Engineering

Abstract: Low Earth Orbit (LEO)-based positioning, navigation, and timing (PNT) systems have attracted growing interest owing to their strong transmission power and rapid Precise Point Positioning (PPP) convergence. A key challenge in realizing such systems is constructing a pseudo noise (PN) code family large enough to accommodate hundreds of satellites while maintaining competitive correlation performance. In this study, we propose the Concatenated Weil (C.W.) family, an extended Weil construction that concatenates two Weil sequences whose prime periods sum to the target code length, motivated by the Goldbach conjecture. A two-stage search---auto-correlation screening followed by cross-correlation screening---identifies 608 candidate codes satisfying the correlation thresholds of established modernized Radio Navigation Satellite System (RNSS) families. A subsequent spectral refinement based on the minimum-to-average Power Spectral Density (PSD) ratio removes codes with deep spectral nulls, yielding a final family of 588 balanced codes. Benchmarking against modernized RNSS PN families demonstrates that the proposed family achieves the largest family size while maintaining comparable correlation performance, thereby providing a viable PN solution for large-scale LEO-PNT constellations.

Abstract: Long-term disposal and management of nuclear waste is one of the major hurdles for nuclear energy. Deep geological disposal, an idea originating in the 1970s, is currently the preferred path being followed in many countries. However, acceptance of this approach is hindered by societal concerns around the safety of the “one-million years” geological disposal and passing the waste burden to future generations. iMAGINE, an integrated nuclear system based on molten salt fast reactor technology with self-sustained iso-breeding, online clean-up and reverse reprocessing, has been proposed as an innovative way to eliminate the demand for a long-term high-level waste disposal. In this work, we investigate the use of iMAGINE as a technological approach for reimagining high-level nuclear waste management by overcoming the challenges of classical partitioning and transmutation (P&T). After discussing the current status and limitations of P&T along with an overview of the nuclear waste classification and management framework existing in major nuclear power producing countries, we demonstrate the potential impact of iMAGINE in simplifying the disposal of high-level waste. The results indicate that among the key long-lived radionuclides, many lie well below the criteria for requiring deep geological disposal. Besides Finland, India and Russia where most (or all) of the important long-lived fission products exceed current high-level waste thresholds, only two to three fission products (generally with half-lives from 30 to 100 years) exceed the national limits in Canada, China, France, Germany, Japan, and South Korea, while concrete conclusions can’t be drawn for the UK and US based on available information. The results presented here do not aim to make inflated claims but should be seen as the scientific basis for deeper discussions amongst all nuclear waste disposal stakeholders to explore a novel technological solution for rethinking high-level waste management and possibly eliminating the need for a “one-million years” geological disposal.

Abstract: Magnesium hydroxide is attracting growing interest as a versatile, halogen free flame retardant, and this review surveys its production routes, structure–property relationships and use in polymer systems from commodity polyolefins to advanced bio based materials. Industrial Mg(OH)₂ is still predominantly obtained from mining or hydration of MgO, but increasing attention is being devoted to recovery from seawater and saltwork brines, where precipitation from Mg²⁺ rich streams followed by controlled rehydration or direct precipitation yields fine, high purity powders suitable for flame retardant use and simultaneously valorizes saline wastes. In parallel, hydrothermal synthesis has been extensively explored to tailor particle size and morphology by adjusting precursor, solvent, temperature and time, enabling high surface area Mg(OH)₂ or MgO with narrow size distributions that are attractive for high performance composites also evaluated via ball milling crushing and refining. More recently, process intensification strategies such as microwaves and ultrasounds have been proposed to shorten reaction times, lower temperatures and better control nucleation and growth, opening paths toward energy efficient production of structured Mg(OH)₂ from both conventional and brine derived precursors. The second part of the review analyzes how the intrinsic endothermic decomposition and basic character of Mg(OH)₂ can be utilized across a broad range of polymer matrices and how surface functionalization strategies extend its applicability. In addition to “as received” powders, stearic acid and other fatty acids, metal soaps and various organic coupling agents are widely used to render the surface more hydrophobic, enhance dispersion and interfacial adhesion, and in some cases introduce additional char forming or barrier functionality. On the application side, the review compiles and compares fire and mechanical data for Mg(OH)₂ containing, polyolefins (HDPE, LLDPE, PP and EVA) used in cables and building products expandable polymers and foams, bio polymers such as PLA and PBS and elastomers with emphasis on the balance between loading level, processability, flame performance and mechanical integrity. By integrating advances in sustainable feedstocks, controlled synthesis and surface engineering with the rapidly expanding application space, this review aims to provide a comprehensive framework for designing next generation Mg(OH)₂ based flame retardant systems for both conventional and emerging polymer technologies.

