Search Results (350)

The Transformer project at TU Wien exemplifies how universities can act as initiators for sustainability education and STEM science communication. Addressing the urgent need for climate change adaptation and the strengthening of key competencies for sustainability, this paper examines the university’s role in creating a temporary, participatory learning space. The Transformer bridges academic research and societal practice, demonstrating how higher education institutions can actively shape sustainable development. As both a knowledge producer and a facilitator of public dialogue, TU Wien designs the Transformer as a hands-on laboratory for children and adolescents, providing low-threshold access to STEM and sustainability content. By integrating university students and researchers from architecture, civil and environmental engineering, mechanical engineering, electrical engineering, informatics, and technical chemistry, the project transforms abstract scientific concepts into tangible, co-created solutions. This approach is designed to foster systemic thinking, practical skills, and participant agency—outcomes for which this paper presents documented but preliminary evidence—while enriching academic teaching and research through real-world applications. This paper analyses how TU Wien’s commitment to interdisciplinary cooperation and participatory science communication positions the Transformer as a model for other institutions, with a focus on circular economy as the anchor theme. Through reflective practice on four analytical dimensions—place-based learning, staged sustainability education, co-creative STEM communication, and the engaged university—this study offers insights into the challenges and opportunities of university-led co-creation spaces and considerations for institutions seeking to develop comparable initiatives. Full article

Liquid-hydrogen fuel-cell propulsion is a promising option for reducing the climate impact of short-range aviation, but its aircraft-level feasibility depends on the concurrent integration of cryogenic storage, megawatt-class propulsion systems, and thermal management. This paper presents an integrated conceptual design and technology-sensitivity assessment of a 101-passenger liquid-hydrogen fuel-cell aircraft, targeting a 1000 nmi design range and a 2040 entry into service, framed within the European Union FAME project. A JPAD-based aircraft sizing framework is coupled with a surrogate model for cryogenic tank sizing to investigate how selected hydrogen-subsystem characteristics propagate, through mission-fuel and tank-sizing convergence loops, to configuration-level performance and compliance with top-level aircraft requirements. The storage-system trade study identifies 2.0 bar as the most favourable sampled tank venting pressure; relative to the other investigated pressure levels, this solution reduces MTOM and design-mission block fuel by up to 8.1% and 9.2%, respectively. The propulsion-architecture study selects a four-engine layout as the best compromise between one-engine-inoperative performance, spanwise structural relief, nacelle drag, and mission fuel consumption, yielding a 2.6–2.7% lower MTOM and a 3.5–3.7% lower design-mission block fuel than the two- and six-engine alternatives. A technology-sensitivity matrix spanning 51–55% fuel-cell efficiency and 60–100% cooling-line speed recovery reveals a non-linear increase in installed power, aircraft mass, and hydrogen consumption as either parameter deteriorates. For the fixed-geometry FAME baseline, the onset of multiple TLAR violations occurs as speed recovery falls through approximately the 70–80% region, depending on fuel-cell efficiency. Within the assumptions of the present model, maintaining fuel-cell efficiency at or above approximately 53% and cooling-line speed recovery above this transition region therefore represents an approximate feasibility condition. Full article

Background: This study investigates information-flow and logistics coordination challenges in Saudi Arabian construction projects within the context of ongoing national infrastructure developments, severe climatic conditions, and evolving labor regulations. Methods: Utilizing the Supply Chain Operations Reference (SCOR) framework, semi-structured interviews were conducted with 29 construction professionals spanning site-level engineers, logistics managers, project executives, and material suppliers over an extended 20-month monitoring period (March 2024–October 2025). Data were analyzed using thematic coding and mapped across the SCOR domains. Results: The findings reveal that logistics vulnerabilities stem predominantly from systemic information-sharing deficiencies, fragmented digital workflows, and weak stakeholder integration rather than standalone material constraints. Operational disruptions across Plan, Source, Make, Deliver, and Return are compounded by region-specific barriers including extreme thermal stress, migrant labor turnover, and high administrative fees for reverse logistics. Conclusions: To address these challenges, the study formulates a tiered, context-adjusted deployment framework for digital integration (BIM, IoT, and real-time tracking) tailored for both large infrastructure schemes and small-to-medium contractors. Staged implementation pathways and policy recommendations are provided to enhance supply chain resilience. Full article

