Search Results (2,559)

This paper explores the replanning, reconstruction, and rebranding of Austro-Hungarian military buildings, encompassing common military administrative, healthcare, and housing facilities as well as railways that were under military jurisdiction, and their profound influence on the development of Banja Luka, Bosnia and Herzegovina. These structures, originally built for military and logistic purposes during the Austro-Hungarian period (1878–1918), played a pivotal role in shaping the city’s urban and architectural landscape. The study employs historical analysis of archival documents, maps, and photographs, combined with contemporary field observations that assess the current state and adaptive reuse of these buildings. This approach allows for a comprehensive understanding of the buildings’ transformation over time, from symbols of military authority to cultural and social landmarks within the city. The key periods of transformation—between 1945–1991 and post-1995—were largely driven by changes in national politics, military ownership, and local urban development policies that promoted the urbanization of unused military zones. The findings reveal a dynamic process of adaptive reuse, wherein the rebranding of these historical edifices has repurposed them into cultural, educational, and public spaces. These adaptive transformations not only preserved the architectural integrity of the buildings but also revitalized their roles in the community. The study concludes that Banja Luka’s experience serves as a model for sustainable heritage management, demonstrating the balance between historical preservation and modern urban development. The results highlight how the city successfully merged its rich architectural past with contemporary needs, contributing to its cultural identity and urban growth. Full article

This study presents a comprehensive bibliometric analysis of the earthen architecture and construction scientific literature production at present, analysing the historical evolution, research patterns and trends and the investigation of the different existing earthen building technologies. Utilising the SCOPUS database, this study analysed 3804 documents published between 1968 and 2023, with an annual growth of 16.92% since the year 2001. Key findings include the identification of top authors, institutions and collaborative networks, the co-citation analysis and the main keyword analysis and classification into different clusters. Regarding the building technologies, the results indicate a prevalence of research on vernacular earthen building techniques, mainly rammed earth and adobe masonry. Nevertheless, a growing interest in innovative methods using earth-based materials can be spotted. The bibliometric analysis identifies the development of the academic interest and emphasises the importance of interdisciplinary collaboration and the need for international recognition of earthen buildings. Future research should continue to explore the environmental benefits of using earthen materials, the development of earthen building techniques and systems in modern industry and the preservation of the architectural heritage and vernacular knowledge of contemporary technology. Full article

The Building Condition Index (BCI) is a widely adopted quantitative metric for assessing various aspects of a building’s condition, as it facilitates decision-making regarding maintenance, capital improvements and, most importantly, the identification of investment risk. In practice, longitudinal BCI scores are typically used to identify maintenance liabilities and trends and proactively provide indications when maintenance strategies need to be altered. This allows for a more efficient resource allocation and helps maximise the lifespan and functionality of buildings and their assets. Given the historical ambiguity concerns because of the reliance on visual inspections, this research investigates how AI and using ANN, DNN and CNN can improve the predictive accuracy of determining a recognisable Building Condition Index. It demonstrates how ANN and DNN perform over asset classes (apartment complexes, education and commercial buildings). The results suggest that DNN architecture is adept at dealing with diverse and complex datasets, thus enabling a more versatile BCI prediction model over various building categories. It is envisaged that with the expansion and maturity of ANN, DNN and CNN, the BCI calculation methodologies will become more sophisticated, automated and integrated with traditional assessment approaches. Full article

Historic building information modeling (HBIM) represents an emerging field that extends traditional building information modeling (BIM) to the preservation, management, and analysis of heritage structures. This paper provides a comprehensive overview of HBIM, tracing its evolution from its origins and early applications to its current state and future prospects. The processes of data collection and modeling are thoroughly examined, addressing levels of detail, digitization methods, and commonly used software and data formats. Attention is also given to existing BIM standards and protocols and their potential application to HBIM. The paper emphasizes the importance of appropriate data selection and management, both for geometrical and non-geometrical (historical and architectural) information. Furthermore, it explores the integration of HBIM with structural analysis tools, a subject of growing interest, particularly in light of its potential for integration with structural health monitoring systems and advanced computational models. The results of this review highlight the increasing role of HBIM in heritage preventive preservation and management, a topic that accounted for 40% of the articles on this subject in 2023. These findings demonstrate that HBIM offers significant potential for managing and preserving heritage buildings, but to fully realize its capabilities, advancements in data interoperability, standardized protocols, and real-time structural analysis are essential to make it a widely effective tool in conservation efforts. Full article

