Design Of Systems Research Articles

DC Series Arc Fault Detection Method With Resonant Filter Design for PV Systems

DC Series Arc Fault Detection Method With Resonant Filter Design for PV Systems

Periodic event-triggered data-driven control for networked control systems with time-varying delays

This article focuses on data-driven analysis and controller design for networked control systems (NCSs) with network-induced delays. The study considers a linear time-invariant (LTI) system controlled through a periodic event-triggering mechanism. First, by leveraging data-based representations, we establish data-based stability conditions for NCSs with time-varying delays. Furthermore, we propose the data-based method for co-designing the controller and the periodic event-triggering scheme. In addition, we present novel data-based conditions for verifying dissipativity properties of NCSs. The effectiveness of our proposed methods is validated through a simulation and a turbofan engine hardware-in-the-loop (HIL) experiment.

Determination of the moment–rotation relation of continuous timber–concrete composite floors based on the component method

Timber–concrete composite (TCC) combines the advantages of timber and reinforced concrete construction. In multi-storey buildings, the design of TCC floors is often governed by the deformation serviceability requirements. One way to improve deformation serviceability is through the design of continuous floor systems. However, the current practice of TCC slab systems is often limited to load-carrying as single-span beams. This paper presents an analytical model based on the component method for determining the moment–rotation relation of continuous TCC slabs in the range with negative bending moments. The investigations involve the development of load–displacement curves for the individual force-transmitting components, including timber and reinforced concrete, followed by their assembly into a component model. The model has been verified using finite element calculations and the results demonstrate that the moment–rotation relation of continuous TCC systems can be accurately captured. As the variability of the material properties strongly influences the stiffness of the joint and therefore the deformation and stresses in the TCC slab, a probabilistic analysis of the material parameters was performed using the Monte Carlo method. The probabilistic investigations show that the variability of the input parameters has a significant impact on the joint stiffness, with notable scattering observed in the moment–rotation relation, especially in the range of the cracking phase of the concrete. The results from the probabilistic investigations enable initial statements about the joint stiffness of continuous timber–concrete composite slabs in ranges with negative bending moments.

Glycocalyx Interactions Modulate the Cellular Uptake of Albumin-Coated Nanoparticles.

Albumin-based nanoparticles (ABNPs) represent promising drug carriers in nanomedicine due to their versatility and biocompatibility, but optimizing their effectiveness in drug delivery requires understanding their interactions with and uptake by cells. Notably, albumin interacts with the cellular glycocalyx, a phenomenon particularly studied in endothelial cells. This observation suggests that the glycocalyx could modulate ABNP uptake and therapeutic efficacy, although this possibility remains unrecognized. In this study, we elucidate the critical role of the glycocalyx in the cellular uptake of a model ABNP system consisting of silica nanoparticles (NPs) coated with native, cationic, and anionic albumin variants (BSA, BSA+, and BSA-). Using various methodologies-including fluorescence anisotropy, dynamic light scattering, microscale thermophoresis, surface plasmon resonance spectroscopy, and computer simulations─we found that both BSA and BSA+, but not BSA-, interact with heparin, a model glycosaminoglycan (GAG). To explore the influence of albumin-GAG interactions on NP uptake, we performed comparative uptake studies in wild-type and GAG-mutated Chinese hamster ovary cells (CHO), along with complementary approaches such as enzymatic GAG cleavage in wild-type cells, chemical inhibition, and competition assays with exogenous heparin. We found that the glycocalyx enhances the cell uptake of NPs coated with BSA and BSA+, while serving as a barrier to the uptake of NPs coated with BSA-. Furthermore, we showed that harnessing albumin-GAG interactions increases cancer cell death induced by paclitaxel-loaded albumin-coated NPs. These findings underscore the importance of albumin-glycocalyx interactions in the rational design and optimization of albumin-based drug delivery systems.

Design and Implementation of a Width-Adjustable Asynchronous FIFO for Cross-Clock Domain Data Transmission

Existing research shows that asynchronous FIFO has been widely used in a variety of complex system designs, such as FPGA-based image processing systems, USB communication systems, and so on. To make the designed asynchronous FIFO more programmable and flexible, so that it can adapt to various application scenarios more quickly, this paper studies and designs an asynchronous FIFO with adjustable input and output bit width. In this study, according to the relationship between 24-bit input data and 32-bit storage space, four 24-bit data are selected to fill three RAM storage spaces at one time. According to the multiple relationships between 32-bit storage space and 128-bit output data, the reading pointer is enlarged by 4 times to realize the function of reading four 32-bit data at one time. This whole process realizes the conversion of data bit width through data splicing. Finally, the 24-bit RGB888 image data is successfully converted into 128-bit data and transmitted to the bus, which successfully solves the problem of data width mismatch.

