Search Results (244)

With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty fades for users, the usage frequency declines, resulting in considerable resource wastage. This research collected user needs via surveys and employed the KJ method (affinity diagram) to synthesize fragmented insights into cohesive thematic clusters. Subsequently, a hierarchical needs model for electric scooters was constructed using analytical hierarchy process (AHP) principles, enabling systematic prioritization of user requirements through multi-criteria evaluation. By establishing a house of quality (HoQ), user needs were transformed into technical characteristics of electric scooter products, and the corresponding weights were calculated. After analyzing the positive and negative correlation degrees of the technical characteristic indicators, it was found that there are technical contradictions between functional zoning and compact size, lightweight design and material structure, and smart interaction and usability. Then, based on the theory of inventive problem solving (TRIZ), the contradictions were classified, and corresponding problem-solving principles were identified to achieve a multi-functional innovative design for electric scooters. This research, leveraging a systematic industrial design analysis framework, identified critical pain points among electric scooter users, established hierarchical user needs through priority ranking, and improved product lifecycle sustainability. It offers novel methodologies and perspectives for advancing theoretical research and design practices in the electric scooter domain. Full article

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative porcelain sheathing system for cold-formed steel (CFS) shear walls. Porcelain has no veins thus it offers integrated and reliable strength unlike granite. Four full-scale CFS shear walls incorporating screwed porcelain sheathing (SPS) were tested under combined cyclic lateral and constant gravity loading. The experimental program investigated key seismic characteristics, including lateral stiffness and strength, deformation capacity, failure modes, and energy dissipation, to calculate the system response modification factor (R). The test results showed that configurations with horizontal sheathing, double mid-studs, and three blocking rows improved performance, achieving up to 21.1 kN lateral resistance and 2.5% drift capacity. The average R-factor was 4.2, which exceeds the current design code values (AISI S213: R = 3; AS/NZS 4600: R = 2), suggesting the enhanced seismic resilience of the SPS-CFS system. This study also proposes design improvements to reduce the risk of brittle failure and enhance inelastic behavior. In addition, the results inform discussions on permissible building heights and contribute to the advancement of CFS design codes for seismic regions. Full article

This study aims to enhance the performance of an innovative steel slag–ceramsite foam concrete (SSCFC) to advance sustainable green building materials. An eco-friendly composite construction material was developed by integrating industrial by-product steel slag (SS) with lightweight ceramsite. Employing a three-factor, three-level orthogonal experimental design at a fixed density of 800 kg/m³, 12 mix proportions (including a control group) were investigated with the variables of water-to-cement (W/C) ratio, steel slag replacement ratio, and ceramsite replacement ratio. The governing mechanisms of the W/C ratio, steel slag replacement level, and ceramsite replacement proportion on the SSCFC’s fluidity and compressive strength (CS) were elucidated. The synergistic application of range analysis and analysis of variance (ANOVA) quantified the significance of factors on target properties, and partial least squares regression (PLSR)-based prediction models were established. The test results indicated the following significance hierarchy: steel slag replacement > W/C ratio > ceramsite replacement for fluidity. In contrast, W/C ratio > ceramsite replacement > steel slag replacement governed the compressive strength. Verification showed R² values exceeding 65% for both fluidity and CS predictions versus experimental data, confirming model reliability. Multi-criteria optimization yielded optimal compressive performance and suitable fluidity at a W/C ratio of 0.4, 10% steel slag replacement, and 25% ceramsite replacement. Full article

In engineering design, optimization is crucial for achieving sustainable goals. This involves creating environmentally responsible structures. Optimizing the design is the first step in reducing the environmental impact of construction. Topology optimization (TO) is one way to do this. TO is the process of designing the material layout in the design domain according to selected criteria. The criteria can be explicitly defined to promote sustainability. As a result, a new structure topology is proposed to make the structure both lightweight and durable, with the aim of improving its functionality and reducing its environmental impact. In optimal engineering design, it is particularly important to take into account the structure’s special operating conditions, e.g., loads subject to random changes. Predicting topologies under such conditions is important since random load changes can significantly affect the resulting topologies. In this paper, an easy to implement numerical method for this kind of problem is proposed. The basic idea is to transform a random loads case into the deterministic problem of multiple loads. A heuristic method of Cellular Automata is proposed as a numerical optimization tool. The examples of topology optimization have been performed to illustrate the concept, confirming the efficiency, versatility, and ease of its implementation. Full article

Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. The accurate detection of major fruit characteristics, including flowering, green fruiting, and ripening stages, is crucial for early yield estimation. Currently, most crop yield estimation studies based on the YOLO model are only conducted during a single stage of maturity. Combining multi-growth period data for crop analysis is of great significance for crop growth detection and early yield estimation. In this study, a new network model, YOLOv8-RL, was proposed using citrus multigrowth period characteristics as a data source. A citrus yield estimation model was constructed and validated by combining network identification counts with manual field counts. Compared with YOLOv8, the number of parameters of the improved network is reduced by 50.7%, the number of floating-point operations is decreased by 49.4%, and the size of the model is only 3.2 MB. In the test set, the average recognition rate of citrus flowers, green fruits, and orange fruits was 95.6%, the mAP@.5 was 94.6%, the FPS value was 123.1, and the inference time was only 2.3 milliseconds. This provides a reference for the design of lightweight networks and offers the possibility of deployment on embedded devices with limited computational resources. The two estimation models constructed on the basis of the new network had coefficients of determination R² values of 0.91992 and 0.95639, respectively, with a prediction error rate of 6.96% for citrus green fruits and an average error rate of 3.71% for orange fruits. Compared with network counting, the yield estimation model had a low error rate and high accuracy, which provided a theoretical basis and technical support for the early prediction of fruit yield in complex environments. Full article

This study presents a cost-effective, carbon-negative construction material for affordable housing, developed entirely from locally available agricultural wastes: rice husk ash, wood ash, and rice straw—materials often problematic to dispose of in many African regions. Rice husk ash provides high amorphous silica, acting as a strong pozzolanic agent. Wood ash contributes calcium oxide and alkalis to serve as a reactive binder, while rice straw functions as a lightweight organic filler, enhancing thermal insulation and indoor climate comfort. These materials undergo natural pozzolanic reactions with water, eliminating the need for Portland cement—a major global source of anthropogenic CO₂ emissions (~900 kg CO₂/ton cement). This process is inherently carbon-negative, not only avoiding emissions from cement production but also capturing atmospheric CO₂ during lime carbonation in the hardening phase. Field trials in Kenya confirmed the composite’s sufficient structural strength for low-cost housing, with added benefits including termite resistance and suitability for unskilled laborers. In a collaboration between the University of Tartu and Kenyatta University, a semi-automatic mixing and casting system was developed, enabling fast, low-labor construction of full-scale houses. This innovation aligns with Kenya’s Big Four development agenda and supports sustainable rural development, post-disaster reconstruction, and climate mitigation through scalable, eco-friendly building solutions. Full article

Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to ensure healthy and favorable conditions for human life but also to the need for the rational use of energy resources. This area is becoming particularly relevant in the context of global challenges related to climate change, rising energy costs and increased environmental requirements. Practice shows that any technical solutions to ensure comfortable temperature, humidity and air exchange in rooms should be closely linked to the concept of energy efficiency. This allows one not only to reduce operating costs but also to significantly reduce greenhouse gas emissions, thereby contributing to sustainable development and environmental safety. In this connection, this study presents a parametric assessment of the influence of climatic and geometric factors on the aerodynamic characteristics of the air cavity, which affect the heat exchange process in the ventilated layer of curtain wall systems. The assessment was carried out using a combined analytical calculation method that provides averaged thermophysical parameters, such as mean air velocity ($V_s$), average internal surface temperature ($t_{in.s}^{av}$), and convective heat transfer coefficient (${\alpha }_s$) within the air cavity. This study resulted in empirical average values, demonstrating that the air velocity within the cavity significantly depends on atmospheric pressure and façade height difference. For instance, a 10-fold increase in façade height leads to a 4.4-fold increase in air velocity. Furthermore, a three-fold variation in local resistance coefficients results in up to a two-fold change in airflow velocity. The cavity thickness, depending on atmospheric pressure, was also found to affect airflow velocity by up to 25%. Similar patterns were observed under ambient temperatures of +20 °C, +30 °C, and +40 °C. The analysis confirmed that airflow velocity is directly affected by cavity height, while the impact of solar radiation is negligible. However, based on the outcomes of the analytical model, it was concluded that the method does not adequately account for the effects of solar radiation and vertical temperature gradients on airflow within ventilated façades. This highlights the need for further full-scale experimental investigations under hot climate conditions in South Kazakhstan. The findings are expected to be applicable internationally to regions with comparable climatic characteristics. Ultimately, a correct understanding of thermophysical processes in such structures will support the advancement of trends such as Lightweight Design, Functionally Graded Design, and Value Engineering in the development of curtain wall systems, through the optimized selection of façade configurations, accounting for temperature loads under specific climatic and design conditions. Full article

