Modular Concept Research Articles

Modular Design for Versatile Broadband Polarizing Metasurfaces with Freely Switching Functions

AbstractPolarization is a fundamental property of electromagnetic waves that plays a key role in many physical phenomena and applications. Schemes to manipulate it are revisited with the emergence of metasurfaces, which have brought multi‐functionalities straightforwardly. However, this has come at the expense of design complexity that relies strongly on field theory. Here, an ingenious strategy of modular design is proposed to construct subwavelength multifunctional polarization control devices. Chiral metasurfaces with different handedness are first proposed and regarded as modules. The versatile polarization controller can thus be obtained with the combination of different modules. These experiments demonstrate that the well‐designed polarization controller possesses reconfigurable functionality, and various broadband polarization and amplitude regulation functions with high efficiency including arbitrary linear polarization rotation, asymmetric transmission effect, neutral‐density‐like filter, polarization beam splitter, etc., can be readily realized just by changing the cascaded modules. The physical mechanisms of the versatile polarization controller and chiral metasurface modules are both guaranteed by the Fabry–Pérot‐like resonances, which are theoretically verified via the transfer matrix method. It is envisioned that the modular concept will be of great benefit to designing compact multifunctional polarization controllers.

Assembling a supramolecular 3D network with tuneable mechanical properties using adamantylated cross-linking agents and β-cyclodextrin-modified hyaluronan

Hydrogels based on the supramolecular host–guest concept can be prepared if at least one constituent is a polymer chain modified with supramolecular host or guest (or both) units. Low-molecular-weight multitopic counterparts can also be used, however, guest molecules in the role of cross-linking agents are seldom reported, although such an approach offers wide-ranging possibilities for tuning the system properties via easily achievable structural modifications. In this paper, a series of adamantane-based star-like guest molecules was used for cross-linking of two types of β-cyclodextrin-modified hyaluronan (CD-HA). The prepared 3D supramolecular networks were characterised using nuclear magnetic resonance, titration calorimetry and rheological measurements to confirm the formation of the host–guest complexes between adamantane moieties and β-cyclodextrin units, including their typical properties such as self-healing and dynamic nature. The results indicate that the nature of the cross-linker (amides versus esters) has a greater impact on mechanical properties than the length of the guest's arms. In addition, the results show that the length of the HA polymer chain is more important than the degree of modification with supramolecular units. In conclusion, it was proven that the modular concept employing low-molecular-weight cross-linking guests is valuable for the formulation of supramolecular networks, including hydrogels.

Development and Experimental Validation of a Reduced-Scale Single-Phase Modular Multilevel Converter Applied to a Railway Static Converter

With special emphasis in recent years, an increase has been verified not only in demand but also in the price of electricity, arising the need to develop more reliable and efficient electrical energy conversion systems. In this context, emerges the utilization of the modular multilevel converter (MMC) based on submodules. The key to the MMC is modularity, which allows the converter to reach higher performance levels, improving the voltage and current output signals of the converter, in a compact solution. The modularity concept allows the increase of the operation voltage using submodules in series, and the increase of the operating current using submodules in parallel. Additionally, in the event of a submodule malfunction, the converter can be reconfigured and continue the operation, albeit at a lower power level. Due to its versatility, the MMC can be used in a variety of applications, such as HVDC power transmission systems, solid-state transformers, renewable energy interfaces, and more recently, railway power systems. In this context, this paper focuses on the development and experimental validation of a single-phase MMC based on the use of half-bridge submodules applied to a railway static converter, where the main focus lies on the AC side control. The control algorithms are fully described for a single-phase MMC reduced-scale prototype implemented (500 W, 230 V–50 Hz, 200 VDC), connecting two submodules in series in the upper arm, two submodules also in series in the lower arm, the respective driver and command circuits, sensing and signal conditioning circuits, as well as a digital control platform recurring to the DSP TMS320F28379D. Experimental results were obtained to validate each submodule individually, and, later, to verify the operation of the MMC with the set of four submodules.