Reliable intensity–duration–frequency (IDF) curves are essential for the design of stormwater drainage systems and flood mitigation infrastructure; however, conventional IDF relationships assume stationarity and may underestimate future rainfall extremes under climate change. This study developed climate-informed IDF curves for Makkah, Saudi Arabia, using hourly observed rainfall records (1985–2025) and projections from five CMIP6 Global Climate Models (EC-Earth3-CC, CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-LR, and UKESM1-0-LL) under the SSP245 and SSP585 scenarios. Spatial downscaling was first carried out using bilinear interpolation, after which the resulting data were corrected for systematic bias using the Delta Change method. Daily precipitation projections were subsequently disaggregated to an hourly timescale using an enhanced KNN-MOF approach. Annual maximum precipitation series were then derived for durations of 1, 2, 3, 6, 12, and 24 h and fitted to a range of candidate probability distributions. The goodness of fit was evaluated using the log-likelihood, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). Across the five CMIP6 models, two emission scenarios, and six rainfall durations, the Log-Pearson Type III distribution consistently yielded the most satisfactory fit. Historical analysis estimated 100-year rainfall depths ranging from 7.84 mm (1 h) to 38.29 mm (24 h), while future projections indicated substantially higher design rainfall intensities under several climate models. For example, under the SSP585 scenario, the 100-year 1 h rainfall intensity reached 29.73 mm h⁻¹ for EC-Earth3-CC, whereas MPI-ESM1-2-LR projected a 102% increase in the 6 h 100-year intensity relative to SSP245. Sherman equations were successfully fitted to develop continuous IDF relationships, while bootstrap resampling and Bayesian inference quantified projection uncertainty. The multi-model ensemble indicated increasing uncertainty with return period, particularly for the 100-year event, highlighting the importance of incorporating uncertainty into engineering design. The proposed framework provides robust climate-informed IDF curves for supporting resilient urban drainage design, flood-risk assessment, and water resources planning in arid environments. Full article

Pumped hydro storage is a well-established and reliable form of energy storage, with construction scale expanding steadily in recent years. Underground cavern excavation is an indispensable part of pumped storage construction, while sustained cavern inflow poses potential threats to engineering and regional water security. This study first summarizes the hydrochemical characteristics of cavern inflow from 62 pumped-storage projects in China. Combining field investigations, water pressure tests, hydrochemical analyses, and multi-method inflow forecasting, the study further discusses the cavern inflow features of two typical projects under different climatic environments. The results indicate that across the 62 projects, total dissolved solids (TDS) in inflow water range from 21.0 to 4270.7 mg/L, with pH values of 6.7–8.3, and are dominated by HCO₃-Ca type. Moving from humid toward arid regions, TDS shows a continuous increase, while pH exhibits no significant variation. At the Shanshan site, controlled by evaporation, silicates weathering and evaporite dissolution, cavern inflows are dominated by high-salinity SO₄-Mg type water with pronounced SO₄²⁻ enrichment. Predicted inflows of the underground powerhouse and water conveyance tunnels are 1247.96–5542.97 m³/d and 105.85–211.69 m³/d, respectively. The Ningshanbei site, located in the humid area, is characterized by low-salinity HCO₃-Ca freshwater controlled by carbonate dissolution, with a high conveyance system inflow of 2914.71–3413.91 m³/d. The two sites differ markedly in recharge conditions, inflow characteristics, and water quality, requiring site-specific water management. This study provides engineering references for inflow hazard control, groundwater resource management, and ecological protection in pumped-storage projects across different climatic zones. Full article

