[article-cris] Insinööritieteiden korkeakoulu / ENG

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    Task-difficulty homeostasis in car following models: Experimental validation using self-paced visual occlusion
    (Public Library of Science, 2017-01-01) Pekkanen, Jami; Lappi, Otto; Itkonen, Teemu H.; Summala, Heikki; Department of Built Environment; Planning and Transportation; University of Helsinki
    Car following (CF) models used in traffic engineering are often criticized for not incorporating "human factors" well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn't incorporated in the current models.
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    Strengthening oil palm smallholder farmers’ resilience to future industrial challenges
    (Nature Publishing Group, 2024-12) Hendrawan, Dienda; Chrisendo, Daniel; Musshoff, Oliver; Department of Built Environment; Water and Environmental Eng.; University of Göttingen
    Oil palm cultivation has improved living standards and alleviated the poverty of many smallholder farmers. However, challenges such as climate change, aging palms and negative sentiments in the major markets, threaten the wellbeing of and raise the question on smallholder farmers’ resilience, which remains poorly understood. Using primary data from Indonesia, the largest palm oil producer in the world, we measure and evaluate the resilience of oil palm smallholder farmers using the Sustainable Livelihoods Approach. Our results revealed five classes of smallholders with different levels of resilience: vulnerable, economically and socially constrained, low-skilled, semi-secure and adaptive smallholders. The farmers in the least resilient group are majorly older local farmers, who established oil palm plantations independently. Meanwhile, the most resilient group is dominated by smallholders who participated in the migration program, and in the past, received support from the government to start oil palm plantations. Our study highlights the heterogeneity of smallholders’ livelihood resilience and the need for inclusive and tailored interventions for the various classes of smallholder farmers to establish sustainable communities.
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    Improved understanding of how irrigated area expansion enhances precipitation recycling by land–atmosphere coupling
    (Elsevier, 2024-06-30) Wang, Xuanxuan; Cheng, Yongming; Liu, Liu; Niu, Qiankun; Huang, Guanhua; Department of Built Environment; Water and Environmental Eng.; China Agricultural University
    Large-scale agricultural activities can intensify atmospheric–terrestrial interactions, of which precipitation recycling plays a critical role. During 1982–2018, irrigated area has dramatically expanded in Northwest China (NWC). In this study, a regional precipitation recycling model—the Brubaker model was used to investigate the precipitation recycling ratio (PRR) and recycled precipitation (RP). Evapotranspiration (ET) estimated by the atmospheric–terrestrial water balance method (A–T) was employed to investigate precipitation recycling. Statistically, there was a turning point in 2002 for the rate in irrigated area increase, from 0.07 × 106 ha/year before 2002–0.217 × 106 ha/year after 2002. There were significant shifts in ET, PRR, and RP in NWC, using the turning point of irrigated area expansion as the line of demarcation. The contribution of the change in irrigated area to PRR increased from 18.3% (1982–2002) to 22.9% (2003–2018) in NWC. Prior to 2002, enhanced RP offset the increased ET by 72.9%. After 2002, the positive effect of irrigated area expansion on precipitation recycling disappeared in NWC. Due to the different climate and irrigation practices at the province level, the variations in irrigated area and their contributions to PRR were examined in three provinces, Xinjiang, Gansu, and Shaanxi. Results based on the Brubaker model and Budyko framework indicate that in Xinjiang and Gansu, the contribution of the irrigated area change after the turning point to PRR were 24.5% and -95.6%, respectively, and there is no potential for continued expansion of irrigated area. In Shaanxi, however, there is potential for continued expansion of irrigated area. The methodology for quantifying the impact of irrigated area change on PRR provides reliable references for the sustainable use of cultivated land and the protection of agricultural water resources.
