Abstract: Blast furnace gas (BFG) must be deeply purified when it is as fuel for combined-cycle power generation. To improve collection efficiency of the fine particulate dust in BFG by wet electrostatic precipitators (WESPs), this study implemented measures such as optimizing nozzle atomization performance and spatial distribution of droplets, along with adding chemical agglomeration agents and surfactants, These approaches pro-moted the chemical agglomeration of fine dust and enhanced dust collection efficiency. The results show that under overlapping spray conditions, the 1/8 solid cone nozzle produced the smallest droplets size with the most uniform spatial distribution, exhib-iting a d50 of 141.17 μm. When this nozzle was used in combination with guar gum (GG) as a chemical agglomerant, the d50 of BFG dust increased from 8.46 μm to 14.75 μm. The synergistic application of 5 mg/m³ sesbania gum (SBG) and 5 mg/m³ oc-tylphenol ethoxylate (OP-10) further increased the dust d50 to 19.08 μm. Using the 1/8 solid cone nozzle and with an XTG concentration of 5 mg/m³, resulted in the highest dust collection efficiency of 96.76%, while the synergistic use of SBG/OP-10 achieved an efficiency of 97.69%. This study elucidates the influence of nozzle atomization charac-teristics and spray liquid type on dust agglomeration and collection efficiency, providing both theoretical and practical foundations for the deep purification of blast furnace gas.

Abstract: Digital twins are becoming an important tool in biomedical systems. They help with real time monitoring, prediction, and control. They work well only when they can combine many types of physiological data. They must also stay closely in sync with the real system.This paper describes a digital twin framework that uses a Unified Namespace. The UNS acts as a central data hub. It collects signals from sensors, organ level models, and patient information. It keeps all data in one clear and interoperable structure. It separates data producers from data users. This makes the system easier to scale. It also supports fast data flow and constant model updates.A multiscale computational model sits at the center of the twin. It joins physiological behavior with predictive methods. It supports real time decisions in a closed loop system. A sample biomedical case shows how the UNS improves system speed, prediction quality, and control actions. The results show that UNS based digital twins can support personalized medicine. They can also improve biomedical workflows and help build advanced cyber physical healthcare systems.

Abstract: Hybrid robotic manufacturing systems integrating additive and subtractive processes enable fabrication of complex, high-value components but are typically executed sequentially, resulting in long cycle times. Concurrent execution of Directed Energy Deposition (DED) and milling promises productivity gains but introduces coupled thermal, mechanical and spatial interactions that challenge conventional process planning. This work addresses the methodological problem of planning milling operations in the presence of an ongoing DED process. The concurrent planning task is formulated as a mixed-integer, nonlinear, multi-objective optimisation problem capturing sequencing and orientation decisions, cutting parameters and temporal coupling to the deposition trajectory. A hierarchical, surrogate-assisted optimisation framework is proposed, combining unified decision-variable encoding, deterministic decoding and staged feasibility enforcement to ensure robotic executability. Disturbance mechanisms such as thermal interaction, particulate interference and pose-dependent dynamic compatibility are incorporated as modular objective abstractions, enabling systematic trade-offs between machining productivity and preservation of deposition process integrity. The proposed framework is demonstrated on a large-scale hybrid manufacturing case study with sparsely distributed machining segments, illustrating interaction between spatial sequencing, temporal feasibility and disturbance-aware optimisation under stated assumptions. The framework is methodological and provides a transferable foundation for future development and validation of disturbance-aware planning strategies for concurrent additive-subtractive manufacturing.

Abstract: Reliable and resilient communication systems are essential for first responders, enabling quick coordination and effective emergency responses. However, traditional communication networks often encounter congestion, interoperability problems, and failures during large-scale disasters. To address these challenges, specialized networks like FirstNet have been developed, leveraging advancements in LTE and 5G, as well as priority access mechanisms, to enhance reliability and coverage. This paper examines the technological advancements in first-responder communication systems, highlighting the limitations of legacy networks and the enhancements offered by modern solutions. We examine key components, including network prioritization, spectrum allocation, and integration with AI-driven traffic management. Additionally, this study assesses the role of digital twins in bolstering network resilience and fault tolerance for emergency communications. By synthesizing recent advancements, this research provides insights into future developments and policy considerations necessary to ensure a seamless and robust communication infrastructure for first responders.