The automated detection and classification of immature macauba (Acrocomia aculeata) fruits is critical for improving post-harvest processing and quality control. In this study, we present a comparative evaluation of two state-of-the-art YOLO architectures, YOLOv11x and YOLOv12x, trained on the newly constructed VIC01 dataset comprising 1600 annotated images captured under both background-free and natural background conditions. Both models were implemented in PyTorch and trained until the convergence of box regression, classification, and distribution-focal losses. Under an IoU (intersection over union) threshold of 0.50, YOLOv11x and YOLOv12x achieved an identical mean average precision (mAP₅₀) of 0.995 with perfect precision and recall or TPR (true positive rate). Averaged over IoU thresholds from 0.50 to 0.95, YOLOv11x demonstrated superior spatial localization performance (mAP_50–95 = 0.973), while YOLOv12x exhibited robust performance in complex background scenarios, achieving a competitive mAP_50–95. Inference throughput averaged 3.9 ms per image for YOLOv11x and 6.7 ms for YOLOv12x, highlighting a trade-off between speed and architectural complexity. Fused model representations revealed optimized layer fusion and reduced computational overhead (GFLOPs), facilitating efficient deployment. Confusion-matrix analyses confirmed YOLOv11x’s ability to reject background clutter more effectively than YOLOv12x, whereas precision–recall and F1-score curves indicated both models maintain near-perfect detection balance across thresholds. The public release of the VIC01 dataset and trained weights ensures reproducibility and supports future research. Our results underscore the importance of selecting architectures based on application-specific requirements, balancing detection accuracy, background discrimination, and computational constraints. Future work will extend this framework to additional maturation stages, sensor fusion modalities, and lightweight edge-deployment variants. By facilitating precise immature fruit identification, this work contributes to sustainable production and value addition in macauba processing. Full article

This study assessed the feasibility of producing lightweight aggregates (LWAs) using diatomite waste (DW) as a clay substitute. The research aimed to reduce the consumption of natural resources and minimise the environmental impacts caused by the disorderly disposal of DW. Chemical, physical, and mechanical tests were carried out on six formulations of mixtures containing 50% to 100% DW, sintered between 1100 and 1250 °C, resulting in 24 samples. The aggregates had a particle density between 1.14 and 2.13 g/cm³, a maximum bloating index of 5.7%, a crushing strength of up to 11.14 MPa, and a mass loss of up to 8.7%. Minimum porosity of 2.8 percent and water absorption of 2.0 percent were observed. Sixteen samples met the criteria required for commercial applications, demonstrating that replacing clay with DW is technically feasible. The high porosity of DW was found to influence the density of the LWAs. The findings of this study highlight the environmental sustainability of using DW as an alternative raw material, contributing to circular economy strategies in the construction sector. Full article

This study investigates the feasibility of pumice-based internal curing based on the 3D printability of engineered cementitious composites (ECCs) for water-scarce environments and arid regions. Natural river sand was partially replaced with the presoaked pumice lightweight aggregates (LWAs) at two different levels, 30% and 60% by volume, and 50% of the cement was replaced with slag to enhance sustainability. Furthermore, 2% polyethylene (PE) fibers were used to improve the mechanical characteristics and 1% methylcellulose (MC) was used to increase the rheological stability. Pumice aggregates, presoaked for 24 h, were used as an internal curing agent to assess their effect on the printability. Three ECC mixes, CT-PE2-6-10 (control), P30-PE2-6-10 (30% pumice), and P60-PE2-6-10 (60% pumice), were printed using a 3D gantry printing system. A flow table and rheometer were used to evaluate the flowability and rheological properties. Extrudability was measured in terms of dimensional consistency and the coefficient of variation (CV%) to evaluate printability, whereas buildability was determined in terms of the maximum number of layers stacked before failure. All of the mixes met the extrudability criterion (CV < 5%), with P30-PE2-6-10 demonstrating superior printing quality and buildability, having 16 layers, which was comparable with the control mix that had 18 layers. Full article

Accurate spatial mapping of Tailing Impoundments (TIs) is vital for environmental sustainability in mining ecosystems. While remote sensing enables large-scale monitoring, conventional methods relying on single-sensor data and traditional machine learning-based algorithm suffer from reduced accuracy in cluttered environments. This research proposes a deep learning framework leveraging multi-source high-resolution imagery to address these limitations. An upgraded You Only Look Once (YOLO) model is introduced, integrating three key innovations: a multi-scale feature aggregation layer, a lightweight hierarchical fusion mechanism, and a modified loss metric. These components enhance the model’s ability to capture spatial dependencies, optimize inference speed, and ensure stable training dynamics. A comprehensive dataset of TIs across varied terrains was constructed, expanded through affine transformations, spectral perturbations, and adversarial sample synthesis. Evaluations confirm the framework’s superior performance in complex scenarios, achieving higher precision and computational efficiency than state-of-the-art detectors. Full article