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    Molecular Dynamics Simulation and the Regeneration and Diffusion Effects of Waste Engine Oil in Aged Asphalt Binder
    (MDPI AG, 2024-05) Sun, Yuxuan; Cannone Falchetto, Augusto; Zhang, Fan; Wang, Di; Chen, Wei; Department of Civil Engineering; Mineral Based Materials and Mechanics; Tongji University; University of Ottawa
    In recent years, the potential of waste engine oil (WEO) as a rejuvenator for aged asphalt binders has gained significant attention. Despite this interest, understanding WEO’s regeneration mechanism within aged asphalt binders, particularly its diffusion behavior when mixed with both aged and virgin asphalt binders, remains limited. This study adopts a molecular dynamics approach to constructing models of virgin, aged, and rejuvenated asphalt binders with different WEO contents (3%, 6%, 9%, and 12%). Key properties such as the density, glass transition temperature, cohesive energy density, solubility parameter, viscosity, surface free energy, fractional free volume, and diffusion coefficient are simulated. Additionally, models of rejuvenated asphalt binder are combined with those of aged asphalt binder to investigate mutual diffusion, focusing on the impact of WEO on the relative concentration and binding energy. The findings reveal that WEO notably decreased the density, viscosity, and glass transition temperature of aged asphalt binders. It also improved the molecular binding within the asphalt binder, enhancing crack resistance. Specifically, a 9% WEO content can restore the diffusion coefficient to 93.17% of that found in virgin asphalt binder. Increasing the WEO content facilitates diffusion toward virgin asphalt binders, strengthens molecular attraction, and promotes the blending of virgin and aged asphalt binders.
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    Behavior of stressed skin corrugated sheet under hydrostatic loads
    (Elsevier, 2024-07) Abd El-Latif, Mohamed Y.; Yossef, Mostafa; Chen, An; Elsayad, Mohamed; Department of Civil Engineering; Structures – Structural Engineering, Mechanics and Computation; Ain Shams University; Beijing Jiaotong University; Arab Academy for Science, Technology & Maritime Transport
    Water storage in buildings is an integral part of water supply, which can be used for firefighting and drinking. It can be divided into three categories: elevated, rooftop, and underground water tanks. This paper presents a novel water storage system consisting of thin-walled corrugated steel sheets, which can be installed in a multi-story building on any floor. Compared with a reinforced concrete tank, the integrated steel water tank can be fabricated and installed much faster and store freshwater more easily. To develop the system, a finite element model is developed, which is validated using the on-site measurements. Next, the model is used to conduct a parametric study to evaluate the effects of boundary conditions, panel depth, sheet thickness, trough-to-crest width ratio, and corrugation angle on the behavior of integrated steel water tanks. The model is further used to evaluate the water tank subjected to lateral diaphragm loads and report the tank stiffness under combined loads. Finally, an implementation guide for the steel tank is presented, showing the supporting system, vacuum and magnetic handling of steel panels, robotic welding techniques, and delivery. It can be concluded that the paneled steel tank can be an efficient solution for water storage inside buildings.