Abstract: This review paper explores two primary methodologies for modeling flexible multi-body systems, namely, the Assumed Mode Method and the Lumped Pa-rameter Method. Flexible multi-body systems models, which involve small elastic deformations, are critical for simulating and optimizing the behavior of structures in various engineering applications, such as robotic arms, space structures, and rotating machinery. The Assumed Mode Method decomposes a system’s motion into rigid-body movements and elastic deformations using predefined mode shapes, providing an efficient alternative to the Finite Element Method. The Lumped Parameter Method simplifies flexible systems by modeling them as rigid segments connected by springs and dampers, which capture elasticity and damp-ing effects. This review focuses on the basic use, implementation of these two approaches. Additionally, a carne with flexible pendulum load is modeled using both approaches to demonstrate their effectiveness in capturing system dynamics.

Abstract: Growing disruptions, uncertainties, and complex risks such as pandemics, extreme weather, and geopolitical conflicts imperil the under-examined construction supply chain, a network that occupies a pivotal nexus in the broader economy. Therefore, it is vital to map its relationships and pinpoint where disruptions concentrate, and recovery can be accelerated. Guided by three research questions on network emergence, positional vulnerability, and how pressures steer technology adoption, this exploratory study maps how construction supply chain networks both create and alleviate operational strain. To address this problem, this study combines empirical, semi-structured interviews with social network analytics. Purposive and snowball sampling yield semi-structured interviews that span all major supply chain roles. Thematic coding translates reported interactions into nodes and edges of a complex network and groups challenges into thematic categories. Furthermore, degree, betweenness, and eigenvector metrics outlined structural vulnerabilities and leverage points. The results show how six main challenge categories (comprising 16 open codes) concentrate systematically at specific network positions. Relationship and contract issues accumulate at high-centrality brokers (degree centrality 0.818) while external pressures affect peripheral suppliers. Technology adoption preferences emerge from structural roles, with central coordinators seeking predictive analytics and peripheral actors prioritizing traceability systems in networks with moderate density (0.591). The research provides a replicable framework for identifying structural vulnerabilities and designing position-based interventions in construction supply chains. The network-theoretic framework opens new research directions for dynamic network analysis, multi-project supply webs, and stakeholder-centered technology integration strategies.

Abstract: Gypsum based fire protection relies on thermally activated dehydration, where chem-ically bound water is released and evaporated, producing an endothermic heat sink and delaying heat penetration through assemblies. In parallel, non-organic hydrated salts are increasingly used as flame retardant additives in gypsum-based systems to enhance heat absorption over targeted temperature ranges. Fire simulation tools and performance-based fire engineering methods require dehydration kinetics and reaction enthalpies that can be implemented as coupled thermal chemical source terms. How-ever, additive specific kinetic datasets suitable for such implementation remain limited, especially under restricted vapor exchange conditions representative of porous con-struction materials. The present study investigates the thermal decomposition behavior and dehydration kinetics of selected non-organic hydrated salts—aluminium trihydrate (ATH), magne-sium hydroxide (MDH), calcium aluminate sulphate (CAS), and magnesium sulphate heptahydrate (ESM)—commonly used as flame-retardant additives in gypsum-based construction materials. Differential scanning calorimetry (DSC) experiments were conducted at three heating rates (10, 20, and 30 K/min for MDH, CAS and ESM and 20, 40 and 60 K/min for GB-ATH) up to 600 °C using pinhole crucibles to simulate autogenous vapor pressure. Thermal analysis revealed that ATH, MDH, and CAS undergo single-step dehydration, while ESM exhibits a complex multi-step mechanism involving the formation of in-termediate meta-stable hydrates. Kinetic parameters were determined using both model-free (Starink) and model-fitting approaches. The derived activation energy profiles confirmed the single-step nature of ATH and MDH and identified CAS and ESM as multi-stage systems. All reactions were well described using the Avrami–Erofeev model, indicating nucleation-and-growth mechanisms. The extracted kinetic triplets were validated through numerical simulation, showing close agreement with experimental α(t) and dα/dt(T) data. The resulting kinetic triplets and dehydration enthalpies form a directly usable dataset for coupled heat transfer and dehydration models of gypsum-based assemblies, enabling improved parameter-ization of endothermic heat sinks and bound water release in fire safety engineering simulations.