Abstract: Previous studies by the authors and others have shown that ultra-high performance concrete (UHPC) is an ideal printing material for 3D concrete printing (3DCP). However, its high carbon emissions may limit its application in 3DCP. As a solution, this study reports the development of a 3D-printed low-carbon UHPC using limestone calcined clay cement (LC3), denoted as 3DP-LC3-UHPC. The fresh and hardened properties of 3DP-LC3-UHPC were evaluated and compared with those of conventional 3D-printed UHPC using Portland cement (3DP-PC-UHPC). Conventionally mold-cast mixtures were also prepared for comparison. Fresh properties included flowability, setting time, rheological properties, extrudability, and buildability. Hardened properties included compressive strength and flexural performance in different directions. The effect of two curing regimes (heat- and ambient temperature-curing) on hardened properties was also investigated. The results showed that 3DP-LC3-UHPC possessed higher dynamic yield stress, plastic viscosity, and thixotropy recovery, and exhibited satisfactory extrudability and buildability. The 3DP-LC3-UHPC achieved compressive strengths of 130.4-169.4 MPa and flexural strengths of 26.9-30.6 MPa, depending on the testing direction. Environmental and cost assessments confirmed that 3DP-LC3-UHPC reduces carbon dioxide emissions, embodied energy, and cost by about 25%, 10%, and 9%, respectively, compared to 3DP-PC-UHPC. Overall, the findings demonstrate that 3DP-LC3-UHPC is a sustainable and cost-effective alternative to conventional 3DP-PC-UHPC.

Abstract: In this paper, we present an optimized driving strategy for a dual RF input envelope tracking power amplifier (ET PA) exploiting load modulation. The dual-input architecture enables dynamic load modulation (LM), allowing real-time adjustment of the load impedance to enhance performance over the signal dynamics typical of digital modulation schemes. The proposed approach considers a GaN HEMT-based LM-ET PA characterized under pulsed excitation across multiple amplitude and phase conditions of the load modulation control. Optimizing the control parameters yields a suitable shaping function that extends conventional ET supply modulation to include amplitude and phase control of the auxiliary amplifier, thereby improving the efficiency, output power, and linearity of the main amplifier. Experimental data demonstrate that the proposed dual RF input GaN-based LM-ET PA at 3.6 GHz outperforms a conventional ET PA in both efficiency and linearity when tested with high peak-to-average ratio signals.

Abstract: In the context of the transformation of urban construction from incremental expansion to inventory renewal, the reuse of industrial remnants has gradually shifted from the issue of spatial transformation to that of scene construction. Taking Tianjin as the research object, based on the scene theory framework, by comprehensively applying kernel density spatial analysis and network comment text mining methods, the research is conducted from two levels: spatial structure and public perception. The study found that the three main models of industrial park, museum, and commercial area have significant differences in spatial distribution and accessibility conditions; the network comment analysis further indicates that public perception shows structural differences in the dimensions of neighborhood environment, appropriateness of objects, activities, and values, which essentially stem from the transmission effect of spatial structure on behavior and experience, and then through influencing activity frequency and population structure, shaping differentiated scenes such as "creative life", "consumption leisure", and "historical culture". At the same time, different models generally have problems such as superficial cultural expression, entertainment-oriented experience, and insufficient value recognition. Based on this, a scenario-based renewal strategy oriented towards mechanism optimization is proposed, providing theoretical basis and practical paths for the spatial translation and cultural regeneration of industrial remnants.

