Search Results (7,106)

The photothermal effect is an important part of biological tissue optics. The reasonable use of temperature changes caused by the photothermal effect is of great value for the treatment of lesions. However, it is not easy to measure changes in light and heat temperatures in tissues experimentally. This paper combines Monte Carlo simulation and finite-element numerical calculation based on the Pennes biological tissue heat transfer equation to simulate light transmission and distributions of light and heat in biological tissues, including single-layer uniform biological tissue simulations and a classic three-layer skin optical model. Through the simulation of single-layer uniform biological tissue, the overall trend and range of biological tissue temperature change under different parameters are obtained in this work. Third, in the classic three-layer skin optical model simulation, this work combines a data-fitting method to derive a formula relating internal temperature and tissue depth to the absorption coefficient. Compared with the simulation standard results, the error of the above fitting formula is within 1.2%, and it can be applied in the field of photothermal therapy in the future to help medical workers understand the range of temperature changes in biological tissues. Full article

Fuel cell technologies are increasingly investigated as alternatives to conventional auxiliary diesel generators in order to enhance shipboard energy efficiency and reduce greenhouse gas emissions. This study presents a unified and uncertainty-driven system-level assessment of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) systems operating as auxiliary power sources on a 200 m bulk carrier. Both technologies are evaluated under identical vessel characteristics, operating profiles, auxiliary load levels (360–600 kW), and cost assumptions, and are benchmarked directly against a conventional three–diesel-generator configuration. A modular numerical framework is developed to model propulsion–auxiliary interactions for ship speeds between 10 and 14 knots. SOFC systems are assessed using grey, bio-derived, and green natural gas pathways, while PEMFC systems are examined under grey, blue, and green hydrogen supply routes. Performance indicators include annual fuel consumption, carbon dioxide (CO₂) emission reduction, net present value (NPV), internal rate of return (IRR), payback period (PBP), and marginal abatement cost (MAC). Economic uncertainty is explicitly embedded in the framework through Monte Carlo simulation, where fuel prices (±20%) and capital costs are sampled across defined ranges, generating probabilistic distributions rather than single deterministic estimates. This uncertainty-centred approach enables assessment of robustness, downside risk, and probability of profitability. Results show that replacing a single operating 600 kW diesel generator with fuel cell systems reduces auxiliary fuel energy demand by 25–35% for SOFC and approximately 15–25% for PEMFC relative to the diesel benchmark. Annual CO₂ reductions range from 1.1 to 1.3 kt for SOFC systems and 1.8–2.8 kt for PEMFC configurations. Under grey fuel pathways, median NPVs reach approximately 2–4.5 M$ for SOFC and 9–17 M$ for PEMFC as load increases, with IRRs exceeding 15% and 30%, respectively. Transitional pathways exhibit narrower margins, while renewable pathways remain more sensitive to fuel price variability. The findings demonstrate that fuel pathway cost dominates lifecycle outcomes under uncertainty and that hydrogen-based PEMFC systems exhibit the strongest economic resilience within the examined market ranges. The framework provides structured, uncertainty-aware decision support and establishes a foundation for integration into model-based systems engineering (MBSE) environments for early stage ship energy system design. Full article

This paper studies a black-box methodology for optimizing ergodic stochastic systems, focusing on the construction of scalar measures that reliably indicate progress toward optimality. Our starting point is a state-value quantity that inherently exhibits oscillatory behavior and does not converge under standard conditions. We show that, despite its fluctuations, this quantity admits a recursive representation derived from a one-step-ahead fixed-local-optimal policy. The approach relies on identifying a Lyapunov-like function whose evolution reflects the long-run behavior of the system without requiring explicit knowledge of its internal dynamics. Such a function provides a monotonic indicator—non-increasing over time—that remains valid for any initial probability distribution. Whenever an optimal trajectory of the Markov chain exists, the proposed method guarantees convergence to it. We also provide a constructive procedure for obtaining the Lyapunov-like function and validate the methodology through theoretical analysis and numerical simulations. Full article