Low-emission zones (LEZs) require cities to define policy rules, predict effects before deployment, and verify outcomes afterwards, yet mobility, emissions, meteorology, exposure, data governance, and public communication are commonly handled in separate systems. This paper presents envair360, a Physical Intelligence architecture and a four-stage, evidence-gated LEZ methodology connecting project definition, baseline feasibility, digital-twin design, deployment, and verified impact closure. A design-science method is combined with an operational case study of Cartagena, Spain, because the research object is both a socio-technical artefact and a context-dependent municipal deployment. The technology chain is selected to bridge complementary scales and functions: SUMO for link- and vehicle-level traffic, WRF and CHIMERE for meteorology and regional chemistry, MUNICH and street-canyon parameterisation for computationally tractable street resolution, model-output calibration anchored to measurements, and FIWARE/NGSI-LD for governed context exchange. The manuscript distinguishes city observations, peer-reviewed component validation, demonstrated platform capabilities, and policy or engineering targets. A Murcia component study reports lower hourly than daily agreement after deep-learning calibration (NO₂: $r=0.79$ hourly and $0.94$ daily; O₃: $r=0.85$ hourly and $0.97$ daily), illustrating the importance of temporal aggregation and transfer limits. Digitisation of the prior Madrid ozone-density figure indicates modal shifts of approximately +32.0 and +27.8 source-axis units at two stations; the supplied source does not permit a numerical NO_x bias estimate. A separate six-city export audit covers 24,384 records and 4064 street segments and demonstrates a common model-output schema, not predictive validation. In Cartagena, project documentation reports elevated PM₁₀/PM_2.5, urban heat and solar-radiation stress, and a plausible role for dry-climate dust resuspension, supporting a superblock-oriented LEZ proposal with a long-term 30% vehicular CO₂ reduction target. The paper’s specific contribution is the governed orchestration, evidence taxonomy, quality gates, reproducible lineage, explicit policy-scenario representation, and portable city-onboarding protocol; it does not claim that the individual scientific models, the Cartagena deployment, or the cited project targets originated in this manuscript. Full article

Surface soil moisture (SM) is the keystone variable of terrestrial ecohydrology. Yet, the rapid diversification and development of deep learning architectures for satellite SM estimation have outpaced practitioners’ capacity to select among them. This review synthesizes 37 deep learning studies from the SMAP era (2015–2026) across five architecture families (MLP and physics-informed neural networks [MLP/PINN], long short-term memory [LSTM] and gated recurrent unit [GRU] networks, convolutional neural networks [CNN], convolutional LSTM and graph neural networks [GNN], and Transformer-based models) to establish an architecture–task-matching framework that links each family to its dominant estimation niche. The analysis reveals consistent specializations: MLP/PINN models achieve competitive surface SM retrieval from satellite inputs; recurrent networks extend SMAP temporally (RMSE ≤ 0.035  ${\mathrm{m}}^3\hspace{0.17em}{\mathrm{m}}^{-3}$); CNN disaggregates SMAP to 1 km (reported unbiased root-mean-square error (ubRMSE) approaching 0.04  ${\mathrm{m}}^3\hspace{0.17em}{\mathrm{m}}^{-3}$); ConvLSTM and GNN address spatiotemporal gap-filling (low reported ubRMSE 0.022  ${\mathrm{m}}^3\hspace{0.17em}{\mathrm{m}}^{-3}$); and Transformers enable global multi-source fusion and decadal climate-scenario projection. Across all families, four physics-DL integration modes (hard architectural constraints, soft loss-function penalties, physics-as-input feature engineering, and physics-ML hybrid output fusion) consistently yield RMSE reductions of 8–50% relative to data-driven baselines. These findings provide a practitioner-oriented framework that is applicable to ecohydrological monitoring of plant water stress, agricultural drought, early flood warnings, and land–atmosphere coupling. Full article

