Search Results (60)

Steel structures that support machines and industrial process installations should ideally be flexible, adaptable, and easily reconfigurable. However, in current practice, new profiles are frequently used and discarded whenever layout modifications are required, leading to considerable material waste, increased costs, and environmental burdens. Such practices conflict with the principles of the circular economy, in which reusability is preferable to recycling. This paper presents a life cycle sustainability assessment (life cycle cost, LCC, and life cycle assessment, LCA) applied to six structural typologies: (a) welded IPE profiles, (b) bolted IPE profiles, (c) welded tubular profiles, (d) bolted tubular profiles, (e) clamped IPE profiles with demountable joints, and (f) flanged tubular profiles with demountable joints. The assessment integrates structural calculations with an updatable database of costs, operation times, and service lives, providing a systematic framework for evaluating both economic and environmental performance in medium-load industrial structures (0.5–9.8 kN/m²). Application to nine representative case studies demonstrated that demountable clamped and flanged joints become economically competitive after three life cycles, and after only two life cycles under high-load conditions (9.8 kN/m²). The findings indicate relative cost savings of up to 75% in optimized configurations and carbon-footprint reductions of approximately 50% after three cycles. These results provide quantitative evidence of the long-term advantages of demountable and reconfigurable steel structures. Their capacity for repeated reuse without loss of performance supports sustainable design strategies, reduces environmental impacts, and advances circular economy principles, making them an attractive option for modern industrial facilities subject to frequent modifications. Full article

This study proposes a multi-stage collaborative design framework integrating sensitivity analysis, response surface methodology (RSM), and topology optimization for synergistic lightweighting and performance enhancement of micromanufacturing systems using ultra-precision computer numerical control (CNC) machine tools. Overall sensitivity analysis identified the base and column as stiffness-critical components, while the spindle box exhibited significant weight-reduction potential. Using spindle box wall and bottom thickness as variables, RSM models for mass and stress were constructed. Multi-objective optimization via a genetic clustering algorithm achieved a 57.2% (590 kg) weight reduction under stress constraints (<45 MPa). Subsequent variable-density topology optimization (SIMP model) reconfigured the rib layouts of the base and column under volume constraints, reducing their weights by 38.5% (2844 kg) and 41.5% (1292 kg), respectively. Whole-machine validation showed that maximum static deformation decreased from 0.17 mm to 0.09 mm, maximum stress reduced from 58 MPa to 35 MPa, and first-order natural frequency increased from 50.68 Hz to 84.08 Hz, significantly enhancing dynamic stiffness. Cumulative weight reduction exceeded 3000 kg, achieving a balance between lightweighting and static/dynamic performance improvement. This work provides an effective engineering pathway for a structural design of high-end micromanufacturing systems. Full article

Amid expanding higher education and enhancing spatial quality, modern university campuses face challenges including inefficient space utilization and a disconnect from human-centered design. We developed a coupled model that integrates the analytic hierarchy process (AHP) with space syntax theory to identify and address functional fragmentation, limited accessibility, and diminished spatial vitality. The Delphi method was employed to determine weights on visual and traffic influence factors. Through spatial quantitative analysis using Depthmap software, we estimated spatial-efficiency discrepancies across 11 component types, including school gates, teaching buildings, and libraries. A case study was conducted at a university located in the hilly terrain of Conghua District, Guangzhou, China which revealed significant contradictions between subjective evaluations and objective data at components, such as the administrative building and gymnasium. These contradictions led to poor visual permeability, excessive path redundancy, and imbalanced functional layouts. Based on the results of this study, targeted optimization strategies were proposed, including permeable interface designs, path network reconfiguration, and the implementation of dynamic functional modules. These interventions were tailored to accommodate the humid subtropical climate, balancing shading, ventilation, and visual transparency. In this study, methodological support for the renovation of existing campus infrastructure was provided as theoretical and technical references for space renewal in tropical and subtropical academic environments and the enhancement of the quality and resilience of campus spaces. The results also broadened the application of interdisciplinary methods in university planning. Full article

This study presents a high-fidelity digital twin (DT) framework designed to evaluate and improve vertiport operations for Advanced Air Mobility (AAM). By integrating Unreal Engine, AirSim, and Cesium, the framework enables real-time simulation of Unmanned Aerial Vehicles (UAVs), including unmanned electric vertical take-off and landing (eVTOL) operations under nominal and disrupted conditions, such as adverse weather and engine failures. The DT supports interactive visualisation and risk-free analysis of decision-making protocols, vertiport layouts, and UAV handling strategies across multi-scenarios. To validate system realism, mixed-reality experiments involving physical UAVs, acting as surrogates for eVTOL platforms, demonstrate consistency between simulations and real-world flight behaviours. These UAV-based tests confirm the applicability of the DT environment to AAM. Intelligent algorithms detect Final Approach and Take-Off (FATO) areas and adjust flight paths for seamless take-off and landing. Live environmental data are incorporated for dynamic risk assessment and operational adjustment. A structured capacity evaluation method is proposed, modelling constraints including turnaround time, infrastructure limits, charging requirements, and emergency delays. Mitigation strategies, such as ultra-fast charging and reconfiguring the layout, are introduced to restore throughput. This DT provides a scalable, drone-integrated, and data-driven foundation for vertiport optimisation and regulatory planning, supporting safe and resilient integration into the AAM ecosystem. Full article