Abstract: The Zeta-Minimizer Theorem formalizes the minimization of a phase functional derived from compressibility factor expansions and exponential resummations, yielding convergence to the Riemann zeta function ζ(s). In a symmetric measure space (Xⓜ,μⓜ,G) equipped with helical operators, constraints of rational signed cosines, positive integer representation dimensions, non-zero integer differences, and prime-modulated exponential decays ensure prime emergence as indivisible cycles in representation graphs (via Hilbert's irreducibility and Maschke's theorem). Corollaries derive stacked phases as stratified orbifolds with hyperbolic tendencies, emergent geometries as layered manifolds, bounded prime descent, dimensional resistance, and RH Theorem via spectral centering at Re(s)=1/2. Axioms abstract thermodynamic intuitions purely: Axiom I as concave entropy maximization on measures; Axiom II as spectral Gibbs minima with explicit frequency forms; Axiom III as covariance projections and flux conservation. The framework generates number-theoretic structures as shadows of optimization processes, with complex numbers/polynomials as projected artifacts and quantization implicit in multiphase triads. Applications include atomic stratification (quantized shells from phase jumps), angular momentum tensors (minimized over strata), fine structure invariant (α ̂^(-1)=4π^3+π^2+π≈137.036 from cycle sums with β=5 leaps), and covariant mappings to arbitrary variables via category theory (functors and RG universality for Gear discretization). This provides rigorous deduction for analytic number theory, algebraic geometry, and spectral theory, demoting elementary constructs to derived descriptions.

Abstract: This study evaluates the technical feasibility of deploying containerized oxy-combustion power modules with integrated CO₂ capture in remote Ecuadorian Amazon oil fields. Associated petroleum gas is conditioned with a 35 wt.% diethano-lamine (DEA) sweetening stage specifically implemented to remove H₂S and reduce acid-gas loading prior to combustion, improving fuel quality and protecting down-stream equipment while increasing methane mole fraction for combustion. System ef-ficiency is governed by stoichiometric oxygen demand, with methane requiring 2 mol O₂/mol fuel and hexane requiring 11 mol O₂/mol fuel; favoring methane-rich streams reduces ASU energy demand, enhances combustion performance, and lowers separa-tion costs. The combined oxy-combustion cycle attains a thermal efficiency of 33.10% and an exergetic efficiency of 39.98%. Major energy penalties arise from the cryogenic air separation unit and the CCS train, yet operational tuning of CO₂ recirculation and steam flow could raise thermal efficiency by up to 2%. The ASU produces oxygen at 96.67% purity with an energy consumption of 0.385 kWh/kg O₂, while the CCS achieves 99.99% CO₂ capture at 0.41 kWh/kg CO₂. Sourcing gas from three production blocks provides flexibility to accommodate supply variability. The modular 272 MW unit demonstrates viability for off-grid power supply, routine flaring reduction, and scalable acid-gas valorization in frontier oilfields.

Abstract: Underground utilities represent a critical risk factor in large-scale water infrastructure projects, particularly in dense urban environments such as Riyadh, KSA. This paper presents a comparative technical assessment of three primary methods used for subsurface utility detection and verification in a TSE (Treated Sewage Effluent) network construction project: Ground Penetrating Radar (GPR), existing as-built drawings, and site trial pit investigations. The study evaluates the accuracy, reliability, and limitations of each method, with a specific focus on deep utilities exceeding 6 meters in depth.A real project case is analyzed where GPR failed to detect an existing utility pipe at approximately 13 meters depth, resulting in a microtunneling collision. The incident is used to explore root causes, including high soil cover levels, surface reinstatement conditions, and signal attenuation mechanisms. The paper further discusses the project-level implications of relying solely on GPR and historical records without adequate trial pit verification, including time delays, cost overruns, and risk exposure in large-scale KSA infrastructure programs.The findings highlight that while GPR and as-built records are valuable planning tools, they are insufficient as standalone methods for deep utility risk management. The paper concludes with a set of practical lessons learned and recommendations for site engineers and project managers, emphasizing the need for a hybrid verification strategy that systematically integrates GPR, document review, and targeted trial pits for high-risk sections.

