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Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Emergency situations may differ in many ways but they share some common characteristics, such as the sudden onset and the need to transparently evaluate various usually conflicting objectives. In nuclear power generation, however, emergency situations constitute a special challenge. The focus of this paper is to highlight the role of multi‐criteria decision analysis (MCDA) in nuclear emergency and recovery management on the basis of a hypothetical case study.

Multi‐attribute value theory as one field of research within MCDA is introduced. Special emphasis is placed on the modelling of the decision makers' preferences which is a crucial part in any multi‐criteria analysis. A central aim is to facilitate the preference elicitation in group decision processes.

The management of emergency situations in nuclear power generation necessitates the consideration of technical, economic, environmental, socio‐psychological and political aspects. Furthermore, various stakeholder and expert groups with diverse background knowledge and different views, responsibilities and interests are involved in such a decision‐making process. MCDA can help to take into account various incommensurable aspects and the subjective preferences of the decision makers and thus contribute to transparency and traceability of decision‐making processes. Since the preference parameters are inherently afflicted with uncertainties, thorough sensitivity analyses are important to visualise the impact of the uncertainties in an understandable way.

A new approach to sensitivity analysis is proposed, allowing one to comprehensibly visualise and communicate the impact of the uncertainties associated with the subjective preference parameters on the results of the decision analysis.

First, the contributions of spatial characteristics to microclimate were analyzed. And the results from mobile measurements were compared to those from fixed measurements to examine accuracy of mobile method. Air temperature and physiologically equivalent temperature (PET) profiles were plotted to explore the impacts of the spatial characteristics of that urban square and local street.

This research investigates the effects of urban canyons and landscape on air temperature and outdoor thermal comfort in an open square in Seoul, Korea, a city of diverse thermal environments. Mobile field measurements were carried out to obtain local meteorological data based on higher spatial resolution.

On a day in October under clear sky, air temperature and PET differences of up to 1.77 °C and 9.6 °C were observed at 2 p.m. and 3 p.m., respectively. These were mainly from the impact of shading effects caused by surrounding obstacles. The current layout and volume of vegetation in the square seemed not effective for reducing air temperature and improving thermal comfort, which needs further study.

The authors tested a way to investigate time delay when using mobile measurements by correcting measured local data using adjacent meteorological observatory data. The findings of and limitations on mobile station-based field measurement and analysis are discussed herein.

In this study, 12 potential wake vortex encounters that were reported at a major European airport have been investigated. Because almost all encounters occurred in ground proximity, most pilots conducted a go-around. The primary purpose of this study is to discriminate between incidents caused by wake vortices or rather by effects like wind shear or turbulence. Detailed knowledge of real-world encounter scenarios and identification of worst-case conditions during the final approach constitute highly relevant background information to assess the standard scenario used for the definition of revised wake turbulence separations.

Wake vortex predictions using the probabilistic two-phase wake vortex model (P2P) are used to investigate the incidents in detail by using data from the flight data recorder, meteorological instrumentation at the airport and numerical weather prediction.

In the best documented cases, the flight tracks through the vortices could be reconstructed in good agreement with wake vortex predictions and recorded aircraft reactions. Out of the eight plausible wake vortex encounters, five were characterized by weak crosswinds below 1.5 m/s combined with tailwinds. This meteorological situation appears favourable for encounters because, on the one hand, weak crosswinds may compensate the self-induced lateral propagation of the upwind vortex, such that it may hover over the runway directly in the flight path of the following aircraft. On the other hand, tailwinds limit the propagation of the so-called end effects caused by the breakdown of lift during touchdown.

The installation of plate lines beyond the runway tails may improve safety by reducing the number of wake vortex encounters.

The conducted investigations provide high originality and value for both science and operational application.

Troposphere delay is one of the important error sources in global positioning system (GPS) positioning. The purpose of this paper is to analyze the accuracy and adaptability of GPS troposphere error correction models, and to provide theoretic foundation for model selection in GPS accurate positioning.

The principle of troposphere delay error effecting on GPS signals is theoretically analyzed. The model peculiarity and modeling method of the four common troposphere delay correction models: Hopfield, Saastamoinen, Black, and Egnos models are discussed detailedly. With the measurement data from Crustal Dynamics Data Information System of the technical support institution for GPS, the accuracy and applicability of the four models are quantificationally studied.

For a low elevation, Hopfield, Saastamoinen, and Black models show great agreement with each other, and have quite high precision. In the zenith direction, the maximal troposphere delay error of three models are all less than 1 dm, but Black and Hopfield models have higher precision than Saastamoinen model. Black model can be regarded as the improved form of Hopfield model: for a high elevation, precision of two models are close, while for a low elevation, Black model shows to be more effective than Hopfield model. The precision of Egnos model is quite lower than that of Black, Hopfield, and Saastamoinen models. However, Egnos model can be a better choice when it is difficult to obtain real‐time meteorological data in certain application environment.