Well pattern infill adjustment combined with chemical flooding is an important technical approach for significantly improving oil recovery in high-water-cut reservoirs after polymer flooding. Current research predominantly focuses on the evaluation of oil displacement potential through either well pattern infilling or chemical flooding alone, while systematic experimental investigations and mechanism studies on the synergistic effect of well pattern infilling and chemical flooding remain insufficient. To overcome the limitations of single adjustment measures, this study proposes a synergistic improved oil recovery (IOR) strategy integrating branched preformed particle gel (B-PPG) heterogeneous phase composite flooding (HPCF) with well pattern infill adjustment. Two-dimensional visual physical simulation experiments are conducted to evaluate the synergistic oil displacement effects of different displacement systems and well pattern adjustment strategies after polymer flooding and to elucidate the synergistic IOR mechanisms under the coupling of dense well patterns and chemical flooding. The experimental results demonstrate that, under well pattern infill conditions, the HPCF system exhibits significant water control and oil enhancement effects during the chemical flooding stage, achieving a 29.95% increase in stage recovery compared to the water flooding stage. The system effectively blocks high-permeability channels while enhancing displacement in low-permeability zones through a coupling effect, thereby significantly expanding the displacement sweep volume, improving displacement uniformity, and efficiently mobilizing the remaining oil in low-permeability and residual oil-rich areas. Meanwhile, well pattern infill adjustment optimizes the injection–production well pattern layout, shortens the inter-well spacing, and effectively increases the displacement pressure differential between injection and production wells. This induces disturbances and reconfiguration of the streamline field, disrupts the original high-permeability channel-dominated flow regime, further expands the sweep range of the remaining oil, and substantially improves overall oil recovery. The findings of this study enrich and advance the theoretical framework of water control and potential tapping, as well as synergistic IOR mechanisms, in high-water-cut and strongly heterogeneous reservoirs, providing a reliable theoretical and technical basis for the efficient development and remaining oil recovery in such reservoirs during the late production stage. Full article

This study presents a multi-objective optimization framework for enhancing environmental performance in high-density residential complexes, addressing the critical balance between sunlight access, visual openness, and ground-level privacy. Applied to Helio City Phase 3 in Seoul—a challenging case with 2026 units surrounded by adjacent blocks—the research developed a sequential three-stage optimization strategy using computational design tools. The methodology employs Ladybug simulations for solar analysis, Galapagos genetic algorithms for view optimization, and parametric modeling for privacy assessment. Through grid-based layout reconfiguration, tower form modulation, and strategic conversion of vulnerable ground-floor units to public spaces, the optimized design achieved 100% sunlight standard compliance (improving from 64.31%), increased average visual openness to 66.31% (from 39.48%), and eliminated all privacy conflicts while adding 30 residential units. These results demonstrate that computational optimization can significantly surpass conventional planning approaches in addressing complex environmental trade-offs. The framework provides a replicable methodology for performance-driven residential design, offering quantitative tools for achieving regulatory compliance while enhancing residents’ experiential comfort in dense urban environments. Full article

This paper proposes a machine learning (ML)-based energy optimization framework for 5G New Radio (5G NR) utilizing a Classification and Regression Tree (CART) algorithm. The methodology implements dynamic cell resource reconfiguration through predictive load forecasting, achieving a 42.3% reduction in energy consumption, while maintaining QoS parameters within 3GPP-specified thresholds. A case study with a network layout made up of an inter-band NR-NR Dual Connectivity (DC) was simulated to quantitatively validate our model. Full article

