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The complexities of scaling have long presented challenges in applying small-scale test results of geocell-reinforced footings to field conditions in geosynthetic engineering. There has been no research that thoroughly examines the scaling of both geometry and material stiffness in geocell-reinforced footing systems although limited studies have attempted to scale geocells using alternative materials with lower strength, such as simile paper, non-woven geotextile etc. Therefore, this is a leading study to address the complexities of scaling using 3D-printing technology, where both geometry and tensile stiffness of geocell were accurately scaled using scaling laws. In the present study, the impact of scaling on the performance of strip footings reinforced with both traditional fabricated and 3D-printed geocells in terms of pressure-settlement response and improvement factors were assessed. The results indicated that 3D-printed geocells offered significant advantages in customization and rapid prototyping of field scale. Specifically, the strip footings reinforced with fabricated geocells showed up to 65% higher improvement factors in both loose and dense soils compared to those using the scaled 3D-printed geocells. Furthermore, the footings reinforced with scaled geocells using 3D-printing technologies closely aligned with existing large-scale test results regarding improvement factors, which were further validated through various numerical analyses. These findings offer new perspectives for optimizing and applying 3D-printed geocells in geotechnical engineering and address the longstanding challenge of scaling geocell-reinforcement systems in small-scale model tests.

The International Institute for Applied Systems Analysis (IIASA), in collaboration with its Japan National Member Organization (NMO), supported by Ministry of the Environment Japan (MOEJ) has initiated a joint research endeavor centered on Cities Transformation. The primary aim of this collaborative effort's inaugural phase is the compilation of a fast-track comprehensive report. This report aims to consolidate the current understanding of urban transformations, identifying critical knowledge gaps therein. It serves to support the scientific community, city stakeholders, and policy-makers in discerning areas warranting greater attention and, crucially, further investigation and study. Particularly, it provides updates on the IPCC 7th Assessment Cycle, with a specific focus on its Special Report on Climate Change and Cities. Commencing with an overview of global urbanization trends, the report delves into the status of informal urban settlement development (Section 2). Subsequently, it comprehensively discusses the physical aspects of climate change, including impacts, vulnerability, adaptation, and mitigation, with a spotlight on air pollution and waste challenges (Section 3). Section 4 shifts focus to systems transformation, examining sectors and cross-cutting perspectives through various case studies. Following this, Section 5 investigates the enabling conditions for city transformations, emphasizing the roles of governance, behavioral and lifestyle changes, innovation and technology, and finance. Expanding further, Section 6 assesses the synergies and trade-offs of mitigation and adaptation strategies, with a particular lens on Sustainable Development Goals (SDGs), health, and well-being. The report concludes by recognizing significant knowledge gaps highlighted through expert insights. We had the privilege of interviewing several experts in the field, including Xuemei Bai, Shobhakar Dhakal, Arnulf Grubler, and Ayyoob Sharifi. We extend our sincere appreciation to them for their valuable contribution. The resulting report will be launched during an international expert workshop and symposium to disseminate the project's findings to the broader public. The event is scheduled for February 27th to 28th, 2024, in Tokyo-Japan.

The International Institute for Applied Systems Analysis (IIASA), in collaboration with its Japan National Member Organization (NMO), supported by Ministry of the Environment Japan (MOEJ) has initiated a joint research endeavor centered on Cities Transformation. The primary aim of this collaborative effort's inaugural phase is the compilation of a fast-track comprehensive report. This report aims to consolidate the current understanding of urban transformations, identifying critical knowledge gaps therein. It serves to support the scientific community, city stakeholders, and policy-makers in discerning areas warranting greater attention and, crucially, further investigation and study. Particularly, it provides updates on the IPCC 7th Assessment Cycle, with a specific focus on its Special Report on Climate Change and Cities. Commencing with an overview of global urbanization trends, the report delves into the status of informal urban settlement development (Section 2). Subsequently, it comprehensively discusses the physical aspects of climate change, including impacts, vulnerability, adaptation, and mitigation, with a spotlight on air pollution and waste challenges (Section 3). Section 4 shifts focus to systems transformation, examining sectors and cross-cutting perspectives through various case studies. Following this, Section 5 investigates the enabling conditions for city transformations, emphasizing the roles of governance, behavioral and lifestyle changes, innovation and technology, and finance. Expanding further, Section 6 assesses the synergies and trade-offs of mitigation and adaptation strategies, with a particular lens on Sustainable Development Goals (SDGs), health, and well-being. The report concludes by recognizing significant knowledge gaps highlighted through expert insights. We had the privilege of interviewing several experts in the field, including Xuemei Bai, Shobhakar Dhakal, Arnulf Grubler, and Ayyoob Sharifi. We extend our sincere appreciation to them for their valuable contribution. The resulting report will be launched during an international expert workshop and symposium to disseminate the project's findings to the broader public. The event is scheduled for February 27th to 28th, 2024, in Tokyo-Japan.