Abstract: The downtime and maintenance associated with the failure of a wind turbine gearbox can be significant, leading to high repair costs. Currently, when warning signals are received through the condition-monitoring system, wind farms typically perform maintenance on the gearbox to ensure continued operation. However, reducing power not only leads to an imbalance between the life of the transmission system and the amount of electricity generated, but also reduces revenue; Moreover, it faces the dilemma of being unable to accurately grasp the health status of the gear transmission system, which increases the difficulty of life extension. To address the above issues, this study proposes a gearbox life extension strategy based on wind turbine control methods. This approach breaks through the limitation of traditional methods where damage assessment is decoupled from operating conditions, and transforms the previous research status where life and power generation optimization were treated as separate entities. And the effectiveness of the life extension strategy was validated using actual operating data from China. The results demonstrated that the proposed strategy could extend the gearbox's life and enhance total power generation.

Abstract: Since tires from end-of-life vehicles are not entirely biodegradable and pose a serious environmental problem, their disposal has grown to be a significant global environmental concern. One technique to decrease these environmental issues is incorporating waste rubber to make sustainable green concrete. This study examined the usage of waste supplementary cementitious materials (SCMs) such as fly ash (FA), metakaolin (MK), marble powder (MP), slag (SL), and silica fume (SF) for surface precoating of crumb rubber (CR) to improve the mechanical properties of the produced crumb rubber concrete (CRC) by strengthening the bond between CR and cement paste in the Interfacial Transition Zone (ITZ). The CR replaced (0, 15%, and 25%) of sand by weight in the preparation of CRC mixtures. A total of eleven CRC mixes were cast to investigate the fresh properties, compressive strength, and splitting tensile strength. In addition, the compressive stress-strain curve was investigated, and peak stress, peak strain, energy absorption, toughness, and modulus of elasticity have been evaluated. The outcomes showed that pre-coating CR using FA, followed by MK, has the maximum effect in increasing the CRC compressive performance. The 25% substitution of sand with FA-treated CR increased compressive strength after 28 days, splitting tensile strength, peak stress, toughness, and modulus of elasticity by 34.7%, 23.7%, 34.8%, 26.1%, and 25.2%, respectively, in comparison to the same percentage of untreated CR. The proposed approach demonstrates a viable pathway for integrating waste materials and SCM-based technologies to develop high-performance, sustainable cementitious composites.

Abstract: Construction management, from the contractor's perspective, is led by the Construc-tion Manager (CM). The work motivation and leadership style of the CM are critical variables for the successful execution of construction projects. Scientific literature identifies participative leadership as the most effective style for mitigating conflicts among various stakeholders. However, analyzing the specific variables that influence a CM's conflict resolution capacity remains an underexplored area. Furthermore, while the CM must act as a leader for their team (subcontractors, suppliers, etc.), they remain accountable to the contractor’s senior management. Therefore, this study aims to ana-lyze the mediating role of CM motivation in the relationship between leadership and conflict resolution capacity using Partial Least Squares Structural Equation Modeling (PLS-SEM). This research contributes to identifying the factors that influence the CM’s conflict resolution capacity during the execution phase, thereby enhancing best prac-tices in knowledge management within the construction industry.