Probabilistic time series forecasting is crucial in various fields, including reducing stockout risks in retail, balancing road network loads, and optimizing power distribution systems. Building forecasting models for large-scale time series is challenging due to distribution differences, amplitude fluctuations, and complex patterns across various series. To address these challenges, a probabilistic forecasting method with two different implementations that focus on historical segment importance is proposed in this paper. First, a patch squeeze and excitation (PSE) module is designed to preprocess historical data, capture segment importance, and distill information. Next, an LSTM-based network is used to generate maximum likelihood estimations of distribution parameters or different quantiles for multi-step forecasting. Experimental results demonstrate that the proposed PSE module significantly enhances the base model’s prediction performance, and direct multi-step forecasting offers more detailed information for high-frequency data than recursive forecasting. Full article

Public transit systems are critical to the quality of urban life, and enhancing their efficiency is essential for building cost-effective and sustainable smart cities. Historically, researchers sought reinforcement learning (RL) applications to mitigate bus bunching issues with holding strategies. Nonetheless, these attempts often led to oversimplifications and misalignment with the goal of reducing the total time passengers spent in the system, resulting in less robust or non-optimal solutions. In this study, we introduce a novel setting where each bus, supervised by an RL agent, can appropriately form aggregated policies from three strategies (holding, skipping station, and turning around to serve the opposite direction). It’s difficult to learn them all together, due to learning complexity, we employ domain knowledge and develop a gradually expanding action space curriculum, enabling agents to learn these strategies incrementally. We incorporate Long Short-Term Memory (LSTM) in our model considering the temporal interrelation among these actions. To address the inherent uncertainties of real-world traffic systems, we impose Domain Randomization (DR) on variables such as passenger demand and bus schedules. We conduct extensive numerical experiments with the integration of synthetic and real-world data to evaluate our model. Our methodology proves effective, enhancing bus schedule reliability and reducing total passenger waiting time by over 15%, thereby improving bus operation efficiency and smoothering operations of buses that align with sustainable goals. This work highlights the potential of robust RL combined with curriculum learning for optimizing public transport in smart cities, offering a scalable solution for real-world multi-agent systems. Full article

The quality of indoor air is dependent on a number of factors, including the presence of microorganisms that colonize the building materials. The potential for health risks associated with microbial contamination is a significant concern during the renovation of buildings. The aim of this study was to assess the impact of two reconstruction methods for historic buildings on air quality. The two reconstruction procedures were facadism, which preserves only the façade, demolishing the rest of the building and constructing a new building, and complete reconstruction, which involves internal renovation with a less intensive demolition. A total of 70 + 70 air samples, as well as surface and dust samples, were collected throughout the course of the reconstruction of the two buildings. In the case of facadism, total colony counts were found to be 2–4 times higher indoors than outdoors, even at the initial stage of the works. High concentrations of Aspergillus and Penicillium spp. were detected. During the less intensive reconstruction, the total colony count in the indoor air samples was initially lower at almost every sampling point than at the outdoor levels. With regard to fungi, Penicillium species were initially present at lower conidia concentrations, followed by Aspergillus species over time. In both buildings, elevated concentrations of airborne fungi were detected during the main reconstruction period. The fungal genera found in the indoor air were also detected on surfaces and in dust samples. Outdoor air samples collected from the vicinity of the buildings revealed elevated fungal counts at multiple sampling points, particularly in the case of facadism. Disinfection with dry fogging was implemented twice throughout the entire interior of the buildings. Following the first disinfection process, there was no notable decrease in colony-forming unit (CFU) counts in either building. However, the second disinfection resulted in a reduction in microbial concentration in the air. Our study confirms that the renovation of historical buildings can result in an elevated prevalence of fungal bioaerosols, which can be harmful to occupants. While the impact of the reconstruction remained within the range of urban background variability at distant (>1 km) locations, it caused local microbial contamination, often exceeding the detection limit in near-site samples. Full article