In this study, all railway works carried out during the Early Republican Period have been examined through the journal "Nafia İşleri Mecmuası" published between 1934 and 1949. In the journal, which was published monthly by the government of the period, detailed information about all railway-related projects was reported, allowing the public to be informed about the works conducted in the country and their specifics. This study aims to investigate the details of the railway policy pursued immediately after the establishment of the Republic, trace its steps, determine the benefits achieved in the country, and assess the success of this policy in reaching its objectives. The examination of the Nafia İşleri Journal was conducted using a quantitative method, involving reading the journal, extracting headings related to railways, categorizing content annually, creating tables, and interpreting the data. As a result of the study, all the details of railway works conducted during the Early Republic Period in terms of decision-making, implementation, and operational processes have been identified through the Nafia İşleri Journal. In addition to these technical details, the railway policy adopted by the government and the success of the policy pursued have also been observed. Bu çalışmada, Erken Cumhuriyet Dönemi’nde yapılan tüm demiryolu çalışmaları 1934-1949 yılları arasında yayınlanan Nafia İşleri Mecmuası isimli dergi üzerinden incelenmiştir. Dönemin hükümeti tarafından aylık olarak çıkarılan dergide, demiryolu ile ilgili yapılan tüm işlerin detayları bildirilmekte ve halkın bu sayede ülkede yapılan işlerden ve bunların detaylarından haberdar olması sağlanmaktaydı. Bu çalışma, Cumhuriyet’in kurulmasının hemen ardından izlenen demiryolu politikasının detaylarını görmek, adımlarını izlemek, ülkede ne gibi faydaların sağlandığını tespit etmek ve bu politikanın hedefine ulaşması noktasındaki başarısını inceleyebilmek amacıyla yapılmıştır. Nafia İşleri Mecmuasının incelemeleri kantitatif yöntemle yapılmış, dergi okumaları yapılıp demiryolu ile ilgili başlıklar ayıklanmış, yıllık olarak içerikler belirlenmiş, tablolaştırılmış ve yorumlanmıştır. Çalışmada sonuç olarak, Nafia İşleri Mecmuası aracılığıyla, Erken Cumhuriyet Dönemi’nde yapılmış demiryolu işlerinin karar, uygulama ve işletme süreçlerindeki tüm detayları belirlenmiştir. Bu teknik detayların yanı sıra devletin benimsediği demiryolu politikası ve izlenen politikanın başarısı da gözlemlenmiştir.