Abstract: Sensors are a fundamental component of Structural Health Monitoring (SHM) systems. Among the different types of sensors, piezoelectric (PZT) sensors are widely used due to their desirable properties, such as dual actuation–sensing capability, high sensitivity, low cost, and suitability for real-time monitoring. In addition to proper sensors, SHM also requires effective signal processing techniques for interpreting the data acquired by the sensors. Recently, the rapid advancement of Artificial Intelligence (AI) has significantly improved the automated SHM of structures and demonstrated how effective SHM can become when combined with artificial intelligence. Thus, the use of appropriate sensors, effective signal processing techniques, and AI can significantly enhance SHM performance. Guided by these developments, this paper presents a critical review of signal processing and machine learning approaches in PZT-based SHM systems, with emphasis on engineering structures. The fundamental principles of PZT sensing and wave propagation are first outlined. Next, signal processing techniques and their importance in SHM are discussed with a focus on recent advancements in the use of AI in PZT-based SHM. This work also discusses the Hybrid frameworks that integrate signal processing with data-driven AI models which are promising directions for improving robustness and accuracy of SHM. Finally, existing key challenges such as environmental variability, sensor degradation, data scarcity, and model generalization are discussed, along with future directions including physics-informed learning, transfer learning, explainable AI, and baseline-free SHM systems.

Abstract: This study explores the development of lattice-based panels for satellite applications using Direct Metal Laser Sintering and aimed to optimize lightweight, high-strength structures suitable for CubeSat deployment. Three lattice configurations namely Body-Centered Cubic, Octet, and Gyroid were evaluated. While Gyroid lattices exhibited the highest compressive strength at 13,825.8 N, the BCC lattice was selected for the final design due to superior manufacturability and weight reduction potential. The final optimized panel weighed 185.7 g, achieving an 11.4% reduction from the initial rib-type design and a 65.2% reduction from a solid panel. Finite Element Analysis and mechanical testing confirmed that the fabricated structures met the necessary mechanical requirements for aerospace launch conditions.

Abstract: The increasing penetration of distributed renewable energy resources and electric vehicles has transformed microgrids into complex multi-prosumer systems that require coordinated control. Traditional centralized and local independent control strategies fail to exploit distributed flexibility and often lead to sub-optimal renewable utilization and inefficient energy management. This paper proposes a new method for coordinating these multi-prosumer microgrids using a hybrid coordination framework that utilizes Federated Learning for forecasting, game theory for energy trading, and blockchain for transaction recording through a decentralized network of peer to peer transactions between prosumers. Additionally, using the principles of model predictive control the battery algorithm was trained to make optimal decisions about present and probable future conditions of each microgrid node. By conducting simulations on heterogeneous networks of multi-prosumer microgrids, the system demonstrated a significant increase in renewable energy utilization by up to 91.2% and provided for greater coordination across three (3) microgrids through energy trading, fairness, and energy efficiency while also maintaining adequate levels of voltage regulation and power quality. In comparison, the baseline controller only achieved a lower operational cost. The results revealed essential trade-offs between local optimality and system coordination leading to the design of next generation decentralized microgrids.

Abstract: The fast growth of wireless communication systems and the growing need for very high data rates have been the driving force behind the creation of sixth-generation (6G) technologies that operate in the terahertz (THz) frequency region. This research represents the design and analysis of a small compact microstrip patch antenna that works in the terahertz (THz) frequency range for 6G cellular connectivity. The Rogers RT5880 substrate and annealed copper are used in the design of the suggested antenna, which aims for a 593 GHz resonance frequency. A progressive design technique that incorporates slotting and geometric optimization has been used to develop a castle shaped antenna which improve impedance matching and bandwidth to overcome the inherent constraints of traditional microstrip antennas. Excellent impedance matching is shown by the final design's near-ideal voltage standing wave ratio (VSWR) and return loss (S11) of –48.76 dB. It achieves a broad impedance bandwidth of 154.88 GHz, which far outperforms many current systems. The antenna exhibits consistent radiation characteristics in the broadside direction, a gain of 8.005 dBi, a directivity of 8.727 dBi, and an efficiency of around 91.73%. The proposed design performs very well in terms of bandwidth and efficiency, while also preserving compact dimensions and structural simplicity, as shown by a comparative comparison with most current literature. These results validate the suitability of the proposed antenna for high-speed, short-range THz communication systems in future 6G networks.

