Search Results (289)

The development of sustainable tourism requires the use of planning methods that combine environmental protection with inclusive access to nature-based destinations. This article presents a macro-level spatial decision-support framework for planning service infrastructure for specialized off-road electric wheelchairs in mountain destinations. The proposed framework combines predefined static vehicle-related constraints, Geographic Information System (GIS) analysis using QGIS and OpenStreetMap data, and Multi-Criteria Decision Analysis (MCDA). The spatial filtering stage evaluates terrain feasibility using an adopted maximum longitudinal slope threshold and minimum path-width requirement. The location–allocation stage combines Simple Additive Weighting (SAW) with a spatial-dispersion procedure to identify service hubs that are both suitable and regionally distributed. The method is not a dynamic engineering model of vehicle performance, but a GIS-MCDA planning tool for preliminary regional infrastructure siting under predefined operational constraints. Full article

Partial nitrification (PN) is a promising strategy for reducing aeration demand and improving the energy efficiency of biological nitrogen removal in wastewater treatment. However, maintaining stable PN in continuous-flow activated sludge reactors remains challenging due to the recovery of nitrite-oxidizing bacteria (NOB) and the absence of cyclic operational phases that naturally promote microbial selectivity in sequencing batch reactors. This study proposes a model-based multi-criteria optimization framework to identify and classify feasible operating conditions for stable PN in continuous-flow activated sludge reactors. A modified Activated Sludge Model No. 1 (ASM1) was used to describe the dynamics of ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and heterotrophic biomass, while equilibrium points were determined through steady-state optimization and evaluated using a multi-criteria feasibility analysis based on nitrite accumulation ($\beta$), ammonium oxidation efficiency ($\alpha$), oxygen uptake rate (OUR), hydraulic retention time (HRT), and sludge retention time (SRT). Seasonal variability was incorporated through summer and winter operating scenarios. Results indicate that stable PN can be achieved under operating conditions of pH 7.5–8.5, dissolved oxygen concentrations between 0.3 and 2.5 mg/L, HRT values of approximately 2–3 h, and SRT values between 10 and 20 d. Under these conditions, high nitrite accumulation ($\beta >0.8$) and ammonium oxidation efficiency ($\alpha >0.8$) were maintained with moderate oxygen demand, although seasonal differences revealed greater operational flexibility in summer and tighter constraints in winter. The proposed framework provides a systematic approach for identifying robust and energy-efficient operating regions in continuous-flow PN systems and establishes a foundation for future supervisory control implementation in full-scale wastewater treatment applications. The study also shows that over 40% energy savings could be achieved at optimal equilibrium points for partial nitrification compared to full nitrification. Full article

This study proposes a rigorous methodology for the optimal placement of voltage regulators in the Guayacanes feeder of the Buena Fe substation, Ecuador, by integrating electrical feeder modeling, exhaustive search, and multi-criteria decision-making. The feeder was modeled in detail by incorporating its radial topology, nodal electrical parameters, and representative operating conditions under minimum- and maximum-load scenarios. Based on this model, a set of technical evaluation criteria was established to quantify the impact of regulator installation, including active power losses, reactive power losses, global voltage deviation, average voltage variation, and voltage imbalance. An exhaustive search strategy was then implemented to evaluate all feasible regulator-location alternatives over the candidate nodes, thereby ensuring a complete exploration of the solution space. The resulting alternatives were ranked using the Weighted Sum Method (WSM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), allowing the comparison of candidate locations from a multi-criteria perspective. The results indicate that node MTS 108932 provides the most technically favorable overall solution, achieving the greatest improvement in voltage profile quality and the most significant reduction in electrical losses. In addition, a sensitivity analysis was conducted by varying the weighting structure of the decision criteria, confirming the robustness of the selected alternative under different decision-maker preference scenarios. The proposed framework provides a technically sound decision-support methodology for voltage regulation planning in real radial distribution systems. Full article

The integration of renewable energy technologies into urban buildings is a key strategy in sustainable city development. This study explores the application of building-integrated photovoltaic (BIPV) systems in a selected building at Vilnius Gediminas Technical University (VGTU), aiming to identify the most balanced solution among energy efficiency, architectural quality, and operational feasibility. Using a Building Information Model (BIM) of the existing structure, five alternative design scenarios were developed by varying the number and capacity of façade-mounted photovoltaic (PV) panels and semi-transparent PV windows. Each scenario was evaluated against six criteria: (1) potential solar energy yield, (2) temporal correlation between energy generation and building consumption, (3) maintenance accessibility and associated cost, (4) architectural aesthetics, (5) installation cost, and (6) cost effectiveness. To ensure a rigorous and interdisciplinary evaluation, the Delphi-based ELECTRE Multi-Criteria Decision-Making (MCDM) method was applied. Expert panels representing disciplines of construction engineering, architecture, electrical engineering, and business management participated in determining the relative importance of each criterion. The results demonstrate the potential of combining BIM-based energy simulation with expert-driven decision analysis to optimize BIPV integration strategies in complex urban environments. The proposed framework offers a replicable methodology for guiding sustainable façade design and supporting the adoption of renewable energy in various public and administrative buildings across cities. Full article