Autoclaved Aerated Concrete (AAC) is a lightweight, thermally insulating, and fire-resistant building material that has become prominent in sustainable construction due to its reduced production energy demands and minimal environmental impact. As an increasing number of AAC-based structures reach end-of-life, the effective recycling and reuse of AAC waste present both challenges and opportunities within the context of sustainable building practices and circular economy frameworks. This study presents a scientometric review of AAC recycling research published between 2014 and 2024, using the Web of Science database and bibliometric tools such as CiteSpace. Key trends, techniques, and knowledge gaps in AAC recycling are identified, highlighting issues such as high energy consumption, limited practical implementation, and the absence of standardized recovery protocols. The study also outlines emerging research pathways, including detailed material characterization, development of recycling standards, innovative reuse techniques, hybrid material systems, and the integration of recycled AAC in new construction. These insights provide a foundation for advancing sustainable building material strategies and inform policy and practice in construction waste management. Full article

The rapid growth of the wind energy sector has led to a rising number of retired wind turbine blades (RWTBs) globally, posing significant environmental and logistical challenges for sustainable waste management. Handling enormous RWTBs at their end of life (EoL) has a significant negative impact on resource conservation and the environment. Conventional disposal methods, such as landfilling and incineration, raise environmental concerns due to the non-recyclable composite material used in blade manufacturing. This study explores the upcycling potential of RWTBs as innovative construction materials, addressing both waste reduction and resource efficiency in the construction industry. By exploring recent advancements in recycling techniques, this research highlights applications such as structural components, lightweight aggregates for concrete, and reinforcement elements in asphalt pavements. The key findings demonstrate that repurposing blade-derived materials not only reduces landfill dependency but also lowers carbon emissions associated with conventional construction practices. However, challenges including material compatibility, economic feasibility, and standardization require further investigation. This study concludes that upcycling wind turbine blades into construction materials offers a promising pathway toward circular economy goals. To improve technical methods and policy support for large-scale implementation, it recommends collaboration among different fields, such as those related to cementitious and asphalt materials. Full article

As a promising and sustainable construction material, alkali-activated slag lightweight high-strength concrete (AAS-LWHSC) may be influenced by lightweight aggregate (LWA) content. In this study, the effects of hollow glass microspheres (HGM) replacing granulated ground blast furnace slag (GGBFS) under varying LWA dosages on the workability, dry apparent density, mechanical properties, and microstructure of AAS-LWHSC were investigated. The results indicated that the dry density of concrete was significantly reduced by HGM, while the “ball-bearing” effect of HGM was observed to enhance workability at a dosage of 6%. The 7-day mechanical properties of AAS-LWHSC were found to decline progressively with increasing HGM content. However, at the shale ceramsite sand replacement rates of 35% and 65%, the incorporation of 6% HGM slightly improved the 28-day mechanical properties. Due to the absence of the water-releasing effect from shale ceramsite, the pozzolanic reactions of HGM were restricted, resulting in coarse hydration products and a reduction in the mechanical performance of AAS-LWHSC. Full article

This paper presents LokAlp, a modular timber construction system invented and developed by the authors, inspired by the traditional Blockbau technique, and designed for circularity and self-construction. LokAlp utilizes standardized interlocking blocks fabricated from CLT and GLT off-cuts to optimize material reuse and minimize waste. The study explores the application of massive timber digital materials within an open modular system framework, offering an alternative to the prevailing focus on lightweight structural systems, which predominantly rely on primary engineered wood materials rather than reclaimed by-products. The research evaluates geometric adaptability, production feasibility, and on-site assembly efficiency within a computational design and digital fabrication workflow. The definition of the LokAlp system has gone through several iterations. A full-scale demonstrator constructed using the LokAlp final iteration (Mk. XII) incorporated topological enhancements, increasing connection variety and modular coherence. Comparative analyses of subtractive manufacturing via 6-axis robotic milling versus traditional CNC machining revealed a >45% reduction in cycle times with robotic methods, indicating significant potential for sustainable industrial fabrication; however, validation under operational conditions is still required. Augmented reality-assisted assembly improved accuracy and reduced cognitive load compared to traditional 2D documentation, enhancing construction speed. Overall, LokAlp demonstrates a viable circular and sustainable construction approach combining digital fabrication and modular design, warranting further research to integrate robotic workflows and structural optimization. Full article