Cem Kırlangıçoğlu

Subway tunnels exacerbate fire hazards, revealing a critical lacuna regarding the spatio-temporal coupling of fire progression and human egress. To address this, this study proposes and validates an Integrated Spatio-Temporal Risk Assessment Model to explicitly quantify survivability thresholds under complex fire dynamics. The framework synergizes Large-Eddy Simulation (LES) based Computational Fluid Dynamics with agent-based pedestrian trajectory modeling within a 3D tunnel featuring a 2% longitudinal gradient. Evaluating 9.5 MW and 12 MW fire energies, the model assessed Single-Sided Evacuation (SSE), Double-Sided Evacuation (DSE), and Sprinkler-Assisted Single-Sided Evacuation (SSE-S) across 2160 agents. Hazards were quantified by continuously resolving Fractional Effective Dose (FED) indices, 60 °C boundaries, and 500 ppm CO fronts. Simulations reveal the gradient induces a severe stack effect, accelerating toxic dispersion and yielding temperatures exceeding 1200 °C. Consequently, SSE engendered fatal bottlenecks (FED: 15.33), whereas DSE optimized pedestrian flux, capping peak FED at 0.52. Crucially, while active suppression (SSE-S) extinguished flames within 105 s, thermodynamic cooling induced a paradoxical loss of smoke buoyancy, causing toxic layers to stratify at the breathing zone. Ultimately, while DSE and SSE-S are paramount for survivability, water-based suppression generates localized toxicological risks, necessitating the integration of low-level smoke detection and extraction architectures in future subterranean designs.

Subway tunnels exacerbate fire hazards, revealing a critical lacuna regarding the spatio-temporal coupling of fire progression and human egress. To address this, this study proposes and validates an Integrated Spatio-Temporal Risk Assessment Model to explicitly quantify survivability thresholds under complex fire dynamics. The framework synergizes Large-Eddy Simulation (LES) based Computational Fluid Dynamics with agent-based pedestrian trajectory modeling within a 3D tunnel featuring a 2% longitudinal gradient. Evaluating 9.5 MW and 12 MW fire energies, the model assessed Single-Sided Evacuation (SSE), Double-Sided Evacuation (DSE), and Sprinkler-Assisted Single-Sided Evacuation (SSE-S) across 2,160 agents. Hazards were quantified by continuously resolving Fractional Effective Dose (FED) indices, 60°C boundaries, and 500 ppm CO fronts. Simulations reveal the gradient induces a severe stack effect, accelerating toxic dispersion and yielding temperatures exceeding 1200°C. Consequently, SSE engendered fatal bottlenecks (FED: 15.33), whereas DSE optimized pedestrian flux, capping peak FED at 0.52. Crucially, while active suppression (SSE-S) extinguished flames within 105 seconds, thermodynamic cooling induced a paradoxical loss of smoke buoyancy, causing toxic layers to stratify at the breathing zone. Ultimately, while DSE and SSE-S are paramount for survivability, water-based suppression generates localized toxicological risks, necessitating the integration of low-level smoke detection and extraction architectures in future subterranean designs.

This study explores the asymmetric relationship between household disaster awareness and structural preparedness actions in İznik (Türkiye), a region characterized by its vulnerability to multiple hazards and its high sensitivity to cultural heritage damage. The present study examines the "awareness-preparedness gap" paradox within the extant literature. To this end, the study analyzes cross-sectional survey data obtained from 515 households employing binary logistic regression models. The empirical findings indicate that risk perception varies significantly depending on the hazard typology: While the perception of seismic risk is notably high (77.9%), structural retrofitting rates remain marginal (7.0%). Conversely, flood risk is largely neglected both perceptually and behaviorally. Multivariate analyses indicate that, when controlled for sociodemographic and cognitive variables, housing ownership status (homeowners are approximately three times more likely to prepare compared to tenants; OR = 3.031) and self-efficacy constitute the most robust predictors of protective behavior. The analysis demonstrates that fatalism, institutional trust, and mere risk perception, which are frequently emphasized in the literature, do not independently catalyze disaster mitigation actions. Moreover, the factors constraining structural interventions were identified as bureaucratic obstacles rather than concerns regarding the preservation of cultural heritage. Consequently, this study advocates for transcending conventional information-deficit models in disaster risk reduction (DRR) strategies. The study proposes the adoption of an integrated "awareness-capacity-action" framework that centers on ownership-related constraints, institutional barriers, and individual self-efficacy.