Blockchain-enabled cross-chain collaboration model for elderly health information from a whole process perspective.

Due to people having less children and the aging population, the demand for elderly health services is increasing, which leads to an increase in demand for elderly health information. However, there is a gap between elderly medical health information and elderly care information due to different storage institutions and storage methods, which makes it difficult for the medical service industry and the elderly service industry to fully grasp and utilize the health information of the elderly. Therefore, it is difficult to provide whole process services that combine elderly medical health and elderly care. To solve the problem of the poor collaborative utilization of elderly healthcare information, this paper, based on blockchain cross-chain technology and the literature and field research, studies the specific contexts that are needed to realize elderly health information collaboration. Based on the system theory viewpoint, the component-based modular design concept is used to identify the attributes and types of current health information of the elderly from health information related to the five modules of prevention, detection, diagnosis, treatment, and rehabilitation in the process of elderly healthcare. This paper explores the structure, elements, and interactions between the medical health information chains and the elderly care information chains. We build a blockchain-enabled cross-chain collaboration model of elderly health information from the perspective of the whole process with the help of the underlying logic of virtual chain, and to realize the applicability and flexibility of cross-chain collaboration for health information for the elderly in the whole process. The research results show that the proposed cross-chain collaboration model can realize the cross-chain collaboration of health information for the elderly with easy implementation, high throughput, and strong privacy protection.

Diazadiboraacenes: Synthesis, Spectroscopy and Computations

AbstractThe incorporation of heteroatoms into hydrocarbon compounds greatly expands the chemical space of molecular materials. In this context, B−N doping takes a center stage due to its isosterism with a C=C‐bond. Herein, we present a new and modular synthetic concept to access novel diazadiborabenzo[b]triphenylenes7 a–husing the B−N doped biradical16as intermediate. Characterization of the photophysical properties revealed the emission spectra of the diazadibora benzo[b]triphenylenes7 a–hcan conveniently be tuned by small changes of the substitution on the boron‐atom. All of the diazadibora compounds show a short life‐time phosphorescence. Additionally, we were able to rationalize the excited‐state relaxation of the diazadiboraacene7 avia intersystem crossing by quantum chemical calculations. The new synthetic strategy provides an elegant route to various novel B−N doped acenes with great potential for applications in molecular materials.

Diazadiboraacenes: Synthesis, Spectroscopy and Computations.

The incorporation of heteroatoms into hydrocarbon compounds greatly expands the chemical space of molecular materials. In this context, B-N doping takes a center stage due to its isosterism with a C=C-bond. Herein, we present a new and modular synthetic concept to access novel diazadiborabenzo[b]triphenylenes 7 a-h using the B-N doped biradical 16 as intermediate. Characterization of the photophysical properties revealed the emission spectra of the diazadibora benzo[b]triphenylenes 7 a-h can conveniently be tuned by small changes of the substitution on the boron-atom. All of the diazadibora compounds show a short life-time phosphorescence. Additionally, we were able to rationalize the excited-state relaxation of the diazadiboraacene 7 a via intersystem crossing by quantum chemical calculations. The new synthetic strategy provides an elegant route to various novel B-N doped acenes with great potential for applications in molecular materials.

Sport for All

The ‘skateboard’ chassis isn't necessarily right for every EV. E&HVTI investigates how WAE's new modular concept has been designed to accelerate the development of high performance sports cars