Nature-based Solutions (NbS) are increasingly recognised as effective approaches for enhancing coastal resilience while simultaneously supporting biodiversity, ecosystem services, and, where appropriate, climate-change mitigation. Their importance is particularly evident in the Mediterranean Basin, a climate-change hotspot exposed to sea-level rise, coastal erosion, land subsidence, sediment deficits, and intense anthropogenic pressures. This review provides a structured evidence synthesis of NbS for Mediterranean coastal adaptation, integrating ecological, hydrodynamic, geomorphological, biodiversity, governance, and implementation perspectives. We examine the principal NbS typologies, including vegetated habitats, biogenic reefs, sediment-based interventions, and hybrid approaches, with particular attention to vulnerable microtidal systems such as coastal lagoons and subsiding shorelines, including the Venice Lagoon and the Emilia-Romagna coast. Drawing on peer-reviewed literature together with evidence from European LIFE projects and restoration initiatives, the review highlights how process-based interventions can restore ecosystem functioning, strengthen coastal resilience, and provide multiple ecosystem services. At the same time, the analysis emphasises that NbS are inherently context-dependent, with their effectiveness influenced by local geomorphology, sediment availability, hydrodynamic conditions, governance capacity, and long-term management. Although important scientific uncertainties remain, wider implementation is increasingly constrained by economic, institutional, and governance barriers. The review concludes that NbS should not be regarded as stand-alone alternatives to conventional engineering, but as key components of integrated and adaptive hybrid coastal management strategies capable of supporting resilient Mediterranean coastal systems under future climate change. Full article

Beach nourishment has become one of the principal soft-engineering strategies for mitigating coastal erosion while preserving the recreational, environmental and protective functions of sandy beaches. During the last four decades, Spain has accumulated extensive experience in beach nourishment, with annual nourishment volumes approaching 10 million m³ under a wide range of coastal settings. Many of the best-documented engineering examples originate from the Gulf of Cadiz, although the lessons synthesized here are interpreted within the broader context of Spanish coastal practice. This structured narrative review combines publications retrieved from Web of Science and Google Scholar with Spanish technical reports, project records, and institutional sources. It focuses on borrow-area characterization, sediment compatibility, construction quality control, post-nourishment monitoring, and adaptive management. Rather than providing a chronological description of nourishment projects, this review examines how repeated project implementation, monitoring and maintenance have progressively reduced uncertainty and improved engineering practice. Long-term nourishment performance is controlled more by sediment compatibility, local morphodynamics, and construction quality than by the total sediment volume placed. It also demonstrates that systematic monitoring provides the feedback required to improve future project design, optimize maintenance strategies and support evidence-based coastal management. The principal contribution of four decades of Spanish beach nourishment has been the progressive development of an engineering framework in which quality control, long-term monitoring and accumulated field experience continuously refine project planning and management. Although derived from Spanish practice, the lessons synthesized are broadly applicable to nourishment programs facing increasing pressures from climate change, sediment scarcity and growing environmental constraints. Full article

As an important infrastructure for the construction of a new power system, pumped-storage hydropower stations may exert certain impacts on the surrounding fractional vegetation cover (FVC) during their construction. Based on Landsat remote sensing imagery and China Land Cover Dataset (CLCD) land use data from 2013 to 2024, this study investigated the dynamic changes in FVC and the spatial extent of engineering disturbance associated with the Zhen’an Pumped-Storage Hydropower Station in Shaanxi Province, China. The analysis integrated the Pixel Dichotomy Model, Theil-Sen trend analysis, Mann–Kendall significance test, coefficient of variation, landscape pattern indices, and correlation analysis. The results showed that: (1) FVC in the study area exhibited distinct stage-dependent evolution characteristics that were highly consistent with the construction timeline of the project. (2) The spatial influence of engineering disturbance on FVC was mainly concentrated within 1250 m, with the 0–250 m zone identified as the core impact area. Landscape fragmentation in this zone was higher than in other distance ranges, and vegetation degradation gradually weakened with increasing distance from the project. (3) Land use change within the study area was primarily characterized by the conversion of forest to cropland and impervious surfaces, resulting in a reduction in high coverage vegetation areas. Landscape patterns exhibited pronounced buffer-gradient characteristics. Within 500 m, the Largest Patch Index (LPI) decreased while the Shannon Diversity Index (SHDI) increased, indicating weakened continuity of dominant landscape patches. Beyond 500 m, LPI generally increased and SHDI decreased, suggesting a trend toward a more stable landscape structure. (4) Both air temperature and precipitation exhibited interannual fluctuations, but neither showed a significant long-term trend. The correlations between climatic factors and FVC were relatively weak, and the multiple regression model demonstrated limited explanatory power for FVC variation. Full article