Model‐based systems engineering and safety assessment: A workflow for mechatronic systems design

AbstractMechatronic systems become ever more complex because of their increasing number of interconnected safety critical components and sophistication. MBSE (Model‐based Systems Engineering) and MBSA (Model‐Based Safety Assessment) are the most commonly adopted approaches to deal with the design and safety analysis of mechatronic systems. Unfortunately, both approaches are normally adopted separately, especially in the earlier phases of system design, thus leading to a lack of communication between system engineers and the safety team. This work aims to fill that gap at a high level, that is, through process interaction. This paper proposes an enhanced V‐model for the design of safety‐critical mechatronic systems. It relates a system development process with specific safety assessment methods. Specifically, the proposed workflow details exchange flows between the RFLP (Requirements, Functional, Logical, Physical) method, the FHA (Functional Hazard Analysis), the FMEA (Failure Mode and Effects Analysis), the MBSA and simulation, and the FTA (Fault Tree Analysis). These analyses are complemented with multiphysics modeling and simulation to observe system behavior in functional and failure scenarios, with the aim of requirements verification. The design workflow has been applied to a winged Unmanned Aerial Vehicle to apply the parallel process and the necessary interaction of MBSE and MBSA approaches. The information flows between the individual activities proved effective for designing a safe system before the verification phase. The main benefit of the proposed workflow is providing both the design and safety team with some interaction points, thus avoiding a lack of safety‐critical analysis in the early phases of system design.

Review of Recent Developments in AI-based Data Processing and Prediction for Braced Excavation Design

Abstract This paper presents a review of the recent advances in the application of Artificial intelligence (AI) techniques for data processing and prediction in the design and construction of braced excavation systems. It introduces various AI algorithms employed in addressing complex data processing and deformation prediction challenges in braced excavation. A pivotal development has been in the area of soil parameter and in-situ monitoring data processing, which facilitates more reliable site characterization for efficient design. This paper delves into wall system and deformation predictions, showcasing AI’s ability to integrate multi-source data for real-time prediction. It also addresses spatiotemporal prediction, enhancing prediction accuracy by accounting for uncertainties. The significance of groundwater is highlighted by introducing predictive models that consider groundwater drawdown. Additionally, it discusses stability prediction based on the factor of safety of braced excavation, enabling proactive safety management for the retaining wall system and the surrounding environment. Furthermore, the paper discusses the challenges and opportunities associated with the use of generative AI and large language models, providing an overview of their significance, applications, and future directions in braced excavation.

Large Adsorption Capacity for Space Molecular Pollutants Realized by a Metal-Organic Framework.

The rapid development of capable spacecraft coatings for removing volatile organic compounds (VOCs) demands materials with a large adsorption capacity to ensure a long-duration exploration mission in a low Earth orbit (LEO). MIL-53(Al) with abundant sites exhibits resistance to the space environment in the LEO and shows great potential for VOC removal. This study combined an adsorption experiment and first-principles simulations to investigate the adsorption performance of MIL-53(Al). MIL-53(Al) demonstrated an excellent adsorption capacity for various VOCs, reaching 606.04 mg/g for m-xylene and 22.69 cm3/g for methane, which is 6 times higher than traditional adsorption methods. First-principles simulations revealed that the adsorption capacity is significantly influenced by micropores through the pore effect and breath effect, which restrict diffusion and enhance adsorption, respectively. Additionally, we predicted the adsorption properties of VOCs that are difficult to characterize through ground-based simulated experiments, further validating the potential application of MIL-53(Al) for VOC removal in the LEO. This work expands the application range of MIL-53(Al), optimizes VOC removal strategies, and offers a novel approach to protecting spacecraft in the LEO. Our findings contribute to the development of advanced materials for space exploration and provide valuable insights into the design of efficient VOC removal systems for spacecraft in the LEO.

Biomimetic Superhydrophobic Triboelectric Surface Prepared by Interfacial Self‐Assembly for Water Harvesting

AbstractExtracting water from air offers a promising route to address the global challenge of water scarcity. However, bionic engineering surfaces for water harvesting often struggle with efficiently coordinating droplet nucleation and desorption. The recently emerging triboelectric effect at the liquid–solid interface offers a novel approach for developing bionic fog harvesting surfaces. In this study, inspired by Namib Desert beetles and lotus leaves, a biomimetic superhydrophobic surface with nanoscale hydrophilic domains is prepared via interfacial self‐assembly, exhibiting heterogeneous wettability for effective water harvesting. The essence of interfacial self‐assembly lies in the synergy of non‐covalent interaction forces, driving the self‐assembly of nanoparticles into surface micro‐nano hierarchical structures, thereby regulating wettability and increasing potential nucleation sites. Additionally, the triboelectric effect can directly utilize the triboelectric charges to facilitate droplet migration. The triboelectric effect can be generated by flexible mechanical input induced by walking, which enhances interfacial mass transfer, thereby rapidly improving droplet removal and achieving a 39.02% increase in water harvesting efficiency. This study has opened up a new breakthrough for the design of portable and efficient water harvesting systems.