In response to the problem that the gears for offshore wind power are prone to cyclic stress and pitting damage under specific conditions, a finite element analysis method was adopted to establish numerical models for the distribution of cyclic stress on the gears and the dynamic expansion of pitting. Based on the material properties of ASTM5140 alloy structural steel, simulations were conducted using ANSYS 2024 R1 for contact stress analysis during gear meshing and COMSOL 6.3 for the evolution of pitting in a corrosive environment over a 120-h period. The results showed significant stress concentration in the tooth root fillet area under cyclic loads, with a maximum equivalent contact stress of 2.838 × 10⁸ Pa, which was identified as the key region for fatigue damage. Based on the simulated stress amplitude and material fatigue parameters, the predicted fatigue life of the gear under typical offshore operating conditions was approximately 13.3 years. In the corrosive environment, pitting pits exhibited an accelerating expansion trend, with pit volume increasing by approximately 125% and internal surface area by approximately 54% over 120 h. The volume growth followed a cubic polynomial, and the surface area growth followed a quadratic polynomial over time. These research results provide a quantitative basis for fatigue life assessment and corrosion protection design of offshore wind power gears. Full article

Steel–UHPC composite beams are widely used in bridge engineering due to their high strength, durability, and suitability for prefabricated construction. However, the mechanical performance of shear connectors in UHPC differs significantly, and the uniform use of a single connector type along the beam span may result in a mismatch between connector mechanical characteristics and regional force demands, leading to suboptimal force transfer and inefficient utilization of connector capacity along the beam span. While previous studies have mainly focused on the local behavior of individual connectors, a system-level design strategy considering regional force demands is still limited. This study proposes a system-level design method for combined shear connectors in steel–UHPC composite beams, in which headed stud connectors and trapezoidal composite dowel connectors are arranged according to bending moment distribution and interface shear demand, thereby integrating connector mechanical characteristics with the spatial variation in internal forces along the beam span. The design procedure includes shear span division, longitudinal interface shear calculation, and resistance verification of different connector types. The method is applied to a practical steel–UHPC composite beam in a long-span approach bridge. Results show that headed studs provide reliable uplift resistance and ductile behavior in negative bending regions, whereas composite dowel connectors are shown to be more suitable for shear-dominated positive bending regions due to their higher shear capacity and stiffness. The combined system ensures effective composite action under different stress states and reduces total connector steel consumption compared with a stud-only layout. The proposed approach advances connector design toward performance-oriented and system-level structural optimization, providing a practical framework for connector arrangement in steel–UHPC composite beams. Full article

Anaerobic digesters operating under neotropical conditions face significant technological constraints. High humidity, intense solar radiation, and pronounced diurnal temperature variations increase conductive, convective, and radiative heat losses. These factors reduce internal thermal stability and directly affect methane production rates and overall energy efficiency. As a result, thermal instability becomes a recurrent operational bottleneck in biogas plants without active temperature control. This review examines the thermal and dynamic behavior of anaerobic reactors from a process-engineering perspective. It integrates energy balances, heat-transfer mechanisms, and computational fluid dynamics (CFD) modeling. The combined effects of temperature gradients, hydrodynamic mixing patterns, and structural material properties are analyzed to determine their influence on thermal homogeneity, microbial stability, and methane yield consistency under mesophilic conditions. Technological strategies to mitigate thermal losses are evaluated. These include passive insulation using low-conductivity materials, geometry optimization supported by numerical modeling, and thermal recirculation schemes, as these factors govern temperature distribution and process resilience. Current limitations are also discussed, particularly the frequent decoupling between ADM1-based kinetic models and transient heat-transfer analysis. This separation restricts predictive capability under real-scale diurnal temperature oscillations. The development and validation of coupled hydrodynamic–thermal–biokinetic models under fluctuating neotropical boundary conditions are proposed as critical steps. Such integrated approaches can enhance operational stability, ensure consistent methane production, and improve energy self-sufficiency in organic waste valorization systems. Full article