One of the most critical challenges in maritime transport decarbonization, as part of the EU greenhouse gas (GHG) neutrality strategy, is the reduction in GHG and harmful emissions from the energy systems of existing vessels. Furthermore, the potential for implementing decarbonization technologies in operating vessels remains significantly more limited compared to newly constructed ships. Selecting appropriate decarbonization measures requires a comprehensive evaluation of technological feasibility, economic viability, and environmental performance, in accordance with the regulatory frameworks established by the IMO and the EU. A major limitation in such decision-making processes is ensuring the representativeness and reliability of expert judgments. In order to improve the reliability of results by expanding and structuring the information base, this study proposes and implements a method based on the integration of SWOT analysis with multi-criteria decision-making (MCDM) methods. The objective of this study was to examine the methodological aspects of testing the integrated application of comprehensive analysis and ranking methods for decarbonization technologies as applied to a prototype oil tanker. Based on the SWOT analysis method, technological solutions that are available for practical application were identified for the medium-term decarbonization period considered in the study, up to 2030–2035. Subsequent rating based on several applied multi-criteria (MCDM) analysis methods (TOPSIS, COPRAS, SAW) allowed us to examine the range, stability and sensitivity of the obtained solutions in relation to the methods themselves and scenarios with variations in the weighting factors of the evaluation criteria. The complete match of the ratings obtained using the TOPSIS and COPRAS methods confirms the stability of the multi-criteria decision-making process (priority-compromise order): CCS, kite, air lubrication, Flettner rotor. The performed sensitivity analysis showed that the technology rankings remain relatively stable when the weighting factor for the CO₂ reduction criterion varies within a range of approximately ±10%, while larger deviations result in an increasing difference between all three MCDM methods. For the TOPSIS method, the change limits for the critical values of the threshold indicators were ±20%, the COPRAS method showed intermediate results, and changing the weighting coefficients within a ±20% range did not alter the selection of the best technology. The results obtained allow for a positive assessment of the effectiveness of the proposed integrated methodology when applied as an alternative in the initial stage of ranking decarbonization methods for in-service ships. Full article

The electrification of public transport, particularly Bus Rapid Transits (BRT), is a significant step toward achieving sustainable urban mobility and reducing dependency on fossil fuels. However, rapid adoption of Electric Vehicles Smart Charging (EVSC) infrastructure presents grid stability, economic and environmental concerns. The rising demand for electric cars, particularly in developing nations such as Nigeria, highlights the urgent need for a sustainable hybrid renewable energy charging infrastructure for BRT systems. This study presents a techno-economic assessment of an off-grid hybrid systems that use photovoltaic (PV), wind turbines (WTs), hydrogen (H₂), fuel cell (FC) and battery technologies to power Electric Vehicles Smart Charging within Bus Rapid Transits networks. The Lagos BRT charging system at City Mall Station (CMS) serves as a case study, with hourly renewable resources obtained from National Aeronautics and Space Administration database (NASA). Using the HOMER pro-optimization tool, a multi-criteria analysis is performed to evaluate system viability, with special focus on key metrics such as levelized cost of energy (LCOE), net present cost (NPC), renewable energy fraction (REF), and greenhouse gas (GHG) emissions. The simulation results demonstrate that the hybrid PV/wind/FC/battery configuration is exceptionally economical, with an LCOE as low as $0.222/kWh, $2.03M NPC, 51.3% REF, and 159,209 kg of carbon dioxide emissions per year compared to grid-dependent charging. The study shows that integrated renewable-hydrogen systems are not only financially feasible, but also provide significant insights for policymakers, transportation authorities, and energy planners seeking to accelerate the transition to green public transportation infrastructure through innovative hybrid energy schemes. Full article