One of the most frequently used parameters to evaluate track performance in railways is the track modulus. Although it is affected by substructure and superstructure elements, the track modulus mainly depends on the subgrade resilient modulus. The resilient modulus is a function of water content in all soils. Consequently, the track modulus may show seasonal variations depending on the rainfall regime. Periodic measurements of the subgrade water content should be made in order to consider this situation when evaluating track performance. Oven drying is one of the primary methods used to measure soil water content. In addition to the difficulty of taking samples from the subgrade, oven drying can be considered as time consuming since the procedure is based on 24-hour drying. Alternatively, Time Domain Reflectometry (TDR) is an electromagnetic measurement method that enables real-time and remote measurement. Water content is determined with the help of the calibration equation established with the dielectric permittivity of the soil measured by TDR. In this study, TDR measurements made on 7 different soil classes, which can be considered as subgrade material and whose fine content is maximum 15%, were obtained from the literature. For the calibration equation, unlike other studies, dielectric mixture model was used instead of regression methods. The proposed calibration was evaluated with the performance metrics selected in the test set. Again, unlike other studies, the calibration, which is specific to a soil group rather than a soil class, provided 93% prediction success within a wide water content range, provided that it remains within the 2.0% error band. Additionally, it was observed that the prediction error distribution was adequately narrow and centered close to zero. In this context, TDR, whose use is extremely limited in Türkiye is recommended as a rapid method for periodic measurements of subgrade water content on railway tracks that provides high accuracy. Demiryollarında hat performansını değerlendirmek için en sık başvurulan parametrelerden birisi hat modülüdür. Altyapı ve üstyapı elemanlarından etkilenmekle birlikte hat modülü büyük oranda taban zemini esneklik modülüne bağlıdır. Esneklik modülü ise tüm zeminlerde su içeriğinin bir fonksiyonudur. Bu sebeple hat modülü yağış rejimine bağlı olarak mevsimsel farklılıklar gösterebilir. Bu durumun hat performansı değerlendirilirken göz önünde bulundurulabilmesi için taban zemini su içeriğinin periyodik ölçümleri yapılmalıdır. Zemin su içeriğinin ölçülmesi için kullanılan yöntemlerin başında etüvde kurutma gelmektedir. Taban zemininden örnek almanın zor olmasının yanı sıra deney prosedürünün 24 saat kurutmaya dayalı olması nedeniyle etüvde kurutma yavaş bir yöntem olarak değerlendirilebilir. Alternatif olarak Zaman Tanım Alanında Yansıma Yöntemi (Time Domain Reflectometry, TDR), gerçek zamanlı ve uzaktan ölçüm alabilmeyi sağlayan bir elektromanyetik ölçüm yöntemidir. TDR ile ölçülen zeminin dielektrik iletkenliği ile kurulan kalibrasyon denklemi yardımıyla su içeriği belirlenir. Bu çalışmada taban zemini malzemesi olabilecek ve ince dane içeriği en fazla %15 olan 7 farklı zemin sınıfında yapılmış olan TDR ölçümleri literatürden elde edilmiştir. Kalibrasyon denklemi için diğer çalışmalardan farklı olarak regresyon yöntemleri yerine dielektrik karışım modeli kullanılmıştır. Önerilen kalibrasyon, sınama setinde seçilen performans göstergeleri ile değerlendirilmiştir. Yine diğer çalışmalardan farklı olarak bir zemin sınıfı yerine zemin grubuna özgü olan kalibrasyon, geniş bir su içeriği aralığında %2,0 hata bandında kalmak koşuluyla %93 tahmin başarısı sağlamıştır. Ayrıca tahmin hatası dağılımının yeterince dar ve sıfıra yakın merkezlenmiş olduğu görülmüştür. Bu bağlamda demiryolu hatlarında taban zemini su içeriğinin periyodik ölçümleri için Türkiye’de kullanımı son derece sınırlı olan TDR, yüksek doğruluk sağlayan hızlı bir ölçüm yöntemi olarak önerilmektedir.