This paper describes a compact multi-port sub-6 GHz multiple-input multiple-output (MIMO) antenna system tailored for 5G NR mobile terminals operating in the n77 (3.3–4.2 GHz), n78 (3.3–3.8 GHz), and n79 (4.4–5.0 GHz) frequency bands. The proposed design leverages a shared coupling approach that exploits the smartphone metal frame as the radiating element, facilitating efficient integration within the spatial constraints of modern mobile devices. A two-stage method is used to mitigate the mutual coupling and correlation issues typically encountered when designing compact MIMO configurations. Initially, a four-port structure is used to evaluate broadband impedance and spatial feasibility. Based on the observed limitations in terms of isolation and the envelope correlation coefficient (ECC), the final configuration was reconfigured as an optimized two-port layout with a refined coupling geometry and effective current path control. The fabricated two-port prototype exhibited a measured voltage standing wave ratio below 3:1 across the n78 band on both ports, with the isolation levels attaining –12.4 dB and ECCs below 0.12. The radiation efficiency exceeded −6 dB across the operational band, and the radiation patterns were stable at 3.3, 3.5, and 3.8 GHz, confirming that the system was appropriate for MIMO deployment. The antenna supports asymmetric per-port efficiency targets ranging from −4.5 to −10 dB. These are the realistic layout constraints of commercial smartphones. In summary, this study shows that a metal frame integrated two-port MIMO antenna enables wideband sub-6 GHz operation by meeting the key impedance and system-level performance requirements. Our method can be used to develop a scalable platform assisting future multi-band antenna integration in mass-market 5G smartphones. Full article

With the gradual increase in the total volume of underground commerce in cities, underground commercial spaces are increasingly becoming a key carrier for breaking the constraints of land resources and reconfiguring the relationship between people and land. This paper quantifies and visualizes the layout and scale of underground commercial spaces in the central urban area of Qingdao by using kernel density, multi-distance spatial clustering, and spatial autocorrelation analysis and analyzes the influencing factors by using the geographical detector and MGWR model. The research results show that the underground commercial spaces in the central urban area present a “multi-core–multi-level” layout pattern, and high-density areas are more likely to cluster, with the most significant clustering scale being 3.39 km. Commercial supporting facilities, development of underground space, and population heat value are the core driving factors. The impact of rail transit, centrality, commercial supporting facilities, and development of underground space on the east coast urban area is much greater than that on the west and north urban areas. Finally, corresponding strategies are proposed from the perspectives of business districts, station areas, supply and demand, and planning and management to optimize the development and layout of underground commercial spaces, so as to promote the organic integration of underground commercial spaces and urban spaces. Full article

This paper presents a novel fully integrated radio frequency (RF) rectifier tailored for a wide power dynamic range (PDR) with multiband adaptability to efficiently convert AC RF power into DC power. The proposed rectifier utilizes the strength of interstage gate biasing to achieve high power conversion efficiency (PCE) across a broad range of input power levels. Through its reconfigurable mode, the circuit seamlessly transitions between a low-power path and high-power path to ensure optimal performance across a wide PDR. Simulated using CMOS 65 nm technology, the post-layout assessment reveals a peak PCE of 48.8% at 900 MHz and 46.4% at 1800 MHz, with an extensive PDR of 20 dB for PCE exceeding 20% at both frequencies. Full article

Refugee camps are typically designed as temporary sustainable settlements, prioritizing logistics over cultural considerations, which can lead to environments being misaligned with the lived experiences of displaced populations. This study addresses the challenge of traditional humanitarian camp designs that prioritize logistical efficiency over cultural and socio-cultural needs, leading to environments that do not align with the lived experiences of displaced populations. Focusing on the Zaatari Syrian Refugee Camp in Jordan, the research employs a structured questionnaire distributed among 102 households to investigate how refugees have reconfigured the camp’s original grid layout into more cohesive clustered patterns, informed by the principles of defensible space theory. Key findings reveal that refugees actively transform public courtyards into semi-private spaces, driven by cultural imperatives and safety needs. Statistical analyses confirm significant correlations between clustering behaviors and the attributes of defensible space, particularly the zones of influence and boundary demarcation, enhancing community resilience and accessibility. However, the study finds a limited predictive power overall, indicating that while these adaptations are significant, factors such as natural surveillance and territorial behavior do not exhibit strong influences on clustering dynamics. These findings have important implications for humanitarian planning and design. They highlight the necessity for more culturally sensitive and flexible approaches that prioritize refugee agencies and communal identity in camp layouts. This research advocates for a hybrid planning approach that integrates socio-cultural values, promoting resilience and quality of life among refugees. By aligning spatial designs with the social and cultural realities of refugee communities, humanitarian actors can enhance the effectiveness of their interventions, ultimately contributing to more sustainable and inclusive urban environments as part of broader goals related to urban planning and development. Future research is encouraged to explore these practices in diverse refugee contexts, providing further validation of these findings and enhancing the applicability of these design principles in global humanitarian efforts. Full article

