Closed-loop Chain Research Articles

Error Sensitivity Analysis of a 1T2R Kinematically Redundant Parallel Mechanism With Closed-Loop Chain

Abstract In this paper, a generalized method for error modeling of the spatial 1T2R three degrees-of-freedom kinematically redundant parallel mechanism with a closed-loop chain is proposed, which is based on the matrix differential method. First, the detailed process of generalized error modeling and error analysis are described. Based on the proposed method, the error model of the spatial 3PRR(RR)S-P (P—prismatic joint, R—revolute joint, S—spherical joint, and the underline indicates that the joint is the actuator) kinematically redundant parallel mechanism is established as an example, and the correctness of the error model is verified by combining forward with inverse kinematics. Then, the patterns affecting the output error of the moving platform are discussed for the case where the mechanism contains only static error or dynamic error, respectively. In addition, the error sensitivity indices are defined to evaluate the error sensitivity of the moving platform to different redundant parameters L4 under a certain pose. Finally, in order to identify the key error terms, the sensitivity of the output error of the mechanism to a single error term is analyzed. The results show that the error sensitivity of the spatial kinematically redundant parallel mechanism can be effectively reduced by adjusting the kinematically redundant parameters, so that the mechanism can maintain a low error sensitivity in a certain pose.

More different than alike: cross-sector volatility spillovers in Chinese stock sectors during COVID-19 pandemic

ABSTRACT The asymmetric spillovers and dynamic connectedness among sectors in Chinese stock market have not been fully studied, especially the impact of catastrophic events related to the COVID-19 pandemic on the linkages. In this paper, an asymmetric VAR-BEKK (DCC) – GARCH model is employed to measure the volatility spillovers and dynamic correlations among Chinese stock sectors before and during the COVID-19 pandemic. The empirical results indicate that volatility spillovers among sectors are significant, with evident differences before and during COVID-19. To be specific, the primary spillover transmitting sector has shifted from telecom business for the pre-pandemic period to the financial real estate sector after the outbreak. However, the role of the raw materials sector as the spillover receiver has not changed. Notably, the medical health sector forms closed-loop chains of transmission with the most other sectors during the COVID-19 period. In addition, asymmetric volatility spillovers and dynamic correlations among stock sectors are also significantly examined. The findings contribute to investors and decision makers in adjusting trading strategies and monitoring market risks.

Prediction of Aging Performance of Particle-Filled Polymer Composites Based on RVE Model.

In this study, the aging performance of particle-filled polymer composites (PFPCs) under thermo-oxidative conditions was investigated on multiple scales. High-temperature-accelerated tests were conducted to analyze the effects of aging time and temperature. A representative volume element (RVE) model was established for the PFPCs using a random particle-filling algorithm. A predictive model for the crosslink density was conducted based on the closed-loop chain reaction of polymer oxidation. According to the theory of polymer physics, the relation between the crosslink density and matrix modulus was determined. The particle/matrix interface in the RVE model was represented by the cohesive zone model (CZM). The parameters of the CZM were determined by the inversion techniques. Then, a comprehensive multiscale RVE model was constructed, which was applied to predict the modulus and dewetting strain of the aged PFPCs. The predicted results show good agreement with the test results, which verifies the reliability of our model.

Fostering Fashion Ecosystems: A Quadruple Helix-Based Model for European Sustainable Innovation

Industrial sectors’ innovative and sustainable development relies not only on solid government, society, academia, and industry but also on how they interact to set and implement strategic goals. In the fashion industry context, the new sociocultural scenario is increasingly driven by pressures from stakeholders to limit the impacts of industrial practices and to move toward new open ecosystems to create and maintain sustainable innovation. This article explores how such innovation can be enabled by design-driven actions in the context of the quadruple helix. Such a model aims to revitalize the areas of technological innovation and gradually advance the construction of the infrastructure needed for sustainable fashion growth, combining and integrating different knowledge. An initial literature review, complemented by case studies analysis, identifies the European fashion industry dynamics of innovation and the roles of industry, government, university, and society. In particular, the government is transforming from a mere controller to a facilitator of innovation synergies. Society relies on citizens revising their consumption habits by shifting toward a performative economy. Industry understands the need for collaboration and adopts new closed-loop supply chains to create and maintain its sustainable development. Universities enable new open system flows to make innovations concerning knowledge, technologies, and systems thrive, from technology transfer to knowledge co-creation. Based on the analysis, we propose a conceptual framework to understand the micro- and macro-dynamics of open innovation with a quadruple helix model to implement sustainability practices in the fashion sector through design-driven actions—reuse, repair, recycle, and refashion—that aim to eliminate the concept of waste to support local ecosystems toward establishing a closed-loop chain.