Abstract: To verify the harmonic amplification mechanism of wideband oscillations, this paper constructs a benchmark system. Firstly, the theoretical framework of the harmonic amplification mechanism for wideband oscillations is elaborated. Subsequently, the structure and parameters of the benchmark system are presented. Based on the s-domain nodal admittance matrix method, the resonant characteristics of the benchmark system, including resonance frequency, damping ratio, and nodal voltage mode shape, are calculated. Using electromagnetic transient simulation, the time-domain waveforms of current, voltage, and power of the benchmark system under typical operating conditions are obtained, and harmonic decomposition of these waveforms is performed. By comparing and analyzing the harmonic components of current, voltage, and active power with the resonant characteristic quantities, the harmonic amplification mechanism of wideband oscillations is verified. The applicability of analyzing the harmonic amplification effect based on the positive-sequence network model is demonstrated. It is shown that the resonance frequency, damping ratio, nodal voltage mode shape, and resonant peak voltage are four key factors determining the harmonic amplification effect. Finally, the relationship between the frequency of the oscillatory power component and the frequency of the harmonic source is revealed.

Abstract: To increase the energy efficiency of soil tillage with a disc harrow, the interaction of the working elements (discs) with the soil was studied through mathematical modeling, with the aim of finding a local optimum. This involves a systemic approach, considering the agrotechnical, agrobiological aspects and the characteristics of the soil work process, and from the point of view of engineering sciences, studying the inputs and outputs of the system (the desired final state of the soil, correlated with the initial state). The present paper deals with problems related to the disc harrow aggregate, studying the phenomena of the dynamics of the interaction between the working elements (discs) and the soil, only from the point of view of energy aspects (to work with minimal specific energy consumption, relative to the soil surface worked), the other facets being touched upon only tangentially, where necessary and possible. Knowing the initial and final state of the soil, how these changes can be achieved is defined, a state that must be maintained over a longer term, in correlation with the requirements of the plants to be cultivated, the pedo-climatic conditions, the requirements for maintaining soil fertility, and slowing down the process of soil destruction.

Abstract: Two-dimensional electron gases (2DEGs) in complex oxide heterostructures provide a powerful platform for enabling nanoscale energy-conversion mechanisms. In this work, we investigate LaAlO₃/SrTiO₃/LaTiO₃ (LAO/STO/LTO) interfaces as an engi-neered architecture for electricity generation, exploiting the combined effects of LAO-induced polar discontinuity, STO’s high-κ dielectric response, and LTO-driven electronic reconstruction. This trilayer system generates a strongly confined interfacial 2DEG with sheet densities in the 1013–1014 cm−2 range, enabling strong interaction with external electromagnetic fields and efficient charge displacement. To quantitatively capture the physics governing 2DEG formation and energy extraction, we develop a self-consistent analytical model solving the Schrödinger–Poisson equations. The SP module resolves quantum confinement, band bending, and carrier distribution at the LAO/STO/LTO interface, while the analytical engine models electromagnetic excitation (sheet charge density ns), field enhancement, and dynamic charge response across the heterostructure. This approach enables simultaneous evaluation of subband structure, interfacial potential, plasma-resonance behavior, and field-induced current genera-tion. Simulation results demonstrate that the asymmetric LAO/STO/LTO stack pro-duces a deep quantum well on the STO side, promoting strong 2DEG confinement and enhanced sensitivity to THz–IR excitation; under illumination the 2DEG exhibits res-onant carrier modulation, enhanced drift displacement, and energy-transfer pathways conducive to electricity generation. We additionally incorporate temperature depend-ence into the model and find monotonic increases in sheet charge density and conduc-tivity with temperature (measured at zero bias for 10 nm films), with LTO showing metallic-like, strongly temperature-dependent transport, STO exhibiting modest ther-mally activated behavior, and LAO remaining effectively insulating but most sensitive in relative terms—effects that alter subband occupancy, screening, and resonance con-ditions. The model clarifies how layer thickness, dielectric contrast, interface polariza-tion, and temperature jointly govern energy-conversion efficiency. Overall, the vali-dated Schrödinger–Poisson framework provides a predictive tool for optimizing oxide 2DEG power-generating structures and positions LAO/STO/LTO heterointerfaces as promising candidates for tunable, nanoscale energy-harvesting devices.