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    Testing ChatGPT-aided SparQL generation for semantic construction information retrieval
    (2023) Zheng, Yuan; Seppänen, Olli; Seiss, Sebastian; Melzner, Jürgen; Department of Mechanical Engineering; Department of Civil Engineering; Capone, Pietro; Getuli, Vito; Pour Rahimian, Farzad; Dawood, Nashwan; Bruttini, Alessandro; Sorbi, Tommaso; Mechatronics; Performance in Building Design and Construction; Bauhaus-Universität Weimar
    Recently there has been a strong interest in using semantic technologies to improve information management in the construction domain. Ontologies provide a formalized domain knowledge representation that provides a structured information model to facilitate information management issues such as formalization and integration of construction workflow information and data and enables further applications such as information retrieval and reasoning. SPARQL Protocol And RDF Query Language (SPARQL) queries are the main approaches to conduct the information retrieval from the Resource Description Framework (RDF) format data. However, there is a barrier for end users to develop the SPARQL queries, as it requires proficient skills to code them. This challenge hinders the practical application of ontology-based approaches on construction sites. As a generative language model, ChatGPT has already illustrated its capability to process and generate human-like text, including the capability to generate the SPARQL for domain-specific tasks. However, there are no specific tests evaluating and assessing the SPARQL-generating capability of ChatGPT within the construction domain. Therefore, this paper focuses on exploring the usage of ChatGPT with a case of importing the Digital Construction Ontologies (DiCon) and generating SPARQL queries for specific construction workflow information retrieval. We evaluate the generated queries with metrics including syntactical correctness, plausible query structure, and coverage of correct answers
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    Integrating physics-based simulations with Gaussian processes for enhanced safety assessment of offshore installations
    (Elsevier Ltd, 2024-09) Abaei, Mohammad Mahdi; Leira, Bernt Johan; Sævik, Svein; BahooToroody, Ahmad; Department of Mechanical Engineering; Marine and Arctic Technology; Norwegian University of Science and Technology
    Installing large floating objects during offshore operations is a challenging and failure-prone task, especially when passing through the splash zone due to extreme lifting loads on the wire and the payload. For a safe operation, it is essential to predict the peak loads on the installation system and create an early decision-making scenario for the installation vessel before starting the real operation on site. To this end, the extreme loads that can lead to unsatisfactory performance of the system must be evaluated accurately; however, the operation involves a great deal of uncertainty and physics complexity that can lead to unreliable decision-making. It is also challenging to perform numerical calculations to support ongoing marine operations, as it usually takes hours to evaluate different environmental load cases. Thus, it is essential to create an efficient prediction method associated with the environment and the corresponding response levels. In this study, a model is proposed that integrates physics-based simulations with Gaussian Processes, for estimating peak loads in lifting wires. The model offers the advantage of addressing shorter simulation times while still maintaining accuracy in predicting extreme response levels and quantifying the loads uncertainty during the operation. Bayesian Inference is used to incorporate the uncertainty, estimating hyper-parameters and predict the peak loads for various marine environmental conditions. A real case study is considered to demonstrate the application of the proposed model. The results show good agreement with the simulations obtained from time-domain dynamic analysis. The current study provide insights for both onboard and pre-planned decision-making on installation conditions, thereby enhancing predictive accuracy and improving safety in complex marine lifting operations.
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    The Resilient Urban Environment at All Levels and with All Its Actors
    (2024) Toivonen, Saija; Department of Built Environment; Real Estate
    Both resilience building and the impacts of crises must be considered in various contexts of the built environment. Crisis impacts are experienced at the micro, meso and macro levels and by diverse market actors who have their own hopes, fears and abilities to prepare, manage, recover and learn, including ordinary households, office workers, real estate owners, firms occupying spaces and the public sector. Similarly, solutions promoting a resilient built environment cannot be reached without embracing a holistic approach that acknowledges the variety of timeframes, actors, scopes and factors, including political, environmental, social, cultural, technological, economic and legal issues that all contribute to resilience building. The present chapter ties together the essence and the main message of this book: imagine the possible futures, and don't be taken by surprise. Learn and apply the solutions and tools presented in this book to support a more resilient built environment and happier societies.