Multi-Scale Model for the Aging Performance of Particle-Filled Polymer Composites.

In this study, we developed a novel multi-scale model to predict the aging performance of particle-filled polymer composites (PFPCs) under thermo-oxidative aging conditions. To investigate the aging behavior, high-temperature accelerated aging tests were conducted in combination with macroscopic and microscopic characterization. At the microscopic level, the crosslinking density of the polymer matrix is calculated using the closed-loop chain reaction of polymer oxidation. In addition, the theory of polymer physics was used to determine the relationship between crosslinking density and elastic modulus. Relationships between elastic modulus and dewetting strain were analyzed at the macroscopic level. Based on the observations and analyses, a multi-scale model was developed to predict the aging performance of PFPCs. The predicted results show good agreement with the test results, which verifies the reliability of the model.

Conceptual principles for formation of the supply chains' decarbonization strategies

The article examines the conceptual foundations of the formation of a strategy for the decarbonization of supply chains, the identification of strategic solutions for reducing greenhouse gas emissions, and the management of green chains from the point of view of ecological and economic efficiency. A structural and logical diagram of the formation of the strategy of decarbonization of supply chains has been built. Seven key business processes in supply chains/networks have been identified that significantly affect the volume of greenhouse gas emissions: ecological design, environmental procurement, energy- and resource-saving production, green transportation, ecological storage, smart eco-consumption, recycling and disposal. It was established that in closed-loop chains, managerial environmental solutions should be aimed at: preservation or restoration of products to extend their life cycle, which includes diagnostics and repair; reuse of products for the same or new purposes in their original form or with some changes; restorative repair of products or individual components; processing of waste and end-of-life products, or recycling (any recovery operations, with the help of which waste and old products are processed into materials, resources, substances for the production of other products or for other purposes).

Presenting a Fuzzy Multiobjective Mathematical Model of the Reverse Logistics Supply Chain Network in the Automotive Industry to Reduce Time and Energy

The current research aims to design a fuzzy multiobjective model of the reverse logistics supply chain network in the automotive industry, taking into account the energy and time reduction approach. The automobile industry is one of the industries with a high demand worldwide. To continue the competition, the manufacturers of the leading car equipment should strive for better product quality by continuously improving their production processes, directing the production of greenhouse gases with low carbon levels, and increasing sustainability. In this regard, reverse supply chain networks and closed-loop chains have unique features that are very useful in the industry under review. The goal is to transform this model into a supply chain of a secure link in the automotive industry. Deterministic methods, genetic algorithm, particle swarm algorithm, and several scenarios with different aspects have been used to solve the model. The results show that the effectiveness of the three ways in terms of solution time is higher in the deterministic solution method. Proper use of the proposed process can help managers effectively manage the flow of recycled products concerning environmental considerations, and this process provides a sustainable competitive advantage for companies.

Anomalous scaling at nonthermal fixed points of the sine-Gordon model

We extend the theory of non-thermal fixed points to the case of anomalously slow universal scaling dynamics according to the sine-Gordon model. This entails the derivation of a kinetic equation for the momentum occupancy of the scalar field from a non-perturbative two-particle irreducible effective action, which re-sums a series of closed loop chains akin to a large-$N$ expansion at next-to-leading order. The resulting kinetic equation is analyzed for possible scaling solutions in space and time that are characterized by a set of universal scaling exponents and encode self-similar transport to low momenta. Assuming the momentum occupancy distribution to exhibit a scaling form we can determine the exponents by identifying the dominating contributions to the scattering integral and power counting. If the field exhibits strong variations across many wells of the cosine potential, the scattering integral is dominated by the scattering of many quasiparticles such that the momentum of each single participating mode is only weakly constrained. Remarkably, in this case, in contrast to wave turbulent cascades, which correspond to local transport in momentum space, our results suggest that kinetic scattering here is dominated by rather non-local processes corresponding to a spatial containment in position space. The corresponding universal correlation functions in momentum and position space corroborate this conclusion. Numerical simulations performed in accompanying work yield scaling properties close to the ones predicted here.