Abstract: In various countries, the shear strength design formulas for reinforced concrete beam–column joints are primarily constructed based on concrete strength, and the influence of main bars of beam is not explicitly reflected in these expressions. To address this limi-tation, this study examines the shear behavior of the joint, focusing particularly on the amount and arrangement of main bars of beam passing through the joint. Four beam-column joint specimens were tested under cyclic loading. The main variables of the specimens were the amount and arrangement of the main bars of beam. The detailed strain measurements were conducted to clarify the development of bond deterioration along the main bars and the associated internal force transfer mechanisms. The ex-perimental observations revealed significant tension-shift phenomena and progressive bond deterioration in the compression-side main bars. Variations in the amount and arrangement of main bars of beam did not significantly affect the maximum applied load. However, the indirectly evaluated joint shear force was higher in specimens with two layers in beam main bars. Force equilibrium using force components obtained by measured strain produced even larger values at greater drift angles, indicating that joint shear assessment depends strongly on the evaluation basis. A mechanics-based diag-onal strut model incorporating the internal compression field provided improved agreement with experimental results, confirming its applicability for practical design.

Abstract: In general, condition monitoring (CM) and noise, vibration and harshness (NVH) are often treated as separate disciplines, despite the fact that both rely on vibration measurements. CM relies on broadband statistical metrics such as RMS, kurtosis, and envelope analysis to detect faults. Meanwhile, NVH investigates tonal excitation mechanisms related to gear mesh frequency (GMF) and its modulation components. In this study, we investigate whether a numerical relationship can be established between classical CM indicators and physically based tonal excitation indicators derived from frequency-domain analysis. Using a controlled gearbox degradation dataset, Spearman correlation analysis was performed between broadband metrics and GMF-related tonal features, including GMF-band energy and absolute sideband energy. Results show moderate but statistically significant correlations between RMS, envelope peak amplitude, and tonal indicators, whereas kurtosis exhibits no meaningful association. Additionally, tonal amplification due to degradation is shown to be structurally localized rather than uniformly distributed across sensor locations. These findings demonstrate that broadband CM indicators partially encode tonal excitation growth, establishing a reproducible data-driven bridge between diagnostic condition monitoring and NVH excitation analysis.

Abstract: The increasing prevalence of peri-implantitis has led to a growing clinical use of implantoplasty, a procedure involving intraoral machining of the dental implant sur-face to remove biofilm. The absence of standardized clinical protocols may contribute to premature fatigue failure of dental implants. The present study aimed to determine the influence of machining depth on the cyclic mechanical behavior of dental im-plants. A total of 250 commercially pure Grade 3 titanium dental implants were dis-tributed into four groups according to machining depth: untreated (original), 0.2 mm, 0.4 mm, and 0.6 mm wall reduction. The implant system featured an internal connec-tion with a thread height of 0.4 mm. Finite element analysis was performed for each machining depth to evaluate Von Mises stress distribution and to simulate fatigue be-havior. The numerical models were validated through experimental fatigue testing using a servohydraulic MTS Bionix testing machine under ISO 14801:2016 standard conditions. Fractographic analysis was conducted by scanning electron microscopy. The results revealed that maximum Von Mises stresses were concentrated at the junc-tion between the implant thread and the implant body. The fatigue limit of the un-treated implants was approximately 400 N. Implants subjected to 0.4 mm machining exhibited a fatigue limit of 350 N, whereas lower fatigue limits were observed for 0.2 mm (290 N) and 0.6 mm (180 N) reductions. These findings demonstrate the signifi-cant mechanical effect of thread removal. At higher applied loads, fracture occurred in the coronal region of the implant, whereas at lower loads failure shifted to the im-plant–abutment connection. Finite element predictions showed high agreement with experimental results. The findings highlight a clinically relevant criterion: implanto-plasty depth should not exceed the original thread height, as excessive wall reduction markedly compromises fatigue resistance and long-term mechanical reliability.