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    Benchmarking Under- and Above-Canopy Laser Scanning Solutions for Deriving Stem Curve and Volume in Easy and Difficult Boreal Forest Conditions
    (MDPI AG, 2024-05) Muhojoki, Jesse; Tavi, Daniella; Hyyppä, Eric; Lehtomäki, Matti; Faitli, Tamás; Kaartinen, Harri; Kukko, Antero; Hakala, Teemu; Hyyppä, Juha; Department of Built Environment; MeMo; National Land Survey of Finland
    The use of mobile laser scanning for mapping forests has scarcely been studied in difficult forest conditions. In this paper, we compare the accuracy of retrieving tree attributes, particularly diameter at breast height (DBH), stem curve, stem volume, and tree height, using six different laser scanning systems in a managed natural boreal forest. These compared systems operated both under the forest canopy on handheld and unmanned aerial vehicle (UAV) platforms and above the canopy from a helicopter. The complexity of the studied forest sites ranged from easy to difficult, and thus, this is the first study to compare the performance of several laser scanning systems for the direct measurement of stem curve in difficult forest conditions. To automatically detect tree stems and to calculate their attributes, we utilized our previously developed algorithm integrated with a novel bias compensation method to reduce the overestimation of stem diameter arising from finite laser beam divergence. The bias compensation method reduced the absolute value of the diameter bias by 55–99%. The most accurate laser scanning systems were equipped with a Velodyne VLP-16 sensor, which has a relatively low beam divergence, on a handheld or UAV platform. In easy plots, these systems found a root-mean-square error (RMSE) of below 10% for DBH and stem curve estimates and approximately 10% for stem volume. With the handheld system in difficult plots, the DBH and stem curve estimates had an RMSE under 10%, and the stem volume RMSE was below 20%. Even though bias compensation reduced the difference in bias and RMSE between laser scanners with high and low beam divergence, the RMSE remained higher for systems with a high beam divergence. The airborne laser scanner operating above the forest canopy provided tree attribute estimates close to the accuracy of the under-canopy laser scanners, but with a significantly lower completeness rate for stem detection, especially in difficult forest conditions.
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    Introduction to Crises, Crisis Management and Resilience in the Built Environment
    (2024) Tähtinen, Lassi; Department of Built Environment; Real Estate; Real Estate
    In our increasingly more complex and uncertain society, possible crises have grown in numbers and become more systemic in their nature (UNDRR 2022). In parallel, due to continuous urbanization, cities and built environments are becoming a more central part of societies and therefore crucial also for crisis management and resilience development (Al-Humaiqani & Al-Ghamdi 2022). Hence, there is a growing body of theoretical and empirical literature concerning how to manage crises and develop resilience in built environments. This chapter is an introduction to the conceptual and practical understanding of crisis management and resilience development and their applicability in cities and built environments and creates the foundations for the following chapters.
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    Impact of changing urban typologies on residential vegetation and its climate-effects – A case study from Helsinki, Finland
    (Elsevier GmbH, 2024-05) Leppänen, Paula Kaisa; Kinnunen, Antti; Hautamäki, Ranja; Järvi, Leena; Havu, Minttu; Junnila, Seppo; Tahvonen, Outi; Department of Architecture; Department of Built Environment; Real Estate; University of Helsinki; Häme University of Applied Sciences
    Residential green spaces are an integral part of urban green infrastructure and its role in climate change adaptation and mitigation. Various urban typologies and changing planning practices affect the amount and structure of residential greenery, which has a direct impact on climate benefits. While urban green and its climate benefits have received increasing attention, there is still limited knowledge on how changing planning practices and related urban typologies impact residential vegetation and its capacity to deliver climate benefits. This paper aims to address this gap by determining the impact of planning practices on residential vegetation, focussing specifically on climate mitigation and adaptation. With the case study of Helsinki, characterized by a high share of green areas, the paper first examines how construction year and urban density affect the amount and structure of vegetation on residential properties. Second, it estimates the carbon sequestration and summer temperatures in the present-day climate. The paper applies spatial modelling and regression analysis to estimate the impact of construction year on the studied dependent variables, while controlling density via gross floor area of buildings. The study demonstrates that the average amount of residential vegetation, as measured using canopy and vegetation cover, has declined 15 percentage points from the 1970 s to early 2010 s and the canopy to low vegetation ratio has decreased constantly over the periods studied. The decline of the canopy cover in particular has reduced the climate benefits of residential vegetation. The paper highlights the significant impact of gross floor area and planning practices on urban vegetation cover and the climate benefits it provides. It also stresses the importance of ensuring sufficient tree cover and permeable surfaces in cities with progressive climate mitigation agenda throughout the chain of urban planning, construction, and subsequent property management stages.