Quantitative magnetooptical analysis using indicator films for the detection of magnetic field distributions, temperature, and electrical currents

The accurate characterization of local magnetic fields and temperature is vital for the design of electronic systems. To meet this imperative, we present a novel non-contact approach for simultaneous quantitative magnetic field imaging and temperature sensing using magnetooptics and a bismuth-doped yttrium iron garnet film with out-of-plane anisotropy. For the direct signal quantification, a Stokes polarization camera is employed in a conventional magnetooptical microscope. The magnetization in the garnet is modulated with an external magnetic field to continuously image the Faraday rotation at four distinct points along the saturating magnetization loop. The method enables sensing of the magnetooptical signal in saturation, the magnetooptical susceptibility, the temperature, and self-calibrated driftfree imaging of the out-of-plane magnetic field component. A spatial resolution of magnetic field in the micrometer range with millisecond exposure time is demonstrated. The method is verified by analyzing the stray magnetic field distribution of electrical current in a wire simultaneously to the Joule heating induced by the applied current.

Effect of chemical modification on hydraulic conductivity of stratified porous media

ABSTRACT Understanding hydraulic conductivity is essential in porous media as it dictates the capacity of fluids to permeate through these substances. This research investigated the impact of chemical modification using fly ash on hydraulic conductivity. The coefficient of hydraulic conductivity along the bedding plane at different angles of orientations was predicted by employing machine learning techniques such as gene expression programming (GEP), artificial neural networks (ANNs), and regression tree (RT), considering various influencing parameters. As the amount of fly ash in the porous medium rises, the hydraulic conductivity decreases. The statistical results demonstrate that the proposed ANN model effectively forecasted the horizontal hydraulic conductivity. It achieved the highest R2 value (0.989), the lowest mean absolute percentage error value (5.772), the lowest scatter index value (0.040), and the lowest Akaike Information Criterion value (−2,359.914) compared to the GEP, RT, and previously established approaches. Moreover, a novel equation has been proposed for determining horizontal hydraulic conductivity, which can be used for any stratified medium, distinguishing this work from previous ones. These findings can inform global practices in mitigating groundwater contamination, enhancing irrigation efficiency, and improving the design of subsurface fluid flow systems, making it a valuable contribution to both academic and practical applications worldwide.

Dynamic stability analysis of the aircraft electrical power system in the more electric aircraft concept

This paper presents the modelling and analysis process of the electrical power management system on board an electrified aircraft conforming to the More/All Electric Aircraft concept. The main objective of the study is to assess the stability of the Electric Power Distribution System under different operational conditions, including the aspect of constant power loads. The paper describes the structure of the system, in which the key role is played by a synchronous generator and a three-phase rectifier converting alternating current AC into direct current DC. To solve the problem, modeling methods in the Matlab/Simulink environment were used, which enabled the analysis of the dynamic properties of the system and the assessment of stability under various types of loads. The obtained test results show that the presence of constant power loads can lead to instability in the EPDS system, manifested by voltage and current oscillations exceeding the standards specified in the MIL-STD-704E standard. The paper also provides tools for predicting system stability without the need to conduct full stability tests, which is important for the design of modern aviation power systems. The final section of the work presents the research results obtained and the resulting significant insights and practical conclusions.

Shaking Table Test and Numerical Modeling of Seismic Behavior of Rectangular Tunnel Structures Embedded in Soft Clay

In this paper, a series of 1-g shaking table model tests were carried out to investigate the seismic behavior of a relatively stiff rectangular tunnel structure installed in soft clay bed, accounting for different ground motions with varying peak accelerations. Using a validated numerical analysis procedure, a suite of three-dimensional (3D) finite element (FE) analyses was performed to systematically study the factors of tunnel burial depth, seismic intensity, flexural rigidity of the middle column and tunnel wall thickness on the seismic response of rectangular tunnel structures installed in clayey ground. It was found that, with the increasing burial depth, the seismic response of rectangular tunnel structure became more intense due to the increased inertial force arising from the overlying clay; in terms of improving the seismic performance of tunnel structure, increasing tunnel wall thickness seemed more effective than increasing flexural rigidity of the middle column. Furthermore, it was found that the existing simplified approaches generally tended to overestimate the earthquake-induced racking distortions of rectangular tunnels installed in clayey ground. A new semi-empirical relationship was derived for better correlating the racking ratio with flexibility ratio for rectangular tunnels embedded in soft clays, which could provide a useful reference for the seismic design and risk assessment of similar clay-tunnel systems.