More and more distributed generations (DGs), such as wind, PV or battery bank sources, are connected to electric systems or customer loads. However, the locations of these DGs are based on the highest energy that can be potentially harvested for electric power generation. Therefore, these locations create different line impedances based on the distance from the DGs to the loads or the point of common coupling (PCC). This paper presents an adaptive virtual impedance (AVI) in the predictive control scheme in order to ensure power sharing accuracy and voltage stability at the PCC in a microgrid network. The reference voltage from mismatched feeder impedances was modified by utilizing the suggested AVI-based predictive control for creating equal power sharing between the DGs in order to avoid overburdening any individual DG with low-rated power. The AVI strategy used droop control as the input control for generating equal power sharing, while the AVI output was used as the reference voltage for the finite control set–model predictive control (FCS-MPC) for creating a minimum voltage error deviation for the cost function (CF) for the inverter’s vector switching pattern in order to improve voltage stability at the PCC. The proposed AVI-based controller was tested using two DG inverter circuits in a decentralized control mode with different values of line impedance and rated power. The performance of the suggested controller was compared via MATLAB/Simulink with that of a controller based on static virtual impedance (SVI) in terms of efficiency of power sharing and voltage stability at the PCC. From the results, it was found that (1) the voltage transient magnitude for the AVI-based controller was reduced within less than 0.02 s, and the voltage at the PCC was maintained with about 0.9% error which is the least as compared with those for the SVI-based controller and (2) equal power sharing between the DGs increased during the change in the load demand when using the AVI-based controller as compared with using the SVI-based controller. The proposed controller was capable of giving more accurate power sharing between the DGs, as well as maintaining the voltage at the PCC, which makes it suitable for the power generation of consumer loads based on DG locations for future energy communities.

In free-space optical satellite networks (FSOSNs), satellites can have different laser inter-satellite link (LISL) ranges for connectivity. Greater LISL ranges can reduce network latency of the path but can also result in an increase in transmission power for satellites on the path. Consequently, this tradeoff between satellite transmission power and network latency should be investigated, and in this work we examine it in FSOSNs drawing on the Starlink Phase 1 Version 3 and Kuiper Shell 2 constellations for different LISL ranges and different inter-continental connections. We use appropriate system models for calculating the average satellite transmission power and network latency. The results show that the mean network latency decreases and mean average satellite transmission power increases with an increase in LISL range. For the Toronto--Sydney inter-continental connection in an FSOSN with Starlink's Phase 1 Version 3 constellation, when the LISL range is approximately 2,900 km, the mean network latency and mean average satellite transmission power intersect are approximately 135 ms and 380 mW, respectively. For an FSOSN with the Kuiper Shell 2 constellation in this inter-continental connection, this LISL range is around 3,800 km, and the two parameters are approximately 120 ms and 700 mW, respectively. For the Toronto--Istanbul and Toronto--London inter-continental connections, the LISL ranges at the intersection are different and vary from 2,600 km to 3,400 km. Furthermore, we analyze outage probability performance of optical uplink/downlink due to atmosphere attenuation and turbulence. Accepted for publication in IEEE Open Journal of Vehicular Technology

It is essential to solve complex routing problems to achieve operational efficiency in logistics. However, because of their complexity, these problems are often tackled sequentially using cluster-first, route-second frameworks. Unfortunately, such two-phase frameworks can suffer from suboptimality due to the initial phase. To address this issue, we propose leveraging information about the optimal tour lengths of potential clusters as a preliminary step, transforming the two-phase approach into a less myopic solution framework. We introduce quick and highly accurate Traveling Salesperson Problem (TSP) tour length estimators based on neural networks (NNs) to facilitate this. Our approach combines the power of NNs and theoretical knowledge in the routing domain, utilizing a novel feature set that includes node-level, instance-level, and solution-level features. This hybridization of data and domain knowledge allows us to achieve predictions with an average deviation of less than 0.7% from optimality. Unlike previous studies, we design and employ new instances replicating real-life logistics networks and morphologies. These instances possess characteristics that introduce significant computational costs, making them more challenging. To address these challenges, we develop a novel and efficient method for obtaining lower bounds and partial solutions to the TSP, which are subsequently utilized as solution-level predictors. Our computational study demonstrates a prediction error up to six times lower than the best machine learning (ML) methods on their training instances and up to 100 times lower prediction error on out-of-distribution test instances. Furthermore, we integrate our proposed ML models with metaheuristics to create an enumeration-like solution framework, enabling the improved solution of massive-scale routing problems. In terms of solution time and quality, our approach significantly outperforms the state-of-the-art solver, demonstrating the potential of our features, models, and the proposed method. History: This paper has been accepted for the Transportation Science Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0015 .