This study introduces an optimization design method for large-scale curvature-adjustable optical mirrors, innovatively integrating parametric modeling with the optimized layout of actuators, targeting the achievement of extensive curvature adjustability and high-precision surface correction for segmented mirrors. The optimization objective is based on the surface figure residual when the curvature radius of the segmented mirror is altered by 100 mm. Through the optimization of the number, arrangement, and thickness of reinforcement ribs of the actuators on the back of the segmented mirror, a parametric model of a segmented mirror with an edge-to-edge distance of 510 mm and a radius of curvature 9100 mm is developed. Simulation outcomes reveal that a 0–15 μm variation in the actuators results in a curvature radius change of 178.45 mm in the segmented mirror, with a highly linear correlation, achieving a radius of curvature reconfiguration of the primary mirror in the optical system from 9100 mm to 9000 mm, with a residual surface figure error of less than 10 nm. The experimental results indicate that within a 0–15 μm closed-loop stroke range, the curvature radius of the segmented mirror can be adjusted by 146.89 mm, fulfilling the design objective of a lightweight mirror with a significantly adjustable curvature radius. This research is anticipated to offer technical support and serve as a reference for the assembly, adjustment, and inspection of large-aperture segmented mirrors, as well as for the curvature radius variation in multiple segmented mirrors, thereby holding substantial practical value in engineering applications. Full article

Aircraft structures consist of numerous complex components that require a high level of precision to assemble. Tooling plays a crucial role in the assembly of aircraft components, providing the functions of positioning, shape maintenance, and support to guarantee the accuracy of the product. Aiming to obtain reusable assembly tooling that can be rapidly reconfigured, this study focuses on the modular design and layout of tooling structures. The concept of functional elements for the characterization of tooling parts is proposed, and the relationship between each pair of elements is established to clarify the similarities and dependencies among various tooling structures. Based on the analysis of functional elements and their relationships, the tooling structures are divided and recombined into several modules. The detailed module designs are demonstrated by using typical structures such as platforms, columns, and locators as examples. A parametric representation of the multi-source information of tooling modules is proposed, and optimization methods for the layout and configuration of locators and platforms are developed using their parametric information. A reconfigurable tooling process integrated with a monitoring system is designed, realized, and successfully applied to the assembly of a practical type of fuselage. The results from verifying these methods’ efficiencies show that the modular design and reconfiguration planning of tooling only takes about 10 min and a few seconds, respectively, which is far less than the time consumed during traditional tooling design (from several days to weeks). The work in this study provides an engineering paradigm for the serialization and reconfiguration of assembly tooling in aviation manufacturing. Full article

Traditional industrial robots offer significant operational flexibility and adapt well to reconfigurable production systems, although they face limitations in applications demanding high motion performance and spatial positional accuracy. While novel manufacturing solutions supporting small batch productions of custom products are widely researched, they are not yet fully available at industrial level. With the aim to advance in this domain, the present work, conducted in the context of the EU project OPeraTIC, reports the development of a novel manipulator for advanced three-dimensional laser surface treatment of large industrial components. The proposed robotic platform presents a decoupled kinematic architecture, with direct drive actuation in all axes. Its open control ensures adaptability to diverse manufacturing scenarios, making it a versatile tool for modern production lines. Starting from the description of its embodiment design and mechanical layout, the paper delves into robot virtual prototyping focusing on kinematic and dynamics aspects. In particular, a detailed behavioral model covering direct and inverse kinematic calculations, also allowing the precise evaluation of all actuation forces/torques, has been developed using analytical approaches. The model is validated with a commercial solver imposing different spatial motions. The generated performance maps illustrate the robot operational capabilities across a range of work scenarios. Full article

Neural recording systems play a crucial role in comprehending the intricacies of the brain and advancing treatments for neurological disorders. Within these systems, the analog-to-digital converter (ADC) serves as a fundamental component, converting the electrical signals from the brain into digital data that can be further processed and analyzed by computing units. This research introduces a novel nonlinear ADC designed specifically for spike sorting in biomedical applications. Employing MOSFET varactors and voltage-controlled oscillators (VCOs), this ADC exploits the nonlinear capacitance properties of MOSFET varactors, achieving a parabolic quantization function that digitizes the noise with low resolution and the spikes with high resolution, effectively suppressing the background noise present in biomedical signals. This research aims to develop a reconfigurable, nonlinear voltage-controlled oscillator (VCO)-based ADC, specifically designed for implantable neural recording systems used in neuroprosthetics and brain–machine interfaces. The proposed design enhances the signal-to-noise ratio and reduces power consumption, making it more efficient for real-time neural data processing. By improving the performance and energy efficiency of these devices, the research contributes to the development of more reliable medical technologies for monitoring and treating neurological disorders. The quantization step of the ADC spans from 44.8 mV in the low-amplitude range to 1.4 mV in the high-amplitude range. The circuit was designed and simulated utilizing a 180 nm CMOS process; however, no physical prototype has been fabricated at this stage. Post-layout simulations confirm the expected performance. Occupying a silicon area is 0.09 mm². Operating at a sampling frequency of 16 kS/s and a supply voltage of 1 volt, this ADC consumes 62.4 µW. Full article