Multi Combustor Turbine Engine Acceleration Process Control Law Design

Abstract Focusing on the collaborative fuel supply and acceleration problem of multi combustor turbine engine, a variable geometry composite regulation acceleration control law design method based on the combination of compressor intermediate stage air bleed(CIB) and low-pressure turbine guide vanes(LTGV) is proposed. The multi combustor collaborative fuel supply law and variable geometry regulation law during acceleration process are obtained by Particle Swarm Optimization-Sequence Quadratic Program (PSO-SQP) optimization, and the composite regulation acceleration control strategy of dual/single combustion chamber idle acceleration process is explored. The multi combustor acceleration process simulation results indicate that the variable geometry composite regulation method can effectively alleviate the stability margin limitation of the compressor during the initial acceleration stage. Compared with conventional acceleration methods, the maximum relative reduction in acceleration time of our method reaches 26%; Enhancing the combustion exergy efficiency during the acceleration process can significantly improve the engine's acceleration performance.; For the acceleration process from single combustion chamber idle operation to normal operation of a dual combustion chamber, simultaneous fuel supply from both combustion chambers during acceleration has a shorter acceleration time. The research results of this paper can provide important references for the design of transition state control systems for multi combustor turbine engines.

Performance Analysis of Uplink Code Division Multiplexing for LEO Satellite Constellations Under Nonlinear Power Amplifiers

This paper studies the performance of the communication link between a ground station and the satellites of a LEO constellation, employing code division multiplexing and a non-linear high-power amplifier. The analysis shows that the input power selection at the high-power amplifier of the ground station has a significant impact on overall system performance. The results concerning output power, the challenge of adjusting the back-off with a continuously changing number of satellites, and improved energy efficiency suggest operating in saturation. In this scenario, we can choose to transmit directly the sign of the sum of the signals directed to individual satellites. Analytical exact and simplified results are derived, enabling the estimation of performance as a function of the number of satellites being served when the amplifier operates at saturation. These analytic results are further validated through simulations. A formula to compute the loss across different numbers of satellites is also presented. The performance under saturated amplifier conditions is evaluated, compared, and discussed, providing valuable insights for simplifying the design and operation of satellite uplink communication systems under power amplifier constraints.

Investigation of nonlinear dynamic behaviors of vertical rotor system supported by aerostatic bearings

Abstract A common issue associated with gas bearing-rotor systems is the tendency to generate self-excited vibrations, leading to instability. To address this problem, the fluid-structure coupling model of an aerostatic bearing-rotor system is established in this paper. Then a hybrid method combining the finite difference method and direct integration method, is employed to solve the bearing lubrication equation and rotor motion equation simultaneously. Furthermore, based on the orbit of rotor center,frequency spectrum diagram, Poincaré map, waterfall diagram and bifurcation diagram, the effects of rotational speed, rotor mass, orifice diameter and nominal clearance on the nonlinear dynamic behaviors of the bearing-rotor system are investigated. The results indicate that the system exhibits rich nonlinear behaviors with increasing rotational speed and rotor mass, including the occurrence of typical half-speed whirl. However, the nonlinear vibrations of the system can be restricted by selecting appropriate bearing structural parameters, providing theoretical guidance for the design of aerostatic bearing-rotor systems.

Debiasing Judgements Using a Distributed Cognition Approach: A Scoping Review of Technological Strategies.

To review and synthesise research on technological debiasing strategies across domains, present a novel distributed cognition-based classification system, and discuss theoretical implications for the field. Distributed cognition theory is valuable for understanding and mitigating cognitive biases in high-stakes settings where sensemaking and problem-solving are contingent upon information representations and flows in the decision environment. Shifting the focus of debiasing from individuals to systems, technological debiasing strategies involve designing system components to minimise the negative impacts of cognitive bias on performance. To integrate these strategies into real-world practices effectively, it is imperative to clarify the current state of evidence and types of strategies utilised. We conducted systematic searches across six databases. Following screening and data charting, identified strategies were classified into (i) group composition and structure, (ii) information design and (iii) procedural debiasing, based on distributed cognition principles, and cognitive biases, classified into eight categories. Eighty articles met the inclusion criteria, addressing 100 debiasing investigations and 91 cognitive biases. A majority (80%) of the identified debiasing strategies were reportedly effective, whereas fourteen were ineffective and six were partially effective. Information design strategies were studied most, followed by procedural debiasing, and group structure and composition. Gaps and directions for future work are discussed. Through the lens of distributed cognition theory, technological debiasing represents a reconceptualisation of cognitive bias mitigation, showing promise for real-world application. The study results and debiasing classification presented can inform the design of high-stakes work systems to support cognition and minimise judgement errors.