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    Enabling electrical response through piezoelectric particle integration in AA2017-T451 aluminium parts using FSP technology
    (Institute of Physics Publishing, 2024-06) Ferreira, Pedro M.; Caçador, David; Machado, Miguel A.; Carvalho, Marta S.; Vilaça, Pedro; Sorger, Gonçalo; Farias, Francisco Werley Cipriano; Figueiredo, Arthur Ribeiro; Vidal, Catarina; Department of Mechanical Engineering; Materials to Products; NOVA University Lisbon; Universidade Federal do Rio de Janeiro
    In the field of structural engineering, the integration of smart materials and structural health monitoring (SHM) has given rise to self-sensing materials (SSM), leading to a paradigm shift in SHM. This paper focuses on the interplay between self-sensing capabilities and the piezoelectric properties of lead zirconate titanate (PZT) and barium titanate (BT) in aluminium components. Leveraging Friction Stir Processing (FSP), the study explores the synthesis and performance of SSMs with embedded piezoelectric particles, potentially transforming structural engineering. The paper highlights FSP as a key methodology for incorporating piezoelectric particles into structural materials, showcasing its potential in developing SSMs with enhanced functionalities. A specific focus is placed on integrating PZT and BT particles into AA2017-T451 aluminium parts using FSP, with metallographic assessments and mechanical property evaluations conducted to analyse particle distribution and concentration. This study shows how BT and PZT particles are incorporated into AA2017-T451 aluminium to create a SSM that responds to external stimuli. Under cyclic loading, the SSMs exhibit a linear load-electrical response correlation, with sensibility increasing at lower frequencies. Metallographic analysis shows homogeneous particle distribution, while PZT induces increased brittleness and brittle fractures. Yield strength remains relatively stable, but ultimate strength decreases post-FSP. Hardness variations indicate weaker bonding with PZT particles. Eddy’scurrent testing aligns with hardness profiles, and sensorial characterization reveals a non-linear frequency-sensibility relationship, showcasing the SSMs’ suitability for low-frequency applications, particularly with PZT embedment.
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    Individual tree segmentation and species classification using high-density close-range multispectral laser scanning data
    (Elsevier, 2023-08) Hakula, Aada; Ruoppa, Lassi; Lehtomäki, Matti; Yu, Xiaowei; Kukko, Antero; Kaartinen, Harri; Taher, Josef; Matikainen, Leena; Hyyppä, Eric; Luoma, Ville; Holopainen, Markus; Kankare, Ville; Hyyppä, Juha; Department of Built Environment; MeMo; National Land Survey of Finland; University of Helsinki; University of Eastern Finland
    Tree species characterise biodiversity, health, economic potential, and resilience of an ecosystem, for example. Tree species classification based on remote sensing data, however, is known to be a challenging task. In this paper, we study for the first time the feasibility of tree species classification using high-density point clouds collected with an airborne close-range multispectral laser scanning system – a technique that has previously proved to be capable of providing stem curve and volume accurately and rapidly for standing trees. To this end, we carried out laser scanning measurements from a helicopter on 53 forest sample plots, each with a size of 32 m × 32 m. The plots covered approximately 5500 trees in total, including Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H.Karst.), and deciduous trees such as Downy birch (Betula pubescens Ehrh.) and Silverbirch (Betula pendula Roth). The multispectral laser scanning system consisted of integrated Riegl VUX-1HA, miniVUX-3UAV, and VQ-840-G scanners (Riegl GmbH, Austria) operating at wavelengths of 1550 nm, 905 nm, and 532 nm, respectively. A new approach, layer-by-layer segmentation, was developed for individual tree detection and segmentation from the dense point cloud data. After individual tree segmentation, 249 features were computed for tree species classification, which was tested with approximately 3000 trees. The features described the point cloud geometry as well as single-channel and multi-channel reflectance metrics. Both feature selection and the tree species classification were conducted using the random forest method. Using the layer-by-layer segmentation algorithm, trees in the dominant and co-dominant categories were found with detection rates of 89.5% and 77.9%, respectively, whereas suppressed trees were detected with a success rate of 15.2%–42.3%, clearly improving upon the standard watershed segmentation. The overall accuracy of the tree species classification was 73.1% when using geometric features from the 1550 nm scanner data and 86.6% when combining the geometric features with reflectance information of the 1550 nm data. The use of multispectral reflectance and geometric features improved the overall classification accuracy up to 90.8%. Classification accuracies were as high as 92.7% and 93.7% for dominant and co-dominant trees, respectively.