The digital transformation of Morocco’s construction sector requires new approaches to address increasing project complexity and evolving regulatory demands. This exploratory qualitative study investigates the integration of building information modeling (BIM) and artificial intelligence (AI) through eight semi-structured interviews with field engineers, design engineers, sector experts, and researchers. The interview data were analyzed using thematic analysis in NVivo, supported by systematic coding, lexical similarity analysis, and cross-matrix synthesis. The findings reveal that BIM implementation in Morocco remains predominantly at Level 1, despite unanimous recognition of its high perceived usefulness. This gap between perceived usefulness and actual adoption is primarily explained by economic, institutional, legal, and capacity-related barriers rather than technological limitations. Participants also reported successful BIM-based clash detection experiences, highlighting measurable returns on investment through reduced design conflicts, rework, and project coordination efforts. Furthermore, AI was consistently perceived as an augmentation technology that enhances professional expertise and decision-making rather than replacing human roles. Based on these findings, the study recommends establishing a national BIM mandate, developing a national BIM competence center, strengthening regulatory and legal frameworks, and promoting context-specific research and development to accelerate Morocco’s digital transition while adapting BIM and AI implementation to local technical, institutional, and climatic conditions. Future research should validate these findings through pilot implementation projects. Full article

Reliable medium–long-term wind energy projection is essential in the planning, financing, and operation of large-scale offshore wind development. This study classified projection methods into three categories: statistical/empirical and climate-signal-driven methods, dynamical models with reanalysis and regional downscaling, and machine/deep learning and hybrid methods for bias correction, downscaling, and direct data-driven projection. Then, this study reviewed the technical framework, representative studies, and comparative strengths and limitations. The main finding was that the state of the art increasingly converged on “dynamical simulation plus statistical or machine learning correction”. Next, seven main bottlenecks, along with the countermeasures, were systematically presented: (i) difficult data quality control and insufficient observational representativeness, especially offshore; (ii) divergent, even contradictory, conclusions for the same region across data sources and research groups; (iii) large uncertainty in extrapolating 10 m winds to the continually rising turbine hub height; (iv) difficulty in quantifying and communicating non-stationarity and uncertainty to decision-makers; (v) engineering conversion errors from projected “wind resource” to deliverable “electricity”; (vi) systematic biases in the marine atmospheric boundary layer, strong winds, and extreme conditions; and (vii) unresolved reliability, interpretability, and out-of-distribution generalization of AI models. Correspondingly, three mutually reinforcing strands of countermeasures were proposed: first, strengthening the observational and benchmarking foundation through unified, open, quality-controlled observation networks with data-provenance standards and shared reference datasets and intercomparison protocols; second, advancing physics–data integration and uncertainty quantification through hybrid and physics-informed correction, regime-specific bias correction of boundary-layer and extreme-wind errors, and probabilistic frameworks that delivered and clearly communicated credible intervals; and third, closing the resource-to-electricity gap by embedding power-curve convolution, wake-loss modeling, and availability and technology derating into the projection workflow, with the aim of improving medium–long-term wind energy projection accuracy. Full article