The existing built heritage is excessively energy intensive compared to the standards required by European policies that promote zero- or near-zero-energy buildings. Hence the need to promote a radical energy requalification of the existing stock through ad hoc solutions. In the modelling of buildings undergoing redevelopment, the boundary conditions considered by the designer are often underestimated, resulting in a digital model that does not perfectly adhere to reality, due to a lack of historical and documentary knowledge. The present work—which concerns the Santa Maria Micaela residential complex built in Valencia by architect Santiago Artal Ríos, a representative work of Spanish Modernism—aims to overcome this vulnus with modelling that also takes into account historical and archive information. The housing complex was studied using a multidisciplinary approach with historical–archival analyses and site surveys that allowed BIM modelling and localisation in a WEB-GIS platform. The modelling took into account the peculiarities of the original design (exposure, windiness, and shading) and data from historical research (stratigraphy of building elements, dimensions, types of materials). The energy simulation, on the other hand, referred to a representative dwelling unit of the complex, and using SolidWorks software the ventilation flows were evaluated, which made it possible to create a model that was more in keeping with reality and to more correctly identify the performance upgrading proposal. The energy improvement was then evaluated according to the hypothesised interventions using two different analysis methodologies, TerMus and CE3X, for direct comparison. The transposition into WebGIS then made it possible to assess the potential of a digital platform to enhance information sharing. Full article

In coastal regions, groundwater is often the only freshwater resource available for human consumption, agriculture, and other productive activities. From a management point of view, it is essential to understand the processes that occur in a coastal aquifer affected by seawater intrusion and upconing processes and evaluate their potential response to climate change as these scenarios usually indicate a decrease in aquifer recharge. Therefore, the dynamics of seawater intrusion and the upconing process in the Plana de Castellón aquifer on the Mediterranean coast were analysed by building and calibrating a new numerical model of flow and transport using the MODFLOW and SEAWAT codes. The model was used to examine two Shared Socioeconomic Pathway (SSP) climate change scenarios (SSP1–2.6 and SSP5–8.5) when considering field data with constant extraction conditions. The results suggest that by 2050, groundwater levels could rise by 0.18 m (on average) in the SSP1–2.6 scenario and by 0.12 m for the SSP5–8.5 scenario. In these cases, aquifer recharge and groundwater discharge to the sea could increase compared to the historical period, as precipitation is not expected to decrease significantly during this timeframe, even in the most unfavourable scenario (SSP5–8.5). The result would be the attenuation of seawater intrusion and a decrease in the volume of the aquifer that is affected by the upconing process, resulting in total dissolved solids values below 2000 mg/L. The innovation of this research lies in the fact that the numerical model allowed the dynamics of seawater intrusion and the upconing process to be adequately represented, especially in the latter process, as it was not possible to model it with real data in another study. These results can improve and facilitate decision-making for the management of the aquifer and contribute to plans for future exploitation strategies. Full article

Masonry structures, particularly those used in developing countries and in historic buildings, typically consist of unreinforced masonry (URM) walls connected by timber or reinforced concrete elements. This study proposes enhancements to the existing two-dimensional (2D) deformable frame model (DFM) to enhance its ability in simulating masonry walls with a specific focus on accurately predicting the transient dynamic response of three-dimensional (3D) masonry structures while maintaining a minimal number of degrees of freedom (DOF). For the modeling of URM walls, the DFM framework employs elastic beams and diagonal struts with nonlinear constitutive behavior. Structural elements, such as reinforced concrete or timber reinforcements, are represented using conventional beam finite elements. This paper first reviewed the current DFM configuration, which primarily addresses the in-plane (IP) behavior of URM structures. It then introduced modifications tailored for 3D structural analysis. The reliability of the enhanced model was validated through two approaches. First, a modal analysis compared the results from the updated DFM with those from a reference 3D model based on cubic finite elements. Second, a shaking table experiment conducted on a half-scale masonry house was simulated. The findings demonstrate that, despite its limited number of DOF, the updated DFM effectively captures the main natural vibration modes. Furthermore, it shows the model’s ability to predict the nonlinear transient dynamic response of 3D masonry structures with accuracy and limited computational time. Full article

The seismic vulnerability of reinforced concrete (RC) buildings has been an important issue, especially in earthquake-prone regions with limited seismic design codes such as South Sudan. Improving the seismic performance of reinforced concrete buildings is critical for maintaining structural functionality under normal service loads and for rapid recovery after natural disasters such as earthquakes. This research aims to thoroughly assess the methods used to evaluate the seismic vulnerability of RC frame structures in pre- and post-earthquake scenarios. The primary objective is to provide a comprehensive framework that integrates empirical, analytical, and experimental methods, categorizing existing assessment methods and proposing improvements for resource-constrained environments. However, empirical methods have always used historical earthquake data to estimate potential damage. In contrast, analytical methods have used computational tools such as fragility curves to assess the probability of damage at different seismic intensities. Additionally, experimental methods, such as shaking table tests and pseudo-dynamic analyses, have validated theoretical predictions and provided insights into structural behavior under simulated conditions. Furthermore, key findings highlight critical vulnerabilities in RC buildings, quantify damage probabilities, and compare the strengths and limitations of different assessment methods. However, challenges such as limited data availability, computational limitations, and difficulties replicating actual conditions in test setups highlight areas for improvement. By addressing these challenges, the review provides recommendations for future studies, including integrating advanced computational and regional hazard characterization methods, improving experimental methods to enhance the accuracy of vulnerability assessments, and ultimately supporting the design of more resilient RC structures and increasing disaster preparedness. Full article