Numerical Investigation of Two-Phase Shock Waves in CO2 Flows Using a Modified Hertz–Knudsen Model

Abstract Understanding the complex behavior of two-phase shocks in CO2 flows is essential for a variety of applications, including carbon capture and storage () and transcritical refrigeration cycles. This study presents a comprehensive numerical investigation of two-phase shock waves using the multispecies user-defined real gas model in Ansys Fluent. The simulations are performed for de-Laval nozzles, exploring the two-phase shock features for three-dimensional (3D), two-dimensional (2D), and two-dimensional axisymmetric geometries. The nonequilibrium condensation, subsequent evaporation, and denucleation occurring across the shock are modeled through a set of user-defined scalar transport equations implemented within Ansys Fluent. The two-phase computational fluid dynamics (CFD) simulations are carried out in proximity to the critical point where real gas effects are relevant. The CO2 real gas properties are computed using an in-house Python code and integrated into the solver via user-defined functions as external look-up tables. This study provides valuable insights into the physical processes underlying two-phase shocks in CO2 flows and their sensitivity to geometric variations and thermodynamic conditions. The findings contribute to the development and modification of predictive models and optimized designs for systems involving two-phase CO2 flows. The results highlight the influence of geometry configurations and thermodynamic conditions on shock location and intensity, providing comparisons for shock waves occurring in two-phase flows and supercritical single-phase flows.

Generation Method for HVAC Systems Design Schemes in Office Buildings Based on Deep Graph Generative Models

The design process of heating, ventilation, and air conditioning (HVAC) systems is complex and time consuming due to the need to follow design codes. Since the design standards are not fixed, the final outcome often depends on the designer’s experience. The development of building information modeling (BIM) technology has made information throughout the building lifecycle more integrated. BIM-based forward design is now widely used, providing a data foundation for combining HVAC system design with machine learning. This paper proposes an unsupervised learning method based on deep graph generative models to uncover hidden design patterns and optimization strategies from the design results. We trained and validated four deep graph generative models—GAE, GNF, GAN, and diffusion—using HVAC system terminal pipeline layout data. Accuracy and precision metrics were used to compare the generated designs with automated forward design solutions, assessing the models’ ability to capture both local variations and broader changes in design logic. A graph-neural-network-based evaluation method was employed to measure the models’ capacity to detect changes. The results indicate that all four models achieved prediction accuracies exceeding 90% and precision rates above 75%. The models effectively captured both local modifications made by designers and global design changes, showing greater sensitivity to global layout adjustments than to local updates. When comparing the results generated by deep graph generative models and the actual design, it is obvious that the accuracy of the predictions varies significantly due to the complexity of the test buildings.

Flexural Behavior of 3D-Printed Carbon Fiber-Reinforced Nylon Lattice Beams

This study investigates the flexural behavior of 3D-printed multi-topology lattice beams, with a specific emphasis on octet and cube lattice geometries created through fused deposition modeling (FDM). The mechanical properties of these beams were evaluated through quasi-static three-point bending tests. A comparative analysis of load-carrying capacity, energy absorption, and specific energy absorption (SEA) indicates that octet lattice beams exhibit superior performance to cube lattice beams. The octet lattice beam in the triple-layer double-column (TL-DC) arrangement absorbed 14.99 J of energy, representing a 38% increase compared to the 10.86 J absorbed by the cube lattice beam in the same design. The specific energy absorption (SEA) of the octet beam was measured at 0.39 J/g, which exceeds the 0.29 J/g recorded for the cube beam. Two distinct types of deformations were identified for the struts and the beam layers. Octet struts exhibit enhanced performance in stretch-dominated zones, whereas the cube system demonstrates superior efficacy in compressive-dominated regions. The results highlight the enhanced efficacy of octet lattice structures in energy absorption and mechanical stability maintenance. The investigation of sandwich lattice topologies integrating octet and cube structures indicates that while hybrid designs may exhibit efficiency, uniform octet structures yield superior performance. This study provides valuable insights into the structural design and optimization of lattice systems for applications requiring high-energy absorption and mechanical robustness.