Airport stand allocation research has traditionally focused on optimizing assignments within fixed infrastructure configurations, while strategic decisions regarding stand category composition remain underexplored. This study investigates how different proportional distributions of stand categories affect system-level performance under high traffic demand at international airports. A discrete-event simulation model implemented in MATLAB evaluates fifteen infrastructure configurations with varying distributions of small, medium, and large stands, classified according to the ICAO Annex 14. The model employed a first-come–first-served allocation logic to isolate infrastructure-driven effects from algorithmic decision-making. System throughput was measured through acceptance and rejection rates, disaggregated by aircraft stand category. Acceptance rates ranged from 33% to 92% across tested configurations, demonstrating pronounced sensitivity to stand composition. Balanced configurations consistently outperformed asymmetric alternatives. Insufficient stand availability in any single category led to concentrated rejection patterns and non-linear performance degradation; excess capacity in unconstrained categories could not compensate for shortfalls in constrained ones. Proportionality across stand categories is identified as a critical determinant of infrastructure robustness. The proposed simulation framework provides a computationally efficient tool for early-stage (pre-operational planning phase) infrastructure screening, supporting informed strategic capacity decisions prior to detailed operational optimization. Full article

This paper deals with a time-domain methodology for nominal stress-based, screening-level fatigue assessment of semi-submersible FWT hulls, using a 10-MW semi-submersible FWT as a case study. A comprehensive procedure is outlined for both short- and long-term fatigue analysis, emphasizing the influence of wind and wave loads, as well as the probability distributions of environmental conditions. A fully coupled dynamic analysis of the FWT, employing a multibody floater, is conducted to compute internal global loads and time-domain nominal stresses on the hull structure. Short-term fatigue damage is evaluated across various wind-wave directions, environmental conditions, and random wind and wave samples, identifying critical loading scenarios. For long-term assessment, 10,182 one-hour time-domain simulations are conducted across three wind-wave directions for five offshore sites in the North Sea and one site in the China Sea. Fatigue damage at different locations of the hull structure is estimated for each offshore site, with results discussed in the context of screening-level nominal fatigue assessment and identification of fatigue-critical regions. The insights gained from this study form a basis for validating simplified and computationally efficient fatigue analysis procedures in an accompanying paper. Additionally, the findings support the design optimization of hull structures. Limitations of the present study are identified, pointing to future research directions aimed at mitigating fatigue risks. Full article

This study examines how lean manufacturing practices are adopted in Singapore’s SME precision and electronics manufacturing industry. Its main goal is to assess the extent of lean manufacturing method adoption and the challenges involved. The study analyzed 36 responses from 150 surveys distributed online. The results show that about 50% of manufacturers find it difficult to implement lean manufacturing practices. Our research reveals that most SMEs face significant challenges when applying lean manufacturing techniques. The findings identify barriers such as a lack of experience, skills, and knowledge, which significantly slow progress. Additionally, the study emphasizes that management support is vital for successful lean implementation. Key factors include employee training, goal alignment, and the creation of a supportive environment. While tools and external expertise are helpful, internal resources and organizational culture are considered more critical. Full article

Hybrid girder bridges can be likened to plant grafting, where mechanical traits are inherited from both rootstock and scion girders, enabling performance that exceeds that of the individual components. To quantitatively evaluate this inheritance and optimize hybrid girder performance, this study develops a bionic binary grafting model inspired by the genetic principles of quantitative trait inheritance. By analyzing the flexural behavior of hybrid girders through classical beam theory, the research explores two sequential phases: trait inheritance and trait optimization. In the inheritance phase, the bending moment is governed by the hybrid ratio and the positional advantage of scion girders. In the optimization phase, iterative refinements in girder height and internal force further enhance structural performance. The key contributions of this study are as follows: (1) a novel bionic framework is proposed to quantitatively characterize mechanical trait inheritance in hybrid girders, introducing inheritance ratios to describe the distribution of bending moment between rootstock and scion girders as functions of the hybrid ratio, stiffness ratio, and load ratio; (2) a design-oriented framework for mechanical trait optimization is developed, demonstrating that hybrid girders can achieve equivalent stress performance with reduced structural height; and (3) the proposed inheritance and optimization formulations are validated against representative engineering cases, confirming their accuracy in estimating the optimal inheritance ratio and girder height for hybrid girder bridges. This bio-inspired framework enhances our understanding of hybrid girder performance enhancement mechanisms, enabling the efficient optimization of structural systems during conceptual design by leveraging materials with diverse mechanical properties. Full article