Urban drought pressure is increasing the operational risk and cost of maintaining municipal green infrastructure. Irrigation is still widely managed through fixed routines and fragmented information. To address this challenge, the study develops an integrated operational analysis by combining water consumption records, maintenance data and a GIS inventory for twenty municipal green spaces. System characterisation and performance screening were carried out using hourly meter readings to distinguish typical scheduled irrigation peaks from non-standard consumption patterns. To move from monitoring to control, irrigation needs were estimated using evapotranspiration (ET₀) and a garden-coefficient logic adapted to urban planting conditions and compared with measured consumption. The comparison indicates a potential reduction of 29–61% through improved scheduling and system adjustment. Based on the diagnosis, technical intervention scenarios were defined and assessed using techno-economic metrics, including ground-cover redesign and Mediterranean-adapted planting strategies. To support implementation, options were organised into intervention priorities using a multicriteria tool that balances water savings, costs and feasibility under municipal operations. Coimbra, Portugal is used as a case study, and a pilot application in a city garden, supported by 797 user surveys, clarifies practical constraints for scaling beyond isolated pilots. Turf-free scenarios indicate a 53.4% reduction in water use and a 60.5% reduction in operational costs, with a payback period below three years. The results highlight the potential of data-driven irrigation management to support more resilient, cost-effective and water-efficient municipal green infrastructure across diverse urban contexts. Full article

This manuscript creates a framework for decision support based on green urbanism to direct the sustainable development of Gamasa, an Egyptian seaside city. The paper aims to convert the concepts of green urbanism into a multi-criteria evaluation that can support strategic urban development and prioritize spatial interventions. Sustainable mobility, green and blue infrastructure, energy and resource efficiency, urban form and density, social livability and public space quality, and governance and implementation feasibility are the six dimensions that are defined. These dimensions are derived from international sustainability literature and tailored to Gamasa’s particular challenges. The study’s methodology combines a multi-criteria decision-making approach based on the AHP with spatial analysis of land use, street hierarchy, building shape, and green space distribution. Weights for these dimensions are determined by expert-based pairwise comparisons, which are backed by a SWOT analysis. To prioritize priority zones for green transformation, the weighted framework is applied to four important urban areas: residential districts, a large urban park, the waterfront, and the main urban corridor. The top priorities, according to the results, are climate-responsive coastal design, increased green and blue infrastructure, and sustainable transportation. For quickly urbanizing coastal cities, the method demonstrates how the AHP operationalizes green urbanism into quantifiable, context-sensitive goals. Full article

Conventional multi-criteria decision-making approaches for battery energy storage system (BESS) dispatch evaluation treat regulatory and policy conditions as compensable criteria within a single aggregate score. This becomes problematic when institutional admissibility functions as a prerequisite for deployment rather than a tradeable attribute. This study aims to develop and test a sequential gate framework. The methodological contribution lies in the evaluation architecture itself: the framework distinguishes sequential admissibility gating from conventional compensatory Multi-Criteria Decision-Making (MCDM). Deployment feasibility is conceptualized as a layered construct in which regulatory admissibility defines the feasible solution space and technical performance differentiates among admissible options. The framework integrates systematic literature screening, quantitative policy and regulatory assessment, and technical ranking using a hybrid Best-Worst Method, Entropy weighting, and TOPSIS approach. A Danish case study covering twelve dispatch strategies compares the proposed sequential design with two flat alternatives. The results show that the evaluation architecture materially affects outcomes: sequential gating excludes an institutionally incomplete strategy and reorders the upper tier by removing compensatory policy effects. Coordinated multi-BESS control at Electric Vehicle charging parks achieves the highest combined feasibility (closeness coefficient 0.891, ranked 1st), while mobile BESS is excluded by the admissibility gate. The sequential design reorders the upper tier relative to flat MCDM, with S4 and S6 rising and S2 and S10 falling once policy compensation is neutralized after the gate. The top-ranked strategy remains robust across sensitivity analysis, Monte Carlo simulation, score perturbation, and VIKOR cross-validation. The framework is presented as an analytical pre-simulation screening tool rather than a validated implementation instrument; external validation against real deployment outcomes is identified as a priority for future research. The framework provides a structured, decision-consistent approach for evaluating deployment feasibility in regulated energy systems. Full article