The article investigates HVAC (heating, ventilation, and air conditioning) technologies aimed at mitigating Primary Energy (PE) consumption in renovated buildings. This research is part of a broader initiative focused on enhancing air quality and reducing the carbon footprint within the fields of architecture and urban planning. Conducted since 2018 by a team from the Institute of Architectural Design at the Department of Contemporary Architecture, Faculty of Civil Engineering and Architecture, University of Technology in Lublin, the study exemplifies the application of these technologies at the historic Marshal Piłsudski’s “Milusin” Manor House in Sulejówek, near Warsaw. The primary objective of this research is to present HVAC solutions, particularly a free cooling and heating system, which are specifically tailored for the renovation of historic structures. This technology effectively recovers thermal energy from groundwater, achieving low energy consumption levels while simultaneously minimizing CO₂ emissions. Full article

In the process of developing mature deposits, a number of geological and technological complications arise. In order to increase the smooth operation of downhole pumping equipment in oil and gas wells, companies use various methods and techniques. This article presents a novel methodology for predicting downhole pumping equipment failures. A detailed analysis was conducted on historical data regarding downhole pumping equipment failures, which were then incorporated into algorithms to calculate the operation of downhole equipment. As a result, it was discovered that in order to predict failures of downhole equipment, it is crucial to consider the historical data of the field and perform an assessment of the well’s potential. In the process of building a failure prediction model, the authors encountered the quality and completeness of historical data from the pilot field. They concluded that the data classes needed to be more balanced. The authors applied machine learning approaches to an imbalanced dataset. The significance of our approach lies in its ability to forecast equipment failures, thereby ensuring the smooth operation of wells operated by sucker rod pumps. Full article

This experimental study explores the possibility of using an existing Trombe wall as a space for year-round cultivation to increase building resource efficiency. To do so with the least cost to the building, a small 0.75 m²/5.45 m³ Trombe wall cavity space was retrofitted with shelves placed behind the glazing, additional ventilation, and a watering network to be able to grow 400 hydroponic Kratky basil plants in individual glass jars. Historical thermal observations made at the site over a year-long timespan were contrasted with the experimental readings. When fully equipped, the Trombe wall’s thermal mass increased by 51%, which had a balancing effect on the system, lowering the average daily thermal oscillations from 35.41 °C to 17.88 °C. The living plants and water have also had significant cooling (26.99 °C to 22.91 °C) and humidifying (39.88 to 47.74%) effects. The system’s energy efficiency, however, decreased from 26 to 18% (absorption) and from 85 to 46 (dissipation), lowering its energy contribution to the building by about 30%. The average plant’s lifespan within the Trombe wall was 46 days, with 15% of the specimens surpassing the 100-day mark. Over the course of a year, 20.55 kg of edible greens were grown in the Trombe wall. The experiment has shown that it is possible to grow the plants inside the Trombe wall cavity during the warmer half of the year, revealing many possible ways to improve the space’s comfort, yields, and energy efficiency. Full article

Historical building reuse is aimed at preservation, where buildings are recovered for new uses connected to cultural activities. This paper presents the analysis of the impact of thermo-fluid dynamics due to a 500 kW electrical power transformer installed inside a historical building. The analysis is performed using computational fluid dynamics simulations validated through measurement campaigns carried out during the summer period. High temperatures and wide humidity variations can damage building plasters and cause malfunctions in power equipment. To avoid these situations, two different installation layouts were studied. One consists of the power transformer directly installed in the environment and cooled by an inlet fan, and the other consists of the power transformer being insulated from the external environment by an enclosure connected to a forced ventilation system. The second layout showed better results both inside and outside the transformer enclosure. The maximum indoor condition was about 4.3 °C, with a −7.2% RH and an airflow rate of 1100 m³/h, and the maximum outdoor air condition was 3.3 °C, with a −1.39% RH and a flow rate of 2200 m³/h. However, the temperatures and humidity inside the building and outside the transformer enclosure were almost the same. Full article