Universities represent critical yet underutilized platforms for climate change mitigation through renewable energy transitions, yet few have integrated high‐resolution spatial analytics with actionable policy frameworks for institutional decarbonization. This study presents a comprehensive and integrated workflow for campus‐scale decarbonization planning, demonstrated at Sakarya University in Türkiye. High‐resolution unmanned aerial vehicle (UAV) data were used to create precise three‐dimensional rooftop models, combined with ground‐level analysis for solar roads, parking areas, EV‐charging stations, and bus terminals. A multi‐method multi‐criteria decision‐making (MCDM) ensemble—integrating OPA and RANCOM for criteria weighting, root assessment method (RAM), preference ranking based on ideal‐average distance (PROBID), measurement alternatives and ranking according to compromise solution (MARCOS), stable preference ordering towards ideal solution (SPOTIS), and evaluation based on distance from average solution (EDAS) for ranking, and footrule aggregation for consensus—was applied across technical, economic, social, and structural parameters to ensure robust consensus‐based prioritization of solar deployment sites. The framework integrates high‐resolution spatial modeling, carbon emissions inventory, stakeholder survey analysis, and MCDM‐based prioritization into a single, transferable decision‐support workflow designed to serve as a replicable model for universities worldwide. Results reveal rooftop photovoltaic (PV) systems could modestly exceed the university’s current annual electricity demand by ~12%, with low levelized cost of energy (LCOE) indicating strong economic viability. Additional opportunities were identified for solar‐powered mobility infrastructure, including EV charging stations and solar road panels. The approach leverages open‐source software for methodological transparency and replicability and provides a scalable template for other institutions. Aligning directly with Sustainable Development Goals SDG 7 and SDG 11, this study demonstrates how universities can act as living laboratories for climate innovation, translating high‐resolution geospatial analysis and decision‐support tools into actionable, cost‐efficient pathways toward carbon neutrality.

Tuberculosis (TB) remains a critical public health issue, particularly in regions with significant socio‐economic disparities. This study provides a comprehensive spatial analysis of TB dynamics in Şanlıurfa, Türkiye, covering the period from 2016 to 2023. Utilizing Geographic Information Systems, epidemiological data, and advanced statistical techniques, the research examines the spatial distribution and temporal trends of TB cases within this region. By integrating patient data with demographic, environmental, and socio‐economic variables, the study assesses the complex factors influencing TB incidence and prevalence. The results indicate significant spatial clustering of TB cases, with the highest concentrations in areas characterized by high population density, lower socio‐economic status, limited healthcare accessibility, and poor environmental conditions. Temporal trends reveal a gradual decline in TB incidence over the study period; however, certain hotspots persist, underscoring the need for sustained and targeted interventions. Furthermore, the study identifies a correlation between TB prevalence and inadequate living conditions, emphasizing the role of socio‐economic improvement in disease control. These findings provide crucial insights for policymakers and public health officials, facilitating the development of more effective, evidence‐based TB control strategies tailored to the unique socio‐economic and geographical landscape of Şanlıurfa.