Abstract: In the marine navigation environment, static obstacles such as shallow waters, islands, and restricted zones coexist with dynamic threats like typhoons. Rapidly planning safe, shortest routes is crucial for ensuring vessel and personnel safety while enhancing navigation efficiency. However, existing path planning algorithms face limitations when addressing dynamic threats like typhoons, struggling to achieve an effective balance between efficiency and effectiveness. To address this, this study proposes an improved Time-Dynamic Theta algorithm (TDM-Theta*) based on the Theta algorithm. By incorporating wave height as a key constraint, it comprehensively evaluates the actual impact of dynamic marine environments on routes, thereby efficiently planning safe, shortest paths that proactively avoid typhoon impacts. Through testing and analysis of eight case studies across three typical scenarios, this algorithm demonstrates high efficiency and effectiveness in planning the shortest safe routes across diverse operational environments. The research findings provide theoretical foundations and methodological support for intelligent planning of safe vessel routes.

Abstract: This paper provides a rigorous examination of eight fundamental architectural deficiencies that render the Linux kernel unsuitable for deployment in safety-critical avionics. These deficiencies include inadequate temporal determinism, the absence of physical memory isolation, driver-induced contamination of global kernel state, an excessively large and unbounded Trusted Computing Base (TCB), open and nondeterministic system semantics, insufficient inter rocess fault containment, unstable kernel behavior due to continuous patching, and a highly complex toolchain that imposes prohibitive DO-330 qualification burdens. Through a technical and standards-aligned analysis, this paper demonstrates that Linux cannot satisfy the determinism, verifiability, isolation, and lifecycle stability required for airworthiness certification, making it inherently incompatible with certifiable airborne platforms.

Abstract: This paper introduces a novel theoretical framework for classifying Autonomous Mobile Robots (AMRs) into three hierarchical layers: Perception, Cognition, and Operation. Unlike prior hardware-centric taxonomies, our approach, grounded in a structured review of seminal works, foundational methodologies, and state-of-the-art advances, explicitly integrates locomotion mechanisms (wheeled, legged), application domains (industrial, agricultural), and autonomy levels with navigation strategies. The framework unifies terrestrial navigation techniques into a cohesive taxonomy, clarifying modular boundaries and interdependencies. Serving as both a conceptual guide and educational tool, it empowers researchers to evaluate trade-offs in sensor configurations, decision-making algorithms, and trajectory execution under real-world constraints. A comparative analysis positions this framework against established navigation architectures, highlighting its role as a high-level reference design for modular implementations. By bridging theoretical principles with system optimization, the framework enhances interoperability across robotic platforms. Ultimately, this work delivers a practical design atlas, structuring the end-to-end pipeline of autonomous navigation to guide researchers and practitioners in selecting algorithms suited to their specific robotic platforms and mission requirements.

Abstract: The environmental impacts from fossil fuel use have accelerated the global transition to sustainable energy sources. Hydrogen has become a promising alternative due to its high energy density and clean combustion. However, hydrogen production streams are frequently contaminated with methane, which needs efficient, durable, and cost-effective purification technologies such as Pressure Swing Adsorption (PSA). The present study provides a comparative evaluation of biomass-derived activated carbons and a commercial activated carbon for hydrogen–methane separation. High surface-area activated carbons were synthesized from sustainable pine and birch precursors via chemical activation using potassium hydroxide (KOH, impregnation ra-tio 3:1) at 800 °C. Their adsorption performance was systematically assessed in a fixed-bed PSA system operating at pressures of 25, 35, and 50 bar, with a gas mixture of hydrogen-methane, where methane feed concentrations was ranging from 10 to 30 vol%. The biomass-derived activated carbons showed well-developed textural characteristics, with specific surface areas up to 1416 m² g⁻¹, exceeding that of the commercial reference material (1023 m² g⁻¹). This improved pore structure was reflected in their adsorption behavior at an operating pressure of 50 bar, the birch-derived carbon achieved a me-thane uptake of 10.5 mol kg⁻¹, more than twice the capacity measured for the commercial adsorbent of 5.30 mol kg⁻¹. Beyond initial adsorption capacity, the study emphasizes operational durability and reusability. Cyclic adsorption–desorption experiments, supported by Raman spectroscopy, revealed pronounced structural degradation in the commercial activated carbon under repeated operational stress, as indicated by an increase in the ID/IG ratio from 1.08 to 1.24. In contrast, the biomass-derived activated carbons preserved their morphological integrity and adsorp-tion efficiency over successive cycles. These findings demonstrate that pine- and birch-derived activated carbons are not only sustainable alternatives but also operationally stable adsorbents capable for hydrogen purification pro-cesses.