Residential buildings have been responsible for the increasing percentage of final energy consumption in Libya, which is mainly due to the cooling of buildings in hot arid climatic conditions, but there is still a constant discrepancy between the projected and actual energy performance. This review critically synthesises the available literature to find out the knowledge gaps underlying residential energy overconsumption, and it concentrates on the systemic loss of contact between the architectural design intent, material and envelope performance, construction execution, and occupant behaviour throughout the building lifecycle. The literature employed to complete the study is peer-reviewed journals, conference papers, and technical reports concerning Libya and similar hot-arid and Mediterranean settings, which are arranged into four overlapping areas, namely, design practices, materials and construction quality, regulatory enforcement, and occupant energy use patterns. The results show that the cumulative and reinforcing inefficiencies are caused by the lack of adoption of climate-sensitive designs, inattentive view of thermal material properties, ineffective control over the quality of construction, ineffective regulation enforcement, and neglect of the occupant behaviour in performance analysis, which contribute to the increase in cooling loads and expansion of the performance gap. Building a coherent conceptual structure using disjointed evidence, the review offers recommendations that can be applied in practice by architects, engineers, policymakers and housing stakeholders, highlighting the importance of lifecycle-based design methodologies, improved governance and performance energy strategies with behavioural elements in Libyan residential buildings. Full article

Expansive soils represent a critical challenge in geotechnical engineering due to their significant volumetric changes in response to moisture variations, which cause recurrent structural damage to foundations, pavements and infrastructure. The intensification of wet–dry cycles associated with climate change increases the likelihood of failures, reinforcing the need for more efficient and sustainable stabilization methods. Conventional techniques based on lime or salts present environmental and performance limitations when used independently. This study evaluates a combined approach using sodium chloride (NaCl) and lime sludge (LS), an abundant industrial by-product, to improve the behavior of expansive soils while simultaneously valorizing a difficult-to-manage waste material. Mixtures containing 3%, 6% and 9% NaCl and 5%, 10% and 15% LS were prepared. Atterberg limits, free swell, swelling pressure and infiltration tests were carried out to analyze the response of the treated soil. The results show significant reductions in plasticity and swelling potential: the liquid limit decreased by up to 35%, the plasticity index by up to 36% and the free swell by up to 65% for the optimal combination (9% NaCl + 15% LS). In addition, infiltration increased from 25 to 40 mm, indicating improved hydraulic behavior of the treated soil. The direct reuse of lime sludge prevented its disposal in landfills and reduced the environmental impact associated with its management. Overall, the findings demonstrate that the combination of NaCl and LS is an effective and economical alternative under short-term laboratory conditions, with potential for sustainable application subject to long-term validation for mitigating the swelling of expansive soils. Pilot-scale validation under extreme climatic conditions is recommended to advance toward its integration into resilient infrastructure projects. This approach offers a more efficient, cost-effective, and sustainable technical solution, distinguished by its dual action (chemical and recycling) and its contribution to waste valorization. Future research will focus on validating the method at the pilot scale and assessing its performance under extreme climatic conditions, consolidating its applicability in resilient infrastructure projects. Full article

High-plasticity clays (CH) are widely recognized in geotechnical engineering for their poor engineering behavior, including low shear strength, high compressibility, and swelling potential, yet their presence in infrastructure projects is often unavoidable. This study investigates a sustainable alternative to ordinary Portland cement (OPC) by evaluating the durability of soil–geopolymer mixtures (SGMs) incorporating quarry dust (QD), an industrial by-product from sand and gravel operations in the Philippines. Durability assessment was emphasized due to the country’s tropical climate, marked by alternating wet and dry seasons that may accelerate deterioration of stabilized soils. QD was activated using sodium silicate (SS) and sodium hydroxide (SH) and blended with CH to form SGMs. Index property tests were conducted to characterize raw materials and identify optimal mix proportions. After 28 days of curing, specimens were subjected to wetting–drying (WD) cycles consisting of 5 h of water submersion and 42 h of oven-drying at 70 °C. Mass loss and surface degradation were evaluated by brushing in accordance with ASTM procedures. The SGMs exhibited an average mass loss of 6.83% after 12 WD cycles, satisfying the Portland Cement Association (PCA) criterion of less than 7.00% for stabilized clays. These results demonstrate that QD-based geopolymers are a viable and sustainable stabilizer for CH soils in tropical environments. Full article