This paper makes thorough research on GPS troposphere delay error correction models. The conclusions are presented for selecting troposphere delay models, which are useful for practical engineering application.

In this paper, the relationship between meteorological conditions and diseases is investigated. The relative fitting errors for nine kinds of diseases are within the limit of 0.048‐0.228. These results are the bases of researches of mechanism and a component of the numerical model which has been used in the prediction of diseases.

The objective of this study is to develop and validate a neural‐based modelling methodology applicable to site‐specific short‐ and medium‐term ozone concentration forecasting. A novel modelling technique utilizing two feed forward artificial neural networks (FFNN) is developed to improve the performance of time series predictions.

Air pollution and meteorological data were collected for one year in two locations in Kuwait. The hourly averages of the data were processed to generate a covariance matrix and analyzed to generate the principal component method. A two‐FFNN model is then used to predict the actual data.

The newly developed model improves the prediction accuracy over the conventional method. Owing to the presence of noise and other minor disturbances in the data, shorter‐range modelling gives better modelling results.

A novel modelling technique is developed to predict the time series of zone concentration.

The purpose of this paper is to adopt an assemblage theory lens to examine the socio-material forces shaping the development of an infrastructure for the recovery of archived historical marine weather records for use in contemporary climate data sets.

The authors adopted a data journeys approach to research design, conducting in-depth semi-structured interviews with climate scientists, citizen scientists and a climate historian who were engaged at key sites across the journey of data from historical record to the International Comprehensive Ocean-Atmosphere Data Set database. Interview data were complemented by further qualitative data collected via observations of working practices, a digital ethnography of citizen scientists’ online forums, and documentation relevant to the circulation and governance of climate data across emergent data infrastructures. Data were thematically analysed (Ryan and Bernard, 2003), with themes being informed primarily by the theoretical framework.

The authors identify and critically examine key points of friction in the constitution of the data recovery infrastructure and the circulation of data through it, and identify the reflexive and adaptive nature of the beliefs and practices fostered by influential actors within the assemblage in order to progress efforts to build an infrastructure despite significant challenges. The authors conclude by addressing possible limitations of some of these adaptive practices within the context of the early twenty-first century neoliberal state, and in light of current debates about data justice.

The paper draws upon original empirical data and a novel theoretical framework that draws together Deleuze and Guattari’s assemblage theory with key concepts from the field of critical data studies (data journeys, data friction and data assemblage) to illuminate the socio-material constitution of the data recovery infrastructure within the context of the early twenty-first century neoliberal state.

This paper aims to investigate the impacts of introducing voids combinations on natural ventilation performance in high-rise residential building living unit.

This study was carried out through field measurement and computational fluid dynamics methods. The parameters of the study are void types and sizes, and a wind angle was used to formulate case studies.

The results indicate that the provision of a single-sided horizontal void larger by 50% increase the indoor air velocity performance up to 322.37% to 0.471 m/s in the living unit and achieves the required velocity for thermal comfort.

Passive design features are the most desirable techniques to enhance natural ventilation performance in the high-rise residential apartments for thermal comfort and indoor air quality purposes.

The combination of desalination technology with renewable energy sources (RES) provides a sustainable approach for increasing potable water availability without imposing negative environmental effects. This paper aims to present the development of a platform, which is an internet-based tool integrating the design optimization of desalination systems with spatial modeling based on a geographic information system (GIS).

The proposed platform assists decision-makers to select the optimal location and configuration of both the energy- and water-related subsystems of desalination plants that are power-supplied by RES, such that the lifetime cost of the overall desalination plant is minimized. It enables to optimize the desalination plant site selection and sizing with various hybrid power supply (solar, wind, wave and electrical grid power systems) and desalination technologies combinations, while simultaneously exploiting spatial technologies in an internet-based GIS platform.

A pilot study for the optimal design of stand-alone and grid-connected desalination plants powered by RES is presented, which demonstrates the functionality and features of the proposed platform. It is also shown that a grid-connected desalination plant designed by the proposed software design tool exhibits significantly lower lifetime installation and maintenance costs compared to its stand-alone counterpart.

The proposed platform combines technological, scientific and industrial knowledge with information about societal/political conditions and geo-spatial technologies in a user-friendly graphical interface. Therefore, it provides a design tool enabling its users to secure water supply in a sustainable and economically viable manner.