Characterizing surface runoff and the transport process of non-point source pollutants (NSPs) carried by this runoff is crucial for identifying key source areas, estimating pollution loads entering water bodies, and implementing pollution control, which is particularly important in regions dominated by smallholder farming in China. Currently, most of the commonly used NSP models originated from international countries and have shortcomings such as high data requirements, high generalization degrees, and requiring the calibration of numerous parameters in the application process. Therefore, a distributed non-point source pollution model based on the time-varying gain and stormwater runoff response was constructed, designed for application at the watershed scale. This study describes the construction of the model, introducing its principles and structure through three key modules: a rainfall–runoff module, a soil erosion module, and a pollutant migration and transformation module. The proposed model was used to simulate the rainfall–runoff, soil erosion, and nutrient migration and transformation processes at different spatiotemporal scales. Although it achieved the best performance at the monthly and annual scales, its simulation results at the daily and hourly scales still met the relevant requirements, with relative errors within 20% and Nash–Sutcliffe Efficiency (NSE) coefficients of approximately 0.7. The annual sediment delivery ratios for the Yangliu Small Watershed and the basin above the Ankang section in 2022 were determined to be 0.445 and 0.36, respectively. The pollutant processes corresponding to different runoff events in the Yangliu Small Watershed were simulated, and the average NSE for total nitrogen (TN), ammonia nitrogen (NH₃-N), nitrate nitrogen (NO₃-N), total phosphorus (TP), and soluble reactive phosphorus (SRP) were determined to be 0.69, 0.74, 0.79, 0.71, and 0.71, respectively. For the basin above the Ankang section, the NSE coefficients for the simulation of NH₃-N and TP pollutant processes were 0.78 and 0.83, respectively. The model demonstrated robust applicability across various spatial (ranging from small to large watersheds) and temporal (hourly−daily−monthly−annual) scales, and exhibited stability across different basins in a semi-humid region of China. The model is characterized by a parsimonious parameter set, ease of calibration, and strong spatiotemporal versatility, thus providing an efficient and reliable tool for non-point source pollution simulation. Full article

The Taoping paleo-landslide poses a significant risk to local residents and critical infrastructure. However, traditional field surveys and deformation monitoring methods are often inadequate for capturing subtle, localized deformation characteristics—particularly at the head scarp and lateral margins—thereby limiting comprehensive assessments of slope instability. Surface strain data offer direct insights into internal stress redistribution during slope evolution and are essential for interpreting landslide mechanisms and forecasting failure. Given the current limitations in dense and wide-area strain monitoring technologies, this study proposes a novel method for modeling landslide strain fields based on Interferometric Synthetic Aperture Radar (InSAR) phase gradients. Using the phase gradient stacking approach, InSAR-derived phase gradients are transformed into strain-related parameters, enabling estimation of shear strain rates, principal strain rates, and their directional distributions. The application to the Taoping paleo-landslide reveals clear spatial patterns of compressive and tensile strain across the landslide body. Field investigations corroborate the InSAR-derived strain features through corresponding geomorphological evidence observed in both compressional and extensional zones. The proposed method enhances the understanding of landslide deformation behavior, supports evaluation of shear surface continuity and evolution, and offers a robust framework for early warning and risk mitigation in complex landslide-prone areas. Full article