Direct Thermal Management of Windings Enabled by Additive Manufacturing

The electrification and hybridization of ground- and air-transport, in pursuit of Carbon Net Zero targets, is driving demand for high power-density electrical machines. The power-density and reliability of electrical machines is ultimately limited by their ability to dissipate internally generated losses within the temperature constraints of the electrical insulation system. As the electrical windings are typically the dominant source of loss, their enhanced design is in the critical path to improvements in power-density. Application of metal additive manufacturing has the potential to disrupt conventional winding design by removing restrictions on conductor profiles, topologies and embedded thermal management. In this paper, a modular end-winding heat exchanger concept is presented, which enables effective direct cooling without occupying valuable stator slot cross-section. In addition, this arrangement eliminates the need for a good stator-winding thermal interface, thereby allowing mechanical or other less permanent winding retention methods to be used, facilitating non-destructive disassembly and repair. A prototype winding is fabricated and experimentally tested to demonstrate the feasibility of the concept, yielding promising results.

Shoot-root signal circuit: Phytoremediation of heavy metal contaminated soil.

High concentrations of heavy metals in the environment will cause serious harm to ecosystems and human health. It is urgent to develop effective methods to control soil heavy metal pollution. Phytoremediation has advantages and potential for soil heavy metal pollution control. However, the current hyperaccumulators have the disadvantages of poor environmental adaptability, single enrichment species and small biomass. Based on the concept of modularity, synthetic biology makes it possible to design a wide range of organisms. In this paper, a comprehensive strategy of "microbial biosensor detection - phytoremediation - heavy metal recovery" for soil heavy metal pollution control was proposed, and the required steps were modified by using synthetic biology methods. This paper summarizes the new experimental methods that promote the discovery of synthetic biological elements and the construction of circuits, and combs the methods of producing transgenic plants to facilitate the transformation of constructed synthetic biological vectors. Finally, the problems that should be paid more attention to in the remediation of soil heavy metal pollution based on synthetic biology were discussed.

Theoretical modeling and analysis of a quasi-zero-stiffness vibration isolator equipped with extensible and axially magnetized negative stiffness modules

Quasi-zero-stiffness (QZS) isolation systems have demonstrated good performance in low-frequency vibration isolation fields. However, the existing QZS isolation systems with traditional negative stiffness elements cannot support high payloads under miniaturization and simplification. To give some beneficial insights into high loading capacity, optimized structure, and good vibration isolation performance, a novel axially magnetized negative stiffness module (MNSM) is proposed based on the concepts of modularity and expansibility. Concretely, an axially magnetized negative stiffness unit (MNSU) is designed as the fundamental building block of MNSM, and the proposed MNSM can be composed of different axially magnetized negative stiffness units (MNSUs) for diversified requirements. To effectively investigate the characteristics of the MNSU, a computationally high efficient equivalent surface current method is developed. As a result, two types of MNSUs with optimized parameters are achieved, and their design procedures are presented respectively. To verify the benefits of the MNSMs, the designed QZS isolator is theoretically modeled and solved with the average method and then verified through the Runge–Kutta method. Through analyzing the isolation systems with MNSMs under different nonlinearities and dynamic parameters, the results indicate that the proposed MNSMs can endow the QZS vibration isolator with a lower resonant frequency, a wider isolation frequency range, and a smaller transmissibility. Additionally, it is also demonstrated that there is an inverse relationship between the complexity of the MNSM structure and the sensitivity of the isolation system.

A Vertically Modularized Reconfigurable Wireless Power Transfer System: Architecture, Modeling, and Design

It is known that megahertz (MHz) wireless power transfer (WPT) is particularly beneficial in terms of spatial freedom of power transfer and circuit compactness. Meanwhile, design complexity is a main obstacle to the spread of MHz WPT. In this article, a new modular design concept is proposed to conveniently reconfigure a MHz WPT system for different applications. Multiple predesigned functional unit modules can easily be combined to form a complete new WPT system with a different power level and transfer distance. A vertically stacked architecture is especially chosen to save space in actual applications. Detail analytical derivations are conducted to analyze the modular design, including the influence of different combinations of the unit modules. A new interleaved coil design is developed to reduce the proximity effect and cross coupling among the vertically stacked modules. Finally, the modular design concept is validated by experiments and demonstrates the desired scalability in both power levels and transfer distances. Through 15 combinations of the unit modules, the experimental WPT system can be reconfigured to provide an output power from 4 to 116 W. The effective transfer distance can be also extended from 30 to 90 mm and 80% system dc–dc efficiency is achieved within a 70-mm transfer distance using 100-mm-diameter printed circuit board coils.