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    Ontology-based construction inspection planning : a case study of thermal building insulation
    (2023) Seiss, Sebastian; Boden, Markus; Melzner, Jürgen; Zheng, Yuan; Delval, Thibaut; El Chamaa, Rayan; Department of Mechanical Engineering; Mechatronics; Bauhaus-Universität Weimar; Centre Scientifique et Technique du Bâtiment
    Poor construction quality is one of the most significant challenges for the construction industry. However, failures can be avoided or minimized by inspections based on detailed quality inspection plans as a part of quality assurance. Therefore, structured and project-specific planning of inspection plans is required to provide inspectors with the right information. Nevertheless, inspection planning is mainly manual, dependent on the individual’s experience and high level of effort. As a result, inspection planning is often neglected and limited to providing general checklists that often lack semantically rich descriptions and are unspecific concerning individual project requirements. Furthermore, proper planning of inspections requires multiple information sources, such as building design, schedules, contractual and supplier guidelines, and standards, all of which must be provided or linked via an information model. Current research lacks an adequate formalized knowledge model to provide the knowledge-driven inspection planning process with the necessary domain knowledge to support inspection planning with heterogeneous information defined in isolated systems. Therefore, this paper extends the Ontology for Construction Quality Assurance (OCQA) with the OCQA-Thermal Insulation (OCQA-TI) to formalize thermal insulation inspection planning knowledge. The OCQA offers a new linked data model that provides explicit knowledge of quality inspection planning. The development of the OCQA-TI follows the Linked Open Terms (LOT) methodology and is implemented using the Web Ontology Language (OWL). The proposed ontology is evaluated using various approaches, including automatic consistency checking, answering competency questions, and criteria-based evaluation. The results indicate that the OCQA-TI can provide inspectors with relevant inspection planning knowledge and integrate various related information streams, thus providing a more comprehensive and efficient approach to insulation inspection planning. The functionality of OCQA-TI enables the fulfillment of increased sustainability and energy efficiency requirements by providing insulation inspection knowledge.
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    Evaluation of 3D-printed Pattern Material for Heat-hardened Inorganic Moulds
    (AGH University of Science and Technology Press, 2024-06-05) Jalava, Kalle; Anwar, Nurul; Orkas, Juhani; Department of Mechanical Engineering; Materials to Products
    Inorganic binders for sand moulding are currently of high interest due to the need to lessen our environmental impact and emissions. In this study, a heat hardened solid inorganic sodium silicate binder was tested with a 3D printed resin material to see how the use of such a material affected a silica mould’s quality, e.g. surface roughness. Results were compared to moulds made with metallic patterns. The unmodified binder had sticking issues when used with a metallic pattern, resulting in a rough as-moulded surface. Such issues were not seen with the printed resin patterns, also hinting at good performance with binders that contain performance increasing additives. The resin pattern material has a Heat Deflection Temperature (HDT) of 230°C, enabling the use of inorganic binders that require temperatures between 160–200°C to harden and dry. Additive manufacturing of such materials also allows designs for other hardening techniques than furnace heating, such as microwave heating. The moulds hardened with microwaves did not exhibit sticking issues. Additive manufacturing of tooling is a potential source of geometrical variation in final castings and are also studied in this work. In general, switching from traditional sand moulding patterns used with organic binder systems to inorganic systems, the patterns and core boxes need to be replaced by new ones made of a metallic or other heat resistant material. The studied material is a promising option for such a switch, especially when a complex shape enabled by additive manufacturing is also required.