Electric field distortion remains a fundamental challenge to the operational reliability of HVDC cable accessories, where localized stress intensifies space charge injection and accelerates insulation degradation. While nonlinear conductive composites incorporating functional fillers such as ZnO have shown potential for adaptive field grading, their dynamic interaction with space charge under non-uniform fields has yet to be fully resolved. This study experimentally examines the spatiotemporal evolution of space charge in double-layer dielectric structures comprising linear low-density polyethylene (LLDPE) and ZnO-based nonlinear composites, using the laser-induced pressure pulse (LIPP) technique. Localized field enhancement is introduced via metallic pin defects embedded on the cathode side. Comparative analysis reveals that composites with 40 vol% ZnO microvaristors markedly suppress charge injection compared to conventional semiconductive ethylene-vinyl acetate (EVA) layers. Specifically, interfacial charge accumulation during polarization is reduced by 71%, and residual charge density after depolarization decreases by 88%, leading to a more uniform internal field distribution. These findings provide direct experimental evidence of the field-regulating mechanism of nonlinear composites from the perspective of charge dynamics, supporting their application in intelligent HVDC insulation systems. Full article

Background: Multimorbidity frequently involves overlapping neuro-psychic, cardiometabolic, and renal disturbances, yet clinical assessment often relies on diagnosis-based comorbidity counts that may not fully capture cumulative physiological stress. We developed the Neuro–Cardio–Renal Stress Index (NCR-SI) as a pragmatic composite framework to describe multisystem burden using routinely available clinical data. Methods: This cross-sectional study analyzed electronic medical record data from adult patients with chronic conditions. NCR-SI integrates three domains: neuro-psychic burden (text-derived indicators and psychotropic medication use), cardiometabolic stress (triglyceride–glucose index and cardiometabolic diagnoses), and renal function (MDRD-estimated eGFR staging). Importantly, this study is not intended to demonstrate incremental predictive value over individual components or established comorbidity indices. Rather, it presents NCR-SI as a transparent, domain-based descriptive framework and reports its internal coherence and distribution across clinically recognizable multimorbidity contexts. Results: A total of 148 patient records were screened; 143 patients met complete-case criteria and were included in the main NCR-SI analyses. NCR-SI ranged from 0 to 10 (median 5). Higher scores were observed in renometabolic profiles. NCR-SI showed expected structural associations with declining renal function (eGFR; ρ ≈ −0.71), moderately with the TyG index (ρ ≈ 0.42), and weakly with medication burden. Correlation with age-adjusted CCI was minimal (ρ ≈ 0.09), indicating limited overlap with diagnosis-based comorbidity counts. Domain-specific correlations were consistent with predefined score construction rules, particularly between the renal domain and eGFR, and between the cardiometabolic domain and TyG. Conclusions: NCR-SI provides a pragmatic, integrative descriptor of neuro-cardio-renal stress using routinely collected clinical data. Rather than replacing established comorbidity indices, NCR-SI may complement them by summarizing multidimensional physiological burden patterns. NCR-SI is proposed as a research-oriented, hypothesis-generating descriptive framework. External validation in independent cohorts and longitudinal evaluation against clinically meaningful outcomes (e.g., hospitalization, mortality, functional status, healthcare utilization) are required before any claims of clinical performance can be made. Full article

Spatial qualities are central to architectural reasoning; yet, in studio-based education, they often remain implicit rather than structured as a shared analytical framework. This study examines how a multi-scalar taxonomy of spatial qualities can function as a collaborative analytical language in studio-based architectural education. Situated in Košanćićev venac and Dorćol, two historically layered areas of Belgrade’s old town, this study integrates expert spatial analysis with a student questionnaire administered across bachelor and master study levels. Empirical testing was conducted to evaluate structural coherence, conceptual differentiation and the distribution of spatial qualities across detail, architectural and urban drawing scales. The findings indicate consistent internal stability, clear differentiation among constructs and statistically significant cross-scale articulation. Form- and composition-related qualities showed high usability, while interpretative constructs were more variable. Master-level students demonstrated greater engagement with cognitive and interpretative constructs, indicating a shift toward more conceptually grounded design reasoning without affecting overall structural coherence. These results suggest that spatial qualities can operate as a level-independent analytical language, supporting inclusive participation, shared interpretation and structured dialogue within the design studio. By positioning spatial qualities as a collaborative pedagogical framework, this study contributes to interdisciplinary communication and more equitable engagement in architectural education. Full article