Evaluation of a Modular Filter Concept to Reduce Microplastics and Other Solids from Urban Stormwater Runoff

This paper describes an innovative Decentralized Technical Sustainable Drainage System (SuDS) concept, which is based on technical devices, such as sieves, sedimentation barriers, floating barriers and a magnetic module, which addresses, mainly, the fine matter. The SuDS is designed as a retrofit system so that no costly and time-consuming conversion measures are necessary. Due to the possibility of free configurability of individual modules in the three levels, road, gully and drain, a novel solution approach is presented, which is not available on the market, for a reduction in solids in general and microplastics in particular. The retention performance of selected modules and their combinations is demonstrated by means of bench tests according to the test procedure of the German Institute for Construction Engineering (DIBt) for the evaluation of decentralized treatment systems. Four different rain intensities, from light to medium up to heavy rain, are charged to the filter modules. Collected and fractionated road-deposited sediment (RDS) was selected as the test substance (10 kg). Additional tests with tyre powder, PE pellets, cigarette butts and candy wrappers helped to make clear the filter process of the particulate matter. The retention performance was determined by the mass balance between the defined dosage and at the outlet. For this purpose, the total volume flow of the effluent was passed over a stainless-steel sieve with a diameter of 600 mm and a mesh size of 20 µm. For the test substance, RDS retention rates up to 97% were measured. Very fine matter, particularly, was technically challenging to obtain; <63 µm up to 66% could be retained by the filter modules. Modules in the road space, such as porous asphalt or additional retention spaces, in the area of the curb as well as direct infiltration in the road drainage shaft are theoretically described and discussed. The outlook also addresses the potential of an intelligent network to reduce the input of pollution from urban stormwater runoff.

Simulation-ready graphene oxide structures with hierarchical complexity: a modular tiling strategy

Graphene oxide (GO) sheet structures are highly variable and depend on preparation conditions. The use of molecular simulation is a complementary strategy to explore how this complexity influences the ion transport properties of GO membranes. However, despite recent advances, computational models of GO typically lack the required complexity as suggested by experiment. The labor required to create such an ensemble of such structural models with the required complexity is impractical without recourse to automated approaches, but no such code currently can meet this challenge. Here, a modular tiling concept is introduced, along with the HierGO suite of code; an automated approach to producing highly complex hierarchically-structured models of GO with a high degree of control in terms of holes and topological defects, and oxygen-group placement, that can produce simulation-ready input files. The benefits of the code are exemplified by modeling and contrasting the properties of three types of GO membrane stack; the widely-modeled Lerf–Klinowski structure, and two types of highly heterogeneous GO sheet reflecting differing processing conditions. The outcomes of this work clearly demonstrate how the introduction of the complexity modeled here leads to new insights into the structure/property relationships of GO with respect to permeation pathways of water, ions and molecular agents that are inaccessible using previously-considered models.

Solar and Wind Quantity 24 h—Series Prediction Using PDE-Modular Models Gradually Developed according to Spatial Pattern Similarity