Optimizing the Interaction Between Two Closed-Loop Supply Chains Based on Inverse Logistics Using the Game Theory Method

Abstract Over the past few years, attention to environmental problems, legal necessities, and economic advantages emerging from reproduction activities has attracted attention to reverse logistics activities in the form of a closed-loop supply chain, whether in industry or scientific research. The current study aims to model competitiveness and comparison between two closed-loop three-level supply chains, each of which includes a manufacturer, a retailer, and a third party to collect the products used by the customer, taking into account the concepts of game theory and the existence of aggregates. Moreover, a separate supplier for each chain is considered. In the forward supply chain, the manufacturer produces new products using new components or re-used products that have been collected from the consumer, then sells these products mainly to the retailer, and the retailer sells them. In the reverse chain, the collector provides the used products to the manufacturer after collection. The study utilized the definitions and concepts of game theory to model this closed loop chain as a Stackelberg game to obtain the optimal value of wholesale and retail price and the optimal value of the product return coefficient for the collector. Finally, the models based on some numerical examples are solved. Given the results, the remanufacturing costs have a significant role in making more profits for all members in such chains, and competitive chains should attempt to remanufacture the products at lower costs.

Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study.

BackgroundBalance rehabilitation programs represent the most common treatments for balance disorders. Nonetheless, lack of resources and lack of highly expert physiotherapists are barriers for patients to undergo individualized rehabilitation sessions. Therefore, balance rehabilitation programs are often transferred to the home environment, with a considerable risk of the patient misperforming the exercises or failing to follow the program at all. Holobalance is a persuasive coaching system with the capacity to offer full-scale rehabilitation services at home. Holobalance involves several modules, from rehabilitation program management to augmented reality coach presentation.ObjectiveThe aim of this study was to design, implement, test, and evaluate a scoring model for the accurate assessment of balance rehabilitation exercises, based on data-driven techniques.MethodsThe data-driven scoring module is based on an extensive data set (approximately 1300 rehabilitation exercise sessions) collected during the Holobalance pilot study. It can be used as a training and testing data set for training machine learning (ML) models, which can infer the scoring components of all physical rehabilitation exercises. In that direction, for creating the data set, 2 independent experts monitored (in the clinic) 19 patients performing 1313 balance rehabilitation exercises and scored their performance based on a predefined scoring rubric. On the collected data, preprocessing, data cleansing, and normalization techniques were applied before deploying feature selection techniques. Finally, a wide set of ML algorithms, like random forests and neural networks, were used to identify the most suitable model for each scoring component.ResultsThe results of the trained model improved the performance of the scoring module in terms of more accurate assessment of a performed exercise, when compared with a rule-based scoring model deployed at an early phase of the system (k-statistic value of 15.9% for sitting exercises, 20.8% for standing exercises, and 26.8% for walking exercises). Finally, the resulting performance of the model resembled the threshold of the interobserver variability, enabling trustworthy usage of the scoring module in the closed-loop chain of the Holobalance coaching system.ConclusionsThe proposed set of ML models can effectively score the balance rehabilitation exercises of the Holobalance system. The models had similar accuracy in terms of Cohen kappa analysis, with interobserver variability, enabling the scoring module to infer the score of an exercise based on the collected signals from sensing devices. More specifically, for sitting exercises, the scoring model had high classification accuracy, ranging from 0.86 to 0.90. Similarly, for standing exercises, the classification accuracy ranged from 0.85 to 0.92, while for walking exercises, it ranged from 0.81 to 0.90.Trial RegistrationClinicalTrials.gov NCT04053829; https://clinicaltrials.gov/ct2/show/NCT04053829

Design and Analysis of Intelligent Agricultural Monitoring System Based on Biological Intelligence Optimization Algorithm

