we successfully induced bone alterations by (i) decreasing the energy dissipated before fracture and (ii) decreasing the yield and maximum stress. In addition, we showed that Mineral to matrix component [ν1PO4/Amide I], Carbonate to Amide [CO3/Amide I], and Crystallinity [1/FWHM(ν1PO4)] are strongly linked in physiological bone but not in microgravity even after loading intervention. While Crystallinity is very sensitive to bone deformation (strain) alterations coming from simulated microgravity, we show that Carbonate to Amide [CO3/Amide I] – a common marker of turnover rate/remodeling activity—is a specific predictor of bone deformation for bone after simulated microgravity. Our results also invalidate the current parameters of the loading intervention to prevent bone alterations entirely in juvenile mice. Conclusions: Our study successfully induced bone alterations in juvenile mice by using an unloading protocol to simulate microgravity, and we provided a new Raman Spectroscopy (RS) dataset of juvenile mice that contributes to the prediction of cortical bone mechanical properties, where the degree of interrelationship for RS data for physiological bone is improved compared to the most recent evidence. [ABSTRACT FROM AUTHOR]

Near-surface axial tensile residual stresses (from manufacturing) are reportedly detrimental to the yield strength of cold-drawn wires. Therefore, a reliable evaluation of their magnitude is necessary. The size and geometry of electrical wires can pose challenges for experimental measurement of those residual stresses. For that reason, the finite element analysis can prove useful. However, great care must be taken with the right choice of strain hardening law for a sound assessment of residual stresses. Given the complex loading condition during cold drawing, cyclic loading arises through the wire cross section even in single-pass drawing. As a result, it is of crucial importance to account for associated backstresses. The current study makes a comparison between two different hardening laws' prediction of axial residual stress profiles in numerically cold-drawn Cu–Al composite wires of various Al volume fractions. The impact of die geometry on this prediction was also examined for a 25%Al-wire. To that end, a combined isotropic-kinematic law and a pure isotropic constitutive equation were considered. The results imply a possible overestimation of residual stresses by the pure isotropic model at relatively low Al volume fractions. The difference between the maximum magnitudes of tensile or compressive residual stresses (predicted by the two models) could be as large as about 100 MPa (larger than the yield strength of the starting materials). Furthermore, the tooling geometry minimally affects the prediction of the hardening models. In conclusion, backstresses are not to be overlooked for accurate estimations of drawing residual stresses at low Al volume fractions. [ABSTRACT FROM AUTHOR]

Context. Transport of cattle can be stressful and may lead to increased body temperature. It is necessary to quantify the effect of transport on body temperature so that informed management decisions can be made. Aims. This study aimed to determine the effects of a 5.5 h, 430 km road transport journey on body temperature (TB) of feedlot steers. Methods. Body temperature was obtained at 30 min intervals. All cattle were weighed and randomly allocated to a truck pen prior to transport. Cattle were transported on a single B-double truck, with three upper-deck and three lower-deck compartments. At 0630 hours, cattle were walked from their pens (25 m), weighed and loaded onto the truck. Loading was completed by 1030 hours. Key results. During the weighing and loading process prior to transport, mean TB increased from 39.37 ± 0.11°C to 40.21 ± 0.11°C. Immediately following loading, mean TB increased. The TB of cattle on the upper deck was 40.96 ± 0.08°C and on the lower deck 40.89 ± 0.08°C (P = 0.6299). During the first 3 h of the journey, the TB of lower-deck cattle decreased by 1.14°C (P < 0.01), compared with a 0.83°C reduction in cattle on the upper deck. Over the duration of the journey, which took 1 h longer than expected, the mean TB of the cattle on the upper deck (40.47 ± 0.11°C) was greater (P < 0.0001) than that on the lower deck (40.04 ± 0.12°C). One hour after unloading at the abattoir, pooled TB was 40.26 ± 0.12°C. Minimum TB (38.87 ± 0.04°C) occurred at 10.5 h after unloading. Conclusions. The results from this study highlight that increases in TB were more associated with cattle handling and loading events, rather than transport, under these environmental conditions. Understanding the magnitude of this increase will help managers decide on pre- and post-transport management of cattle. Implications. Cattle handling and loading for transport may lead to an increase in TB, which can remain elevated for a number of hours. However, it is unclear what the impact of hotter climatic conditions would have on trailer microclimate and, as such, TB regulation during road transport. [ABSTRACT FROM AUTHOR]

This paper studies an interval data min–max regret (IDMR) version of the packing-delivery problem, in which a 0-1 knapsack problem is for parcel packing and a capacitated travelling salesman problem is for parcel delivery. The parcel profits for the courier and the tour costs are uncertain and they can take any value from a specific interval with lower and upper bound values. The problem is how to select and deliver a subset of parcels to minimise the maximum regret of net profit which is the difference between the total profits of the selected parcels and the total delivery costs, to deal with the trade-off of the solution robustness and performance. To tackle the problem effectively, we first prove the worst-case scenario of a solution to the problem, based on which, a mixed integer linear programming is formulated. A Benders-like decomposition algorithm is then developed to solve small-scale problems to optimality within the manageable computation time. For medium- and large-scale problems, a simulated-annealing-based heuristic method with a local search procedure is designed. Extensive computational experiments show the efficiency and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