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    Real estate and sustainable crisis management in urban environments : challenges and solutions for resilient cities
    (2024-05-31) Department of Built Environment; Department of Architecture; Toivonen, Saija; Heinonen, Sirkka; Verma, Ira; Castaño-Rosa, Raúl; Wilkinson, Sara; Real Estate
    The aim of this book is to promote the dynamic resilience of societies by identifying, analysing, and exemplifying the role of space and land use in both anticipated and unanticipated primary and secondary crisis situations. The book brings together the expertise of a unique team of researchers and methods from fields of futures studies, land use planning, social sustainability and wellbeing, architecture, spatial planning, design and real estate economics, and presents a novel understanding of the direct and indirect impacts of possible crises in the space and land use context. It goes on to discuss the concept of resilience and exemplifies potential solutions and offers a holistic and forward-looking approach for crisis management through a lens of social sustainability and wellbeing, making an important contribution to the promotion of wellbeing in the built environment, especially in terms of land and residential space and building use. This book does not only identify barriers and successful incentives in resilient crisis management but also discusses the role of different stakeholders (e.g., households, office workers, real estate owners, space occupants, firms, the public sector, etc.) in crisis management. Finally, international case studies aiming to tackle the challenging landscape of future threats are presented, along with novel tools to support the development of future policies, regulations, and management practices in the built environment, which can increase the dynamic resilience of societies. Overall, this book is essential reading for decision-makers in the public and private sectors, urban developers, space and spatial designers, architects, planners, community stakeholders, real estate investors, facility managers and crisis and corporate responsibility managers.
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    Study on Multiple Effects of Self-Healing Properties and Thermal Characteristics of Asphalt Pavement
    (MDPI AG, 2024-05) Zhang, Fan; Sun, Yuxuan; Kong, Lingyun; Cannone Falchetto, Augusto; Yuan, Dongdong; Wang, Weina; Department of Civil Engineering; Mineral Based Materials and Mechanics; Chongqing Jiaotong University; Chang'an University
    Asphalt pavements are prone to cracking in low-temperature environments, and microwave heating (MH) can heal the cracks effectively. This research mainly investigates the different MH effects on the self-healing properties of asphalt mixtures. With this objective, the three-point splitting test is conducted to generate the cracks. A microwave oven is employed to heat the samples, and a thermal camera measures the surface temperature. Results indicate that heating power and time show a positive linear correlation with healing efficiency, and the HI of the samples can reach over 80%. The HI of the samples decreases with the heating cycle, but the sample with reasonable power and time still has a HI higher than 70% after 5 cycles. The temperature peaks on thermal images indicate that uneven heating exists during heating, but the heating uniformity is within an acceptable range. The healing efficiency level (HEL) suggests that asphalt mixtures have very low inefficient healing behavior if the heating time is below 45 s, but HEL can reach 86.14% at 700 W after 60 s. Furthermore, although the HI of strength shows ideal results, the recovery of other crack parameters, including stiffness, fracture energy, flexible index, and crack resistance index, are not satisfactory.