The design and implementation of efficient photovoltaic (PV) plants and wind farms require a precise analysis and definition of specifics in the region of interest. Reliable Artificial Intelligence (AI) models can recognize long-term spatial and temporal variability, including anomalies in solar and wind patterns, which are necessary to estimate the generation capacity and configuration parameters of PV panels and wind turbines. The proposed 24 h planning of renewable energy (RE) production involves an initial reassessment of the optimal day data records based on the spatial pattern similarity in the latest hours and their follow-up statistical AI learning. Conventional measurements comprise a larger territory to allow the development of robust models representing unsettled meteorological situations and their significant changes from a comprehensive aspect, which becomes essential in middle-term time horizons. Differential learning is a new unconventionally designed neurocomputing strategy that combines differentiated modules composed of selected binomial network nodes as the output sum. This approach, based on solutions of partial differential equations (PDEs) defined in selected nodes, enables us to comprise high uncertainty in nonlinear chaotic patterns, contingent upon RE local potential, without an undesirable reduction in data dimensionality. The form of back-produced modular compounds in PDE models is directly related to the complexity of large-scale data patterns used in training to avoid problem simplification. The preidentified day-sample series are reassessed secondary to the training applicability, one by one, to better characterize pattern progress. Applicable phase or frequency parameters (e.g., azimuth, temperature, radiation, etc.) are related to the amplitudes at each time to determine and solve particular node PDEs in a complex form of the periodic sine/cosine components. The proposed improvements contribute to better performance of the AI modular concept of PDE models, a cable to represent the dynamics of complex systems. The results are compared with the recent deep learning strategy. Both methods show a high approximation ability in radiation ramping events, often in PV power supply; moreover, differential learning provides more stable wind gust predictions without undesirable alterations in day errors, namely in over-break frontal fluctuations. Their day average percentage approximation of similarity correlation on real data is 87.8 and 88.1% in global radiation day-cycles and 46.7 and 36.3% in wind speed 24 h. series. A parametric C++ executable program with complete spatial metadata records for one month is available for free to enable another comparative evaluation of the conducted experiments.

Concept for a generic modular software architecture for the integration of quality relevant data and sample implementation for a laser sintering system

Additive manufacturing (AM) processes, such as laser sintering (LS), are complex in parameter dependencies and process flow. To be able to analyse and potentially predict the quality of the manufactured parts, the monitoring of multiple process parameters along the process chain is necessary. Currently, there are standards defined for data exchange but there is no framework to store and analyse these data or enhance a system with additional sensors. Therefore, a generic software concept is required that allows a consistent process monitoring. In this publication, a generic workflow for AM including pre- and post-processing steps is presented and relevant communication interfaces as e.g. OPC-UA, and relevant data types to be collected are identified. The concept allows the use of different communication protocols, storing and evaluating process data and by its modularity the enhancement of a system with its hardware. The stored values can be analysed by further scripts. The architecture is applicated on LS and partial aspects are prototypically implemented as well as practically validated. Therefore, a generic modular software concept, based on a hardware independent Docker based architecture, is presented. A practical feasibility test shows that machine and image data can be decentralized tapped and recorded, cloud-based analysed and web-based visualized.

Evolutionary Patterns of Modularity in the Linkage Systems of the Skull in Wrasses and Parrotfish.

The concept of modularity is fundamental to understanding the evolvability of morphological structures and is considered a central framework for the exploration of functionally and developmentally related subsets of anatomical traits. In this study, we explored evolutionary patterns of modularity and integration in the 4-bar linkage biomechanical system of the skull in the fish family Labridae (wrasses and parrotfish). We measured evolutionary modularity and rates of shape diversification of the skull partitions of three biomechanical 4-bar linkage systems using 205 species of wrasses (family: Labridae) and a three-dimensional geometric morphometrics data set of 200 coordinates. We found support for a two-module hypothesis on the family level that identifies the bones associated with the three linkages as being a module independent from a module formed by the remainder of the skull (neurocranium, nasals, premaxilla, and pharyngeal jaws). We tested the patterns of skull modularity for four tribes in wrasses: hypsigenyines, julidines, cheilines, and scarines. The hypsigenyine and julidine groups showed the same two-module hypothesis for Labridae, whereas cheilines supported a four-module hypothesis with the three linkages as independent modules relative to the remainder of the skull. Scarines showed increased modularization of skull elements, where each bone is its own module. Diversification rates of modules show that linkage modules have evolved at a faster net rate of shape change than the remainder of the skull, with cheilines and scarines exhibiting the highest rate of evolutionary shape change. We developed a metric of linkage planarity and found the oral jaw linkage system to exhibit high planarity, while the rest position of the hyoid linkage system exhibited increased three dimensionality. This study shows a strong link between phenotypic evolution and biomechanical systems, with modularity influencing rates of shape change in the evolution of the wrasse skull.