Abstract: In recent years, the rapid expansion of low-temperature facilities—such as cold storage and indoor ice and snow venues—has underscored their pronounced vulnerability to fire, as evidenced by multiple severe incidents. Due to their distinct environmental conditions, existing theoretical frameworks, technical approaches, and standards exhibit limited applicability. Consequently, the fire risk characteristics of such facilities remain insufficiently defined, and systematic methods for hazard identification and assessment are lacking. This study conducts a detailed analysis of fire incident data from representative low-temperature facilities to identify the fire risks characteristics across all lifecycle stages, including construction, renovation and expansion, operation, maintenance, and demolition. An integrated framework combining the WBS/RBS matrix and CN methods is then proposed to establish a structured methodology for full lifecycle fire hazard identification and classification. The results address critical gaps, including the absence of clearly defined lifecycle fire risk profiles and a robust scientific basis for hazard identification, and provide a technical foundation for lifecycle fire risk management in low-temperature facilities.

Abstract: This work introduces a compact multi-resonant metamaterial absorber designed to achieve efficient electromagnetic absorption over several microwave frequency bands. The proposed configuration is based on a hybrid resonator arrangement that promotes strong electromagnetic interaction and enables multiple resonant modes within a single unit cell. Consequently, six distinct absorption peaks are obtained at 2.4, 5.21, 6.88, 9.77, 12.61, and 14.99~GHz, covering S-, C-, X-, and Ku-band applications. The absorber exhibits high absorption performance, exceeding 97\% across most operating frequencies, which indicates effective impedance matching with free space and efficient energy dissipation mechanisms. The absorption characteristics are further examined through surface current distributions, electric field confinement, and effective medium analysis, demonstrating that the multi-band response originates from the interaction of multiple resonant elements and intrinsic material losses. Moreover, the proposed structure maintains stable performance for different polarization angles and oblique wave incidence, confirming its polarization-insensitive and angularly stable behavior. To validate the design, a prototype is fabricated and experimentally characterized using a free-space measurement setup, showing close agreement with the simulated results. The compact geometry, low fabrication cost, and scalability of the proposed absorber make it a promising candidate for applications such as electromagnetic interference mitigation, radar cross-section reduction, and modern wireless communication systems.

Abstract: The proliferation of high-speed railway (HSR) networks necessitates frequent construction activities adjacent to operational lines, posing significant risks to the structural integrity and safety of existing infrastructure. This study addresses the critical need for a comprehensive framework to assess and monitor the deformation of HSR piers throughout the entire construction process of a new, nearby bridge, which includes the cumulative effects of both substructure and superstructure construction. A hybrid methodology integrating quantitative risk assessment and real-time, non-contact monitoring was developed and implemented. A risk evaluation model was established using the Analytic Hierarchy Process (AHP) to structure the problem, combined with Triangular Fuzzy Numbers to handle the inherent uncertainties in expert judgments. The Fuzzy Comprehensive Evaluation method was then employed to quantify the risk levels of various construction stages. Concurrently, a vision-based monitoring system utilizing Digital Image Correlation (DIC) technology was deployed to capture the three-dimensional deformation of adjacent HSR piers with high precision and frequency. The case study, focusing on the construction of a new bridge crossing the operational Beijing-Shanghai HSR, demonstrated the application of this framework. The risk assessment model identified the pile cap and pier construction phase as the highest-risk stage, with a risk weight of 0.311. The DIC monitoring system, validated against total station measurements with a relative error of less than 5%, recorded the cumulative pier deformations throughout 31 distinct construction stages. The maximum recorded deformations in the transverse, longitudinal, and vertical directions were all maintained within the early warning threshold of ±1.2 mm stipulated by railway regulations. The study confirms that the integrated AHP-Fuzzy and DIC framework provides a robust paradigm for proactive risk management in adjacent-line construction projects. The risk model accurately predicted the most critical construction phase, and the DIC system offered a reliable and efficient solution for real-time safety assurance. The findings validate that with appropriate risk-informed monitoring, the impact of new bridge construction on existing HSR infrastructure can be effectively controlled within safe limits, offering a valuable reference for similar engineering projects globally.