The traditional optimization method has insufficient intelligence, slow operation speed, and some problems in the calculation of optimal parameters when facing the relationship between too large sample size and complex thread. The biological intelligence optimization algorithm is based on the genetic and evolutionary mechanism of the genetic system. The smart agricultural system is the application of new IOT technology in the field of smart agriculture, mainly including real-time monitoring, wireless monitoring, and remote image and analysis functions. Through this topic, it is concluded that (1) when the parameter is set to μ = 0.02, β = 0.99, the deviation of the optimal value = 1.74, the deviation of the average value = 3.86, the standard deviation of the experimental value = 3.81, the performance evaluation = 2.68, and the maximum number of peaks = 4. It can give full play to the advantages of various algorithms and learn from each other's strengths. (2) The sNIOA algorithm is the best. Compared with the NIOA algorithm, the accuracy of N is increased by 50% and the accuracy of L = 8 is increased by 20%. Compared with the NGA algorithm, the error of I is reduced by 23.5% and the offset of M is reduced. NPSO algorithm pm performance is improved by 20%, and pmk peak value is reduced by 20%. The domestic research on smart agriculture has experienced explosive growth, and the research has been carried out from the concept of smart agriculture, related technologies, constraints, industrial chain, etc., to provide theoretical guidance for the development of smart agriculture. The worst algorithm parameter is the NIOA model whose offset increases little, the performance decreases by 20%, and the peak value becomes worse. (3) The smart agriculture project uses the latest Internet of Things and cloud computing technology, and based on the analysis of big data and artificial intelligence technology, a new service form is proposed, that is, a cloud, network, and platform composite service system to establish a regional closed-loop ecological chain integrating agricultural production, processing, and marketing. (4) In the biological genetic algorithm model, the recall rate of Cp is low, the ROC curve fluctuates greatly, the specificity AEa is poor, and the sensitivity is not high. Using the integrated technology integrating GIS technology, RS technology, spatial statistics, mathematical models, and other methods, based on the differences of various temporal and spatial scales and their monitoring methods, combined with regression model and spatial sampling method, quantitative analysis was performed, and its influencing factors were analyzed. The comparison shows that the optimal F1 score of biological intelligence optimization parameters is up to 23% higher, the accuracy rate Ao is increased by 20%, and the accuracy rate is high.

A numerical method for suspensions of articulated bodies in viscous flows

An articulated body is defined as a finite number of rigid bodies connected by a set of arbitrary constraints that limit the relative motion between pairs of bodies. Such a general definition encompasses a wide variety of situations in the microscopic world, from bacteria to synthetic micro-swimmers, but it is also encountered when discretizing inextensible bodies, such as filaments or membranes. In this work we consider hybrid articulated bodies, i.e. constituted of both linear chains, such as filaments, and closed-loop chains, such as membranes. Simulating suspensions of such articulated bodies requires to solve the hydrodynamic interactions between large collections of objects of arbitrary shape while satisfying the multiple constraints that connect them. Two main challenges arise in this task: limiting the cost of the hydrodynamic solves, and enforcing the constraints within machine precision at each time-step. To address these challenges we propose a formalism that combines the body mobility problem in Stokes flow with a velocity formulation of the constraints, resulting in a mixed mobility-resistance problem. While resistance problems are known to scale poorly with the particle number, our preconditioned iterative solver is not sensitive to the system size, therefore allowing to study large suspensions with quasilinear computational cost. Additionally, constraint violations, e.g. due to discrete time-integration errors, are prevented by correcting the particles' positions and orientations at the end of each time-step. Our correction procedure, based on a nonlinear minimisation algorithm, has negligible computational cost and preserves the accuracy of the time-integration scheme. The versatility of our method allows to study a plethora of articulated systems within a unified framework. We showcase its robustness and scalability by exploring the locomotion modes of a model microswimmer inspired by the diatom colony Bacillaria Paxillifer, and by simulating large suspensions of bacteria interacting near a no-slip boundary. Finally, we provide a Python implementation of our framework in a collaborative publicly available code, where the user can prescribe a set of constraints through a single input file to study a wide spectrum of applications involving suspensions of articulated bodies.