The rapid electrification of road transport has increased interest in distributed energy strategies that reduce grid demand and support decarbonization. Vehicle-integrated photovoltaics (VIPV), including vehicle-applied photovoltaic configurations (VAPV), can generate electricity directly on the vehicle. This systematic review examines peer-reviewed VIPV literature published between 2015 and 2026, focusing on the distinction between theoretical photovoltaic generation and practically usable energy. A Scopus search conducted on 2 May 2026 identified 196 records, of which 88 studies were included after screening against predefined criteria. Due to heterogeneity in vehicle types, climates, technologies, modeling assumptions, and reported metrics, no meta-analysis was performed. Instead, the review applies a multi-layered framework covering climate, geometry, thermal effects, electrical mismatch, battery state-of-charge interactions, fleet-scale modeling, economics, and life-cycle implications. The evidence shows that VIPV is technically feasible and can deliver measurable energy yields, especially in high-irradiance regions and vehicles with favorable daytime parking exposure. However, useful contribution depends strongly on curvature losses, dynamic shading, electrical configuration, SOC limits, charging behavior, seasonality, and vehicle energy demand. Therefore, VIPV is best understood as a context-dependent supplementary energy strategy rather than a transformative standalone solution. Its strongest value lies in specific vehicle classes, climates, and usage patterns where on-board generation can reduce charging demand, support operational resilience, or improve distributed self-consumption. The review also proposes minimum reporting requirements for future studies, including annual energy yield, Wh/km contribution, PV area or capacity, mileage assumptions, SOC modeling, and curtailment treatment. The review was not formally registered, and no formal risk-of-bias or certainty assessment was applied. Full article

Operating room ventilation is a key engineering factor in maintaining clean air environments. This study presents an integrated three-part methodology combining Computational Fluid Dynamics parametric analysis, performance assessment with effect size analysis and multi-criteria decision analysis using quantitative engineering metrics, and surrogate modeling for thermal effect propagation in an orthopedic operating room. Simulations were conducted in ANSYS Fluent 2020 R₂, benchmarking an existing local operating room against an ASHRAE 170-2021 compliant model, followed by parametric evaluation of four ceiling inlet configurations. The existing system exhibited critically low velocities (0.05–0.10 m/s) with a coefficient of variation of 0.73, indicating severe flow non-uniformity. The proposed Multi-Velocity Ceiling Diffuser—featuring a high-velocity core (0.40 m/s) over the surgical area and a low-velocity peripheral frame (0.20 m/s)—achieved 85% coverage of the ASHRAE-recommended velocity range (0.20–0.30 m/s), a coefficient of variation of 0.14 (81% improvement), and 62 air changes per hour, representing an 86% reduction in supply airflow compared to a full-ceiling system. Effect size analysis confirmed that MVCD performance shows large practical differences from smaller inlet designs (Cohen’s d ≥ 0.41) and negligible difference from full-ceiling systems (Cohen’s d = 0.05). Multi-criteria decision analysis—with feasibility and cost quantified using engineering estimates (ductwork area, downtime days, standardized cost data)—ranked MVCD as optimal under the modeled assumptions (composite score = 0.84), outperforming the existing system (0.59) and full-ceiling design (0.51). To address the isothermal assumption limitation, a Random Forest surrogate model was implemented as a differentiable approximation strategy for parametric uncertainty propagation. Under non-isothermal conditions, the MVCD is predicted to maintain a spatial median velocity of 0.19 m/s (5th–95th percentile range: 0.17–0.21 m/s) and 71% ASHRAE compliance (parameter sampling range across literature-derived distributions: 63–78%). Achieving ASHRAE velocity criteria is an engineering surrogate for ventilation effectiveness; the relationship between these metrics and clinical infection outcomes depends on multiple factors beyond airflow, including surgical technique, patient factors, and antimicrobial prophylaxis. No clinical inference is permitted from the present results. Experimental measurement in a physical MVCD-equipped operating room is required to validate these predictions prior to clinical implementation. Full article

The rapid integration of UAVs (Unmanned Aerial Platforms) introduces new operational capabilities but also raises critical challenges. This paper presents a quantitative risk assessment approach for evaluating the risks related to drone-assisted systems. The methodology combines established standards with the principles of the multi-criteria hierarchy concept. First, a qualitative analysis is performed to identify and register the required risk elements. Following this, a hierarchical model is developed to model the dependencies between systems’ components, environmental factors, structural limitations, and operational uncertainties. An AHP-based (Analytic Hierarchy Process) process is applied to enable elements quantification. To demonstrate the applicability and feasibility of the proposed methodology, two different drone-assisted systems are examined, showcasing their effectiveness in evaluating critical risk elements and computing cumulative risk contribution to quantify and prioritize potential risk events. The results indicate the significance of the methodology in ranking the verified risk elements and identifying those that made the greatest contribution to system failure. As revealed, power- and weather-related elements are among the most significant contributors to performance deterioration. In addition, operator-related factors significantly contribute to the system’s overall functional performance, especially when it is manually controlled. Finally, a comparative analysis underscores the sensitivity of risk ranking to variations in AHP scoring. Full article