Yaya simülasyonu teknolojilerinin mimarlık ve şehir planlama disiplinlerinde kullanımı yeni bir kavram olmamakla birlikte; makine öğrenmesi tabanlı, insan davranışlarına benzer sonuçlar veren, ajan bazlı, gerçekçiliği ve geçerliliği bilimsel olarak ispatlanmış üç boyutlu simülasyon yazılımları son yıllarda ortaya çıkmışlardır. Bu yazılımlar, özellikle kalabalık ve karmaşık mekanlarda ortaya çıkabilecek sirkülasyon ve acil durum tahliye problemlerinin henüz tasarım aşamasındayken görülmesine olanak sağlamakta; bu sayede yapı inşa edilmeden önce projede gerekli revizyonların gerçekleştirilmesine imkan vermektedir. Ulusal ve uluslararası standartlar doğrultusunda gerçekleştirilen bu çalışmanın amacı, güncel simülasyon teknolojilerinin yapılara ilişkin normal işletme ve acil durum tahliye senaryolarının değerlendirilmesinde kullanımını örnek olarak seçilen gerçek bir metro istasyonu projesi üzerinden incelemektir. Seçilen raylı sistem hattındaki istasyona özgü yolcu yüklerinin bulunması amacıyla klasik elle hesaplama yöntemleri kullanılmış, ortaya çıkan değerler Massmotion yazılımına aktarılarak mekânsal kapasite analizleri gerçekleştirilmiş ve istasyonun tüm katlarına ilişkin hizmet seviyeleri bulunmuştur. Sonuç olarak metro istasyonunun normal işletme ve acil durum tahliye senaryolarının gereksinimlerini karşılayıp karşılamayacağı test edilmiş, ortaya çıkan sonuçlar çalışma kapsamında verilmiştir.

Today, the COVID-19 pandemic continues to threaten all humanity worldwide. Turkey, one of the countries severely affected by the disease, has 81 provinces showing regionally different incidence rate patterns. This study explores the effect of social, economic, demographic, climatic, and geographic characteristics of different regions on the COVID-19 spread in Turkey. Geographic Information System (GIS)-based spatial interpolation techniques and multiple linear regression analysis have been conducted to examine the relationship between provincial incidence rates and eighteen explanatory variables determined by an in-depth literature survey. Results show that five of eighteen predictors have a statistically significant impact and can explain 57% of the regional variability of the COVID-19 incidence rates. Urbanization level, education index, and wind speed positively associate with the virus spread, but the sunshine duration and average temperature negatively correlate. On the other hand, 43% of the variation is due to other factors not included in this study. Therefore, an interdisciplinary study should be carried out by participating in all the related fields such as natural sciences, engineering and technology, medical and health sciences, social sciences, and humanities to understand the dynamics of the disease.

Throughout history, human beings have lived to survive, have struggled to have a job and have enough income for a better life. But at the point we have reached today, people's quality of life not only depends on wealth and employment, but also on many subjective factors, including the conditions of the environment in which they live, physical and mental health, education, recreation, security, leisure, freedom, human rights, social belonging and happiness level. Although this situation is related with the individuals at micro scale, it is one of the important focal points of central and local governments on macro scale. For administrators, revealing regional differences in well-being is an important criterion for eliminating social inequalities. There are many different multi criteria decision making based studies calculated the index of quality of life in 81 provinces of Turkey in accordance with 11 dimensions and 41 indicators determined by Turkstat. The aim of this study is to compare the quality of life studies and rankings of cities based on six different statistical methods. GIS based IDW interpolation technique was used to understand the spatial distribution of well-being index and make an accurate comparison of the calculation methodologies. As a result of the study, it was seen that different methods performed on the same data gave very different results from each other.

The Digital World has become the most significant platform for spreading the written and visual documents about cultural and historical heritages in accordance with the recent developments on web based technologies. All kind of digital platforms such as notebooks, personal computers, tablets and mobile phones are the primary tools to transfer local values to global scale. Nevertheless, it is not possible to say that these technological opportunities are not used efficiently to promote museums keeping the inheritance and memory of societies. Fortunately, 3D game technologies and virtual reality applications have been started to use in this area. The traditional promotion methods are being replaced by these new and innovative solutions including ‘virtual museum’ term. People are capable to use this platform to see and interactively walk through the virtually reconstructed museums in a 3D digital environment. Creating accessible web based virtual museum platforms will attract tourists, students and researchers from all ages. The aim of this study is to create a virtual museum platform including all kind of written and visual materials. Hagia Sophia has been selected as the case study area of this study and digitally reconstructed to use in the project.