Unfolding research themes for industrial symbiosis and underlying theories

AbstractThis paper aims to analyze the research themes that are addressed in studies on industrial symbiosis (IS), from the perspective of theories. The paper method is a longitudinal analysis of retrospective nature from 1998 to 2021. This approach allowed to detects the main drivers and associated themes that structured researches on IS in the period. In general, Industrial Ecology Theory, Network Theory, Systems Theory and Organizational Theory were present in a considerable part of research themes on IS. It was observed that the IS research themes moved over the period analyzed to nine areas of study: (1) Waste as a resource, (2) development industrial symbiosis network, (3) circular economy and industrial symbiosis, (4) industrial co‐localization, (5) energy innovations, (6) closed loop chains, (7) IS's social aspects, (8) regional‐level metabolism, and (9) waste knowledge. In summary, the contributions of this paper are the thematic proposition of IS from the perspective of theories, pointing out the key‐aspects; and presentation of a research themes' diagram towards the IS buildup.

Mobility of overconstrained parallel mechanisms with reconfigurable end-effectors

Reconfigurable parallel mechanisms have legs or end-effectors with additional degrees of freedom or with the ability to change their mobility. This allows them to reconfigure into a variety of conventional parallel mechanisms. One type of reconfigurable parallel mechanism can be obtained by replacing the end-effector with a closed-loop linkage. The parts of this linkage that are connected to the legs may be considered as the end-effectors, having their own mobility relative to the base and a coupled mobility with each other. Classical methods for mobility analysis cannot be directly applied to this type of mechanism. This article presents a general method to calculate and represent the coupled mobility of the multiple end-effectors using nullspace operations on a matrix of mobility. The nullspace approach provides an efficient way to calculate the mobility in a closed-loop chain while the matrix of mobility allows for calculating the multiple end-effectors mobility interaction. The general method can be performed analytically to obtain insights on the mechanism in any configuration, or algorithmically to obtain numerical values of the mobility in a particular configuration. Two illustrative examples showcasing the method are presented.

Factors of uneven progress of the European Union countries towards a circular economy

The increased final consumption exacerbates the problem of the scarcity of natural resources and leads to environmental pollution. The concept of circular economy, which implies the formation of closed-loop chains of production and consumption with maximum regeneration and recycling of materials, is considered as an alternative to the firmly established “linear economy” (take-make-dispose). As a part of sustainable development strategy, the European Union adopted a general policy on the transition to a circular economy. However, for objective reasons, such transition is quite uneven at the level of member countries, which adversely affects the total progress. Therefore, the need arises to assess the positions of individual countries and identify major reasons for the uneven transition to support the countries that are lagging.The goal of the study is to identify the factors of uneven progress of the EU countries towards a circular economy. For that reason, a set of empirical data (20 indicators) has been compiled; cluster, classification, and parametric analyses have been conducted. As a result, three clusters of the EU countries have been obtained and six indicators, included into combinations that make all clusters different, have been identified. These indicators can be interpreted as the key factors contributing to the uneven progress of the EU countries towards a circular economy. The difference in harmonic means by clusters allowed quantitatively estimating a “circular gap”. It is of practical value for the EU policy aimed at bridging the gaps between member countries during the transition to a circular economy.

Development and Experimental Validation of an Adaptive, Piston-Damage-Based Combustion Control System for SI Engines: Part 2—Implementation of Adaptive Strategies

This work focuses on the implementation of innovative adaptive strategies and a closed-loop chain in a piston-damage-based combustion controller. In the previous paper (Part 1), implemented models and the open loop algorithm are described and validated by reproducing some vehicle maneuvers at the engine test cell. Such controller is further improved by implementing self-learning algorithms based on the analytical formulations of knock and the combustion model, to update the fuel Research Octane Number (RON) and the relationship between the combustion phase and the spark timing in real-time. These strategies are based on the availability of an on-board indicating system for the estimation of both the knock intensity and the combustion phase index. The equations used to develop the adaptive strategies are described in detail. A closed-loop chain is then added, and the complete controller is finally implemented in a Rapid Control Prototyping (RCP) device. The controller is validated with specific tests defined to verify the robustness and the accuracy of the adaptive strategies. Results of the online validation process are presented in the last part of the paper and the accuracy of the complete controller is finally demonstrated. Indeed, error between the cyclic and the target combustion phase index is within the range ±0.5 Crank Angle degrees (°CA), while the error between the measured and the calculated maximum in-cylinder pressure is included in the range ±5 bar, even when fuel RON or spark advance map is changing.