Over the past few decades, extensive attention has been given by researchers and practitioners to the development and application of multi-criteria decision-making (MCDM) methods within intuitionistic fuzzy environments across a wide range of fields and disciplines. This challenging research area has emerged as one of the most prominent topics, and its importance and popularity are expected to continue growing in the future. The elliptic intuitionistic fuzzy set (EIFS) addresses complex, multidimensional, non-symmetrical vagueness and uncertainty more effectively than other traditional intuitionistic fuzzy sets (IFSs). Sustainable renewable energy source selection is a critical decision-making (DM) process aiming to identify the most suitable energy alternative. The process of selecting sustainable renewable energy sources necessitates a comprehensive assessment of numerous criteria, which encompass environmental ramifications, economic feasibility, and societal acceptance. Contemporary research suggests novel methodologies to enhance this selection process, highlighting the need for an MCDM framework that integrates a variety of factors. This study presents an innovative DM framework for sustainable renewable energy source selection based on EIFS and a newly developed aggregation operator, the Elliptic Intuitionistic Fuzzy Weighted Muirhead Mean Aggregation (EIFWMMA) operator. These mechanisms expand upon conventional intuitionistic fuzzy frameworks by employing an elliptical portrayal of membership and non-membership degrees, facilitating a more accurate and lifelike representation of uncertainty and hesitation in evaluations by experts. To enhance computational efficiency, the framework weaves together machine learning-driven dimensionality reduction and weight optimization strategies of principal component analysis (PCA) for DM. The suggested operators are employed in an MCDM scenario centered around the selection of sustainable renewable energy sources, where the hierarchy of alternatives is established through score values derived from EIFWMMA. A comparative exploration of Circular Intuitionistic Fuzzy Sets (C-IFSs) and Interval-Valued Intuitionistic Fuzzy Sets (IVIFSs) uncovers that the elliptical formulation yields consistently reliable, precise, and geometrically comprehensible results. The findings affirm that EIFS-based operators offer a resilient, adaptable, and broadly applicable strategy for tackling MCDM challenges amidst uncertainty. The Min–Max normalization method is employed to validate our proposed methodology for identifying alternatives within the MCDM paradigm. It also improves accuracy, stability, and scalability in comparison to conventional approaches. Full article

This study develops a human-centered Artificial Intelligence (AI) framework enabling rapid ecodesign prioritization for Ecodesign for Sustainable Products Regulation (ESPR) compliance while demonstrating Large Language Model (LLM) integration in sustainability strategy. A four-stage hybrid methodology combining LLM-assisted action identification (30 ESPR-aligned interventions) with multi-criteria decision analysis with analytic hierarchy process (MCDA-AHP) is developed. Expert validation addressed LLM-driven interventions’ limitations with practitioners evaluating AI suggestions based on the value chain context. The framework applied to two Italian building-integrated photovoltaic (BIPV) small-medium enterprises (SMEs) demonstrated strategic differentiation based on feasibility vs. desirability vs. affordability, producing systematically different action portfolios within regulation-aligned aggregate structures. Sensitivity analysis showed 100% priority stability under ±10% AHP variations for priority one, three, and four actions and 82% for priority two actions, validating framework robustness. The framework provides empirical evidence for augmentation-not-automation in AI-assisted strategic planning, contributing a replicable methodology for responsible LLM integration across manufacturing sectors. Results demonstrate that combining AI synthesis efficiency with human contextual judgment enable regulation-aligned, business-model-specific sustainability strategies. Full article

Trajectory planning algorithms are essential in human–robot collaboration (HRC), as they must generate efficient trajectories for seamless interaction. Given the risks and complexity of testing in real-world scenarios, a virtual environment was developed in Unity 3D, integrating a virtual model of the UR3 robot that delivers workpieces to a user equipped with a Meta Quest device. The RRT, RRT-Star (RRTS), and RRT-Connect (RRTC) algorithms were evaluated using ANOVA and Tukey post hoc tests, considering the following response variables: safety, feasibility, smoothness, and computation time across three experimental scenarios characterized by (i) low, (ii) medium, and (iii) high levels of movement of the participant’s left hand. The statistical results indicate that RRTC exhibited the best performance in terms of smoothness and computation time. Based on these findings, a multicriteria decision-making analysis was conducted using the Analytic Hierarchy Process (AHP), combining quantitative evidence derived from the statistical analysis with expert judgments supported by bibliographic references. This multicriteria analysis enabled the coherent integration of the different evaluation criteria and concluded that RRTC is the most suitable alternative for collaborative assembly tasks in HRC environments. Full article