A Method to Design Assembling Lines for Super Premium Efficiency Motors

Producing highly efficient electric motors remains a challenge nowadays. Given that the legislation in the field requires the transition to the production of engines with increased efficiency, for manufacturing companies, switching from one generation of engines to another can be a difficult task. This paper analyzes ways to adapt the assembly of engines of the IE4 generation starting from the assembly lines of the engines of the previous generation, IE3. The analysis of the assembly process covers both the operator training part and the actual assembly part. Ten possible variants for the assembly line and specific decisional variables have been defined. The decision to choose the optimal assembly configuration was made using as management tools the matrix of consequences and utilities. The validation of the theoretical model of the assembly line was carried out through a case study built for two classes of electric motors, namely G90 and G180. For a total production of IE4 electric motors of 20,000 parts/month, the analyzed variants, respectively, the two sizes (G90 and G100) represent 35% (7000 parts/month) of the G90 size and 22% (4400 parts/month) the G100 size. The aim is to provide a new modular assembly concept, which depending on the orders, can use, as given in the conclusion of this article.

Does concrete modular system add value in residential buildings - Case study and qualitative evaluation

The concept of modularity has been widely accepted in production environment. However, its adoption in the construction sector is still limited. The research aims to address what are the main (sub) challenges in adopting concrete modularity concept in residential housing. The study collected possible challenges from previous studies, and asked expert respondents to perform AHP-pair wise comparison. It also used parameters from two case projects of a two-storey housing to examine the time and cost implications for modular concrete construction. The results shown the 'high upfront investment cost', 'lack of interest from consumers', 'no/lack of guidelines and regulation in design', 'lack of suppliers/products' and 'complexity to integrate with onsite structure' as the top five sub-challenges. From the project case 4% cost increase and 25% time saving can be expected from modular concrete adoption to a two-storey housing project.

Effects of step-by-step line balancing in apparel assembly line

The mixed work assignment technique was applied to the modular production concept to solve the apparel assembly line balancing problem. Specifically, an algorithm was implemented to generate workstations by first classifying tasks into modules through an analysis of the manufacturing process and assigning grouped tasks in the single task–multiple workers and multiple tasks–single worker assignment methods. Then, worker assignment was sequentially performed considering the skill level of the worker. A simulation of producing 100 men’s shirts was performed. Owing to line balancing, the total production time was considerably lower than that reported in previous studies. The enhanced performance was attributable to the fact that unlike previous studies that limited the apparel assembly line balancing problem to worker assignment, line balancing was performed through both task and worker assignment in this study. The results demonstrated that task assignment must be considered in the design stage in the apparel assembly line balancing problem.

Using artificial intelligence assistant technology to develop animation games on IoT

This research proposes an XNA animation game system with AI technology for action animation games in mobile devices, based on an object-oriented modular concept. The animation game function with AI technology is encapsulated into independent objects, through the combination of objects to build repetition. It adds AI technology to the finite state machine, fuzzy state machine and neural network and attempts to combine the traditional rule-base system and learning adaptation system to increase the learning ability of traditional AI roles. The main contributions are compared with traditional methods and the AI animation game system is shown to have more reusability, design flexibility and expansibility of its AI system through the object composition approach. It adds AI technology to combine the traditional rule-base system and learning adaptation system to increase the learning ability of traditional AI roles. Therefore, AI animation game producers can accelerate their processes of developing animation games and reducing costs.