The Oliver and Pharr method for evaluating nanoindentation load–displacement data is based on the measurement of the contact stiffness, which is usually determined at the very beginning of the unloading sequence, or, using dynamic nanoindentation, continuously during the whole loading segment. A new experimental method has been developed to continuously monitor the contact stiffness throughout the unloading sequence. It provides supplementary information about the shape and area of the residual impression, as well as a direct measurement of the shape of the effective indenter previously introduced by Pharr and Bolshakov. The new method was applied to indentations on fused silica, sapphire, nanocrystalline nickel, and ultrafine-grained aluminum. Lastly, the new procedure was adapted to directly measure the epsilon factor used in the Oliver and Pharr method. A value of 0.76 was found from indentation into fused silica, in close agreement with literature values. [ABSTRACT FROM PUBLISHER]

Abstract: In this dislocation dynamics study of a single crystal under a loading–unloading sequence, the role of dislocation reaction is presented. The formation of prismatic dislocation loops is observed during the loading–unloading sequence, when allowing for cross-slip. The cross-slip probability strongly affects the microstructure rearrangement. [Copyright &y& Elsevier]

Elastic wave velocities of compressional and shear waves propagating through sedimentary rocks are often coupled with information of bulk density to derive the rock stiffness. Acquiring the transit time of compressional and shear waves often involves manual picking of wave arrival times from wave trains recorded in the laboratory or by well‐logging tools. Picking the compressional wave arrival time is commonly accepted as straightforward. Oppositely, detecting the shear wave arrival and picking its arrival time is often troublesome because the transmitted shear wave partly converts to compressional waves and back to a secondary shear wave, concealing the transmitted shear wave arrival in the wave train. In laboratory settings, we illustrate the difficulty of shear wave detection in wave trains recorded on highly porous chalk plug samples from the Danish North Sea Basin. Wave trains were recorded on plugs dry, Tap‐water or Isopar‐L saturated during uniaxial strain compaction. The recorded shear wave trains showed two distinct features, which could be interpreted as the transmitted shear wave first arrival; we denoted them as early and late arrivals. However, as only one feature can mark the arrival of the transmitted shear wave, we propose a semi‐empirical disclosure strategy combining a graphical representation of stacked wave trains with rock physical modelling. By stacking recorded wave trains in a graphical strain–time–amplitude domain, we demonstrate that an early shear wave feature marks a converted shear to compressional to shear wave and not the transmitted shear wave. We used physical modelling to identify early shear wave features and illustrate the consequences of adopting a falsely interpreted shear wave on stiffness properties. [ABSTRACT FROM AUTHOR]

The frictional properties of faults control the initiation and propagation of earthquakes and the associated hazards. Although the ambient temperature and instantaneous slip velocity controls on friction in isobaric conditions are increasingly well understood, the role of normal stress on steady‐state and transient frictional behaviors remains elusive. The friction coefficient of rocks exhibits a strong dependence on normal stress at typical crustal depths. Furthermore, rapid changes in normal stress cause a direct effect on friction followed by an evolutionary response. Here, we derive a constitutive friction law that consistently explains the yield strength of rocks from atmospheric pressure to gigapascals while capturing the transient behavior following perturbations in normal stress. The model explains the frictional strength of a variety of sedimentary, metamorphic, and igneous rocks and the slip‐dependent response upon normal stress steps of Westerly granite bare contact and synthetic gouges made of quartz and a mixture of quartz and smectite. The nonlinear normal stress dependence of the frictional resistance may originate from the distribution of asperities that control the real area of contact. The direct and transient effects may be important for induced seismicity by hydraulic fracturing or for naturally occurring normal stress perturbations within fault zones in the brittle crust. Plain Language Summary: A long‐term research goal in earthquake science is the development of friction laws describing how rocks break under stress and heal over quiescent periods to enable the seismic cycle. The constitutive behavior of rocks remains elusive because of the wide range of hydrothermal, barometric, and lithological conditions found in the brittle crust. A long‐standing enigma in rock mechanics is the nonlinear effect of normal stress on frictional strength across the confining pressures relevant to seismogenic faults. Equally puzzling are the sudden and delayed variations of friction upon rapid changes in normal stress. In this study, we explain the connection between these seemingly unrelated observations. The transient evolution of friction under perturbations of normal stress is due to the competition between normal‐stress‐dependent healing of the frictional interface, which strengthens the fault, and the direct effect of normal stress, which reduces the frictional strength. If the two effects do not compensate exactly, a dependence of steady‐state friction with normal stress ensues. We propose a constitutive model that explains quantitatively the frictional resistance of various rocks types and the mechanical data of bare contact and gouge friction during sliding at different normal stress for Westerly granite, pure quartz, and a mixture of quartz and smectite. The study helps build increasingly realistic representations of fault mechanics during seismic cycles. Key Points: For a wide range of lithology, fault strength and fault friction are nonlinear functions of normal stressNormal stress change causes direct and evolutionary effects on the effective friction coefficient, possibly of different amplitudesThe direct and transient effects upon normal stress change are controlled by the area of contact and slip‐dependent healing [ABSTRACT FROM AUTHOR]