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    Drift test analysis of a conventional planing hull utilising CFD and 2D+t models
    (Elsevier Ltd, 2024-09-15) Hosseini, Azim; Tavakoli, Sasan; Dashtimanesh, Abbas; Mikkola, Tommi; Hirdaris, Spyros; Department of Mechanical Engineering; Marine and Arctic Technology; Persian Gulf University; KTH Royal Institute of Technology; American Bureau of Shipping, Greece
    This paper investigates the maneuvering characteristics of a planing hull free to move in heave and pitch directions undergoing a steady drift test. Results assess and compare predictions from Computational Fluid Dynamics (CFD) Detached Eddy Simulation (DES) and a 2D + t strip theory models against available experimental data from Katayama et al. (2005). At high yaw angles and high Froude numbers of predictions from both models marginally deviate from the experimental longitudinal force measurements. Whereas strip theory confronts difficulties in predicting dynamic trim angle and CG rise-up when either Froude number or yaw angle increases and hence nonlinear hydrodynamics prevail, CFD generally agrees well with experimental data. The CFD model is seen to result in numerical ventilation in zero-drift cases, leading to lower pressure and a localized reduction in the skin friction coefficient. These phenomena are hypothesized to contribute to the under-prediction of trim angle and longitudinal force in zero-drift scenarios. Strip theory provides less reliable results in terms of predicting the sway forces at larger yaw angles, the yaw moment at low Froude numbers and sway forces and associated maximum pressures near the stagnation line. This model cannot capture the asymmetric pressure distribution that emerges on the bottom of the hull at large speed and yaw angles, which is likely to be one of the reasons for errors in predicting the side force. Detached Eddy Simulations demonstrate the strong asymmetric vorticity field formation on the exposed side of the hull at nonzero drift angle. This means that added masses used in the 2D + t model can cause large errors in equilibrium predictions.
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    Architecture for data-centric and semantic-enhanced industrial metaverse : Bridging physical factories and virtual landscape
    (Elsevier B.V., 2024-06) Tu, Xinyi; Ala-Laurinaho, Riku; Yang, Chao; Autiosalo, Juuso; Tammi, Kari; Department of Mechanical Engineering; Mechatronics; Mechatronics
    The metaverse paradigm has recently captured increasing scholarly and industrial attention, particularly within the scope of human-centric Industry 5.0. In this context, the metaverse promises a transformative confluence of the physical and digital realms, offering unparalleled avenues for human augmentation in industrial applications. Yet, while several conceptual metaverse architectures and illustrative case studies have emerged, they scarcely delve deep into the nuanced practice of cultivating the industrial metaverse for factory-scale applications. Addressing this research gap, this work introduces a novel architecture for a data-centric and semantic-enhanced industrial metaverse. The architecture intricately weaves the physical factory domain with the metaverse, fortified by a suite of ten modules, facilitating data flow and knowledge synchronization with the integration of digital twins and semantic models. The practical application and relevance of this architecture are further accentuated through a case study focused on in-plant material flow tracking. Emerging results underline that our architecture encapsulates the essential components for constructing a factory-scale industrial metaverse. Future research will be geared towards a comprehensive validation of the proposed metaverse architecture, culminating in tangible implementations across diverse industrial contexts.
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    The complex interplay between sectoral energy consumption and economic growth : Policy implications for Iran and beyond
    (Elsevier, 2024-06-15) Ghadaksaz, Hesam; Saboohi, Yadollah; Department of Mechanical Engineering; Energy Conversion and Systems; Sharif University of Technology
    Iran's abundant energy reserves starkly contrast with recent power and gas shortages, particularly impacting the industrial sector. Furthermore, long-term trends reveal a concerning pattern where total primary energy consumption has outpaced economic growth, doubling in recent decades. These challenges emphasize the need for a thorough evaluation of the intricate interplay between sectoral energy consumption and economic output in Iran, bearing profound policy implications. The current study employs ARDL and VECM approaches to analyze empirical long- and short-term dynamics. Regarding Iran, the results unveil causal relationships from industrial energy consumption to GDP and from GDP to energy consumption in buildings. Notably the significant positive value of elasticity of GDP with respect to industrial energy use highlights the need for nuanced energy management measures. Variations across sectors underscore the justification for recognizing industrial energy consumption as productive energy use. The results gain additional support from a panel data analysis spanning fourteen diverse countries, bearing significance for IAMs applied in climate change research. While IAMs traditionally employ total energy consumption or the sectoral energy uses collectively, as production factors, the research highlights the need to reevaluate model frameworks for potential different outcomes from established practices.