Dynamic modeling of closed-chain robotic manipulators in the presence of frictional dynamic forces: A planar case

In this paper, the phenomenon of impact-contact in a closed-loop robotic chain has been dynamically modeled. The motion of this system, which comprises rigid links and ideal joints, has two phases. In the flight phase, the system is suspended in the air and moves only under the effect of Earth’s gravity. And in the impact phase, the mentioned robotic mechanism collides with a rough surface. We first present the direct form of dynamic equations for an open chain robotic system in the suspension phase. Then by applying the constraints that originate from the closed topology of the examined kinematic chain, the differential equations of the closed-loop system are obtained for the flight phase. In the impact phase, the contact force model is employed for modeling the impact-contact phenomenon. Although this method of impact modeling is more realistic, it leads to the stiffening of motion equations. In order to solve these equations, a special computational algorithm has been developed in this paper. To achieve more realistic results, the force of friction has also been considered in the collision of system joints with the ground. The dynamic formulations of friction have been used to obtain the friction force. In these models, an additional state variable is added to system variables in order to simulate some of the existing friction phenomena. Another objective of this paper is to present a criterion for selecting the most suitable model for simulating the motion of closed-loop robotic systems in the presence of friction. In this regard, the four dynamic friction force models of Dahl, reset integrator, LuGre, and elasto-plastic have been compared with the two static models of Coulomb and Bengisu & Akay. Although the developed algorithm is able to simulate any closed-loop robotic system that comes into contact with an uneven surface, the simulation of a 5-rigid-link closed-loop mechanism in collision with a rough surface of sinusoidal profile has been presented in this paper.

Passive design of green public buildings adapted to cold climate: a case study of China pavilion of the international horticultural exhibition 2019 Beijing China

This paper took the China Pavilion of the International Horticultural Exhibition 2019 Beijing China as the subject for study. Based on the influence of cold climate on people’s behaviors and their perception of the environment, the paper proposed designs of green public buildings adapting to the cold climate and analyzed the overall functions of green buildings via tests of temperature, humidity, illumination and total energy consumption to verify the ecological features and energy conservancy of the buildings, forming a closed-loop chain of procedures of the green design.

Multimodal Chain: Cross-Modal Collaboration Through Listening, Speaking, and Visualizing

Language is an integral part of human interpersonal communication, which is conveyed through multiple sensory channels. This multisensory communication skill has motivated an extensive number of studies on multimodal information processing, which are trying to develop a system that mimics this natural behaviour. For example, automatic speech recognition (ASR) represents listening activity, text-to-speech (TTS) represents speaking, and various image processing models to represent visual perception. Most are trained and tuned independently using parallel examples from the source to the target modality. However, this is not the case in real-life situations, where a lot of paired data are unavailable. Inspired by this self-supervision of the human auditory and visual perception system, we proposed a multimodal chain mechanism with a weakly-supervised chain training strategy that is trained and tuned jointly. In our proposed framework, when the amount of paired training data are insufficient, collaboration among ASR and TTS, image captioning (IC), and image production models can improve their performance through single or dual-loop chain mechanisms. Our experiment result showed that by using such a closed-loop chain mechanism, we can improve a model with both unpaired and unrelated data from different modalities in a semi-supervised manner. Through the collaboration of speech and visual chains, we improve an ASR model performance with an image-only dataset while maintaining the performance of other models.

Geometric design of rotary retractable plate structures based on parallelogram closed-loop chain linkages

For large-span retractable roof structures, the mechanism should be simple and efficient for the convenience of motion control. The kinematic characteristics of parallelogram closed-loop chain linkages (PCCL) show that a set of the angulated beams of PCCL rotates around the fixed points, which is suitable for retractable structures. This paper focuses on the geometrical design of the rotary retractable plate structures (RRPS), which evolves from PCCL by replacing the rotation angulated beams with cover plates. Each plate of RRPS has a fixed support and all the plates rotate simultaneously with a single DOF. The fixed points used as supports for cover plates to improve the stability and simplify the motion control of the system restrict the open area of the RRPS. By adjusting the contact boundaries of the cover plates, an optimisation method is proposed to increase the open area of the RRPS after fully deployed. The design approach is successfully extended to both symmetrical and asymmetrical RRPS. An example is carried out to demonstrate the feasibility of the approach and a simple physical model is manufactured to validate the design result in the example.