Abstract: We present TADI (Tool-Augmented Drilling Intelligence), an agentic AI system that transforms drilling operational data into evidence-based analytical intelligence. Applied to the Equinor Volve Field dataset, TADI integrates 1,759 daily drilling reports, selected WITSML real-time objects, 15,634 production records, formation tops, and perforations into a dual-store architecture: DuckDB for structured queries over 12 tables with 65,447 rows, and ChromaDB for semantic search over 36,709 embedded documents. Twelve domain-specialized tools, orchestrated by a large language model via iterative function calling, support multi-step evidence gathering that cross-references structured drilling measurements with daily report narratives. The system parses all 1,759 DDR XML files with zero errors, handles three incompatible well naming conventions, and is backed by 95 automated tests plus a 130-question stress-question taxonomy spanning six operational categories. We formalize the agent's behavior as a sequential tool-selection problem and propose the Evidence Grounding Score (EGS) as a simple grounding-compliance proxy based on measurements, attributed DDR quotations, and required answer sections. The complete 6,084-line, framework-free implementation is reproducible given the public Volve download and an API key, and the case studies and qualitative ablation analysis suggest that domain-specialized tool design, rather than model scale alone, is the primary driver of analytical quality in technical operations.

Abstract: Rapid urbanization and intensifying climate risks are placing unprecedented pressure on cities to transition toward sustainable and resilient models. Achieving Sustainable Development Goals (SDGs) 11 (Sustainable Cities and Communities) and 13 (Climate Action) requires intelligent systems capable of interpreting complex urban dynamics and enabling proactive, adaptive decision-making. This paper presents a PRISMA-guided rapid review examining the role of Agentic Artificial Intelligence (AAI)–autonomous, goal-directed systems with multi-step reasoning, tool use, and multi-agent coordination–in advancing urban sustainability and climate resilience. Studies were required to exhibit at least two attributes: autonomous decision-making, multi-step planning, tool use or environmental interaction, and multi-agent coordination. From 920 records, 70 peer-reviewed studies were synthesized, covering smart mobility, infrastructure planning, waste management, emergency response, climate monitoring, emissions tracking, renewable energy forecasting, and multi-hazard early warning systems. Results show that despite rapid progress, AAI applications remain fragmented and domain-specific. To address this, a unified Agentic AI–Digital Twin framework is proposed, integrating real-time sensing, urban–climate co-simulation, multi-agent coordination, and adaptive decision intelligence. A Pareto-based optimization approach balances competing sustainability goals. Key challenges in interoperability, data governance, ethics, and scalability are identified, alongside a research roadmap for integrated intelligent urban ecosystems.

Abstract: The purpose of this paper is to investigate, collect, and analyze the different technologies that are being integrated into vehicle automation systems. These technologies can range from LIDAR/RADAR sensors, voice recognition, and AI models. With the continued push for the development of AI and au- tonomous vehicles in both the economy and among the populace, designers and engineers are more incentivized than ever to break new ground. As technology in the industry changes, so must the priorities of its developers. First, data and analysis on the safety of autonomous vehicles will be provided, providing context for the importance of the topic. Second, an overview of the research and development of the technology used to address the previous concerns is provided. Third, an examination of the successes and failures of the technology in regard to those concerns will be made. Lastly, this paper will explore the emerging breakthroughs and future advancements that will drive the mass adoption of autonomous vehicles, specifically those that can be scaled up to civilian automobiles.

Abstract: This paper describes the design and implementation of PolyUAnalog, a modular and open-source polyphonic analog synthesizer. The architecture utilizes the AS3397 analog voice chip, with each voice managed by a dedicated RP2040 microcontroller. System coordination, including MIDI processing and voice allocation, is handled by a central conductor board communicating over an I²C bus. Technical implementation details and associated measurements are provided regarding real-time DCO pitch stabilization via a PID feedback loop and the generation of high-resolution control voltages using filtered Pulse Width Modulation (PWM). The complete hardware schematics and C++ software stack are documented to facilitate replication, modification, and further development within the electronic musical instrument community.