TY - JOUR A1 - Band, Shahab S. A1 - Janizadeh, Saeid A1 - Chandra Pal, Subodh A1 - Saha, Asish A1 - Chakrabortty, Rabbin A1 - Shokri, Manouchehr A1 - Mosavi, Amir Hosein T1 - Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility JF - Sensors N2 - This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) based on a deep learning neural network (DLNN) model and an ensemble particle swarm optimization (PSO) algorithm with DLNN (PSO-DLNN), comparing these approaches with common artificial neural network (ANN) and support vector machine (SVM) models in Shirahan watershed, Iran. For this purpose, 13 independent variables affecting GES in the study area, namely, altitude, slope, aspect, plan curvature, profile curvature, drainage density, distance from a river, land use, soil, lithology, rainfall, stream power index (SPI), and topographic wetness index (TWI), were prepared. A total of 132 gully erosion locations were identified during field visits. To implement the proposed model, the dataset was divided into the two categories of training (70%) and testing (30%). The results indicate that the area under the curve (AUC) value from receiver operating characteristic (ROC) considering the testing datasets of PSO-DLNN is 0.89, which indicates superb accuracy. The rest of the models are associated with optimal accuracy and have similar results to the PSO-DLNN model; the AUC values from ROC of DLNN, SVM, and ANN for the testing datasets are 0.87, 0.85, and 0.84, respectively. The efficiency of the proposed model in terms of prediction of GES was increased. Therefore, it can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon. KW - Geoinformatik KW - Maschinelles Lernen KW - gully erosion susceptibility KW - deep learning neural network KW - partical swarm optimization KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210122-43341 UR - https://www.mdpi.com/1424-8220/20/19/5609 VL - 2020 IS - Volume 20, issue 19, article 5609 SP - 1 EP - 27 PB - MDPI CY - Basel ER - TY - JOUR A1 - Reichert, Ina A1 - Olney, Peter A1 - Lahmer, Tom T1 - Combined approach for optimal sensor placement and experimental verification in the context of tower-like structures JF - Journal of Civil Structural Health Monitoring N2 - When it comes to monitoring of huge structures, main issues are limited time, high costs and how to deal with the big amount of data. In order to reduce and manage them, respectively, methods from the field of optimal design of experiments are useful and supportive. Having optimal experimental designs at hand before conducting any measurements is leading to a highly informative measurement concept, where the sensor positions are optimized according to minimal errors in the structures’ models. For the reduction of computational time a combined approach using Fisher Information Matrix and mean-squared error in a two-step procedure is proposed under the consideration of different error types. The error descriptions contain random/aleatoric and systematic/epistemic portions. Applying this combined approach on a finite element model using artificial acceleration time measurement data with artificially added errors leads to the optimized sensor positions. These findings are compared to results from laboratory experiments on the modeled structure, which is a tower-like structure represented by a hollow pipe as the cantilever beam. Conclusively, the combined approach is leading to a sound experimental design that leads to a good estimate of the structure’s behavior and model parameters without the need of preliminary measurements for model updating. KW - Strukturmechanik KW - Finite-Elemente-Methode KW - tower-like structures KW - experimental validation KW - mean-squared error KW - fisher-information matrix Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44701 UR - https://link.springer.com/article/10.1007/s13349-020-00448-7 VL - 2021 IS - volume 11 SP - 223 EP - 234 PB - Heidelberg CY - Springer ER - TY - JOUR A1 - Schirmer, Ulrike A1 - Osburg, Andrea T1 - A new method for the quantification of adsorbed styrene acrylate copolymer particles on cementitious surfaces: a critical comparative study JF - SN Applied Sciences N2 - The amount of adsorbed styrene acrylate copolymer (SA) particles on cementitious surfaces at the early stage of hydration was quantitatively determined using three different methodological approaches: the depletion method, the visible spectrophotometry (VIS) and the thermo-gravimetry coupled with mass spectrometry (TG–MS). Considering the advantages and disadvantages of each method, including the respectively required sample preparation, the results for four polymer-modified cement pastes, varying in polymer content and cement fineness, were evaluated. To some extent, significant discrepancies in the adsorption degrees were observed. There is a tendency that significantly lower amounts of adsorbed polymers were identified using TG-MS compared to values determined with the depletion method. Spectrophotometrically generated values were ​​lying in between these extremes. This tendency was found for three of the four cement pastes examined and is originated in sample preparation and methodical limitations. The main influencing factor is the falsification of the polymer concentration in the liquid phase during centrifugation. Interactions in the interface between sediment and supernatant are the cause. The newly developed method, using TG–MS for the quantification of SA particles, proved to be suitable for dealing with these revealed issues. Here, instead of the fluid phase, the sediment is examined with regard to the polymer content, on which the influence of centrifugation is considerably lower. KW - Zement KW - Polymere KW - polymer adsorption KW - cement KW - visible spectrophotometry KW - depletion method KW - mass spectrometry Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44729 UR - https://link.springer.com/article/10.1007/s42452-020-03825-5 VL - 2020 IS - Volume 2, article 2061 SP - 1 EP - 11 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Dokhanchi, Najmeh Sadat A1 - Arnold, Jörg A1 - Vogel, Albert A1 - Völker, Conrad T1 - Measurement of indoor air temperature distribution using acoustic travel-time tomography: Optimization of transducers location and sound-ray coverage of the room JF - Measurement N2 - Acoustic travel-time TOMography (ATOM) allows the measurement and reconstruction of air temperature distributions. Due to limiting factors, such as the challenge of travel-time estimation of the early reflections in the room impulse response, which heavily depends on the position of transducers inside the measurement area, ATOM is applied mainly outdoors. To apply ATOM in buildings, this paper presents a numerical solution to optimize the positions of transducers. This optimization avoids reflection overlaps, leading to distinguishable travel-times in the impulse response reflectogram. To increase the accuracy of the measured temperature within tomographic voxels, an additional function is employed to the proposed numerical method to minimize the number of sound-path-free voxels, ensuring the best sound-ray coverage of the room. Subsequently, an experimental set-up has been performed to verify the proposed numerical method. The results indicate the positive impact of the optimal positions of transducers on the distribution of ATOM-temperatures. KW - Bauphysik KW - Bauklimatik KW - Akustische Laufzeit-Tomographie Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220524-46473 UR - https://www.sciencedirect.com/science/article/abs/pii/S0263224120304723?via%3Dihub VL - 2020 IS - Volume 164, article 107934 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Cerejeiras, Paula A1 - Kähler, Uwe A1 - Legatiuk, Anastasiia A1 - Legatiuk, Dmitrii T1 - Discrete Hardy Spaces for Bounded Domains in Rn JF - Complex Analysis and Operator Theory N2 - Discrete function theory in higher-dimensional setting has been in active development since many years. However, available results focus on studying discrete setting for such canonical domains as half-space, while the case of bounded domains generally remained unconsidered. Therefore, this paper presents the extension of the higher-dimensional function theory to the case of arbitrary bounded domains in Rn. On this way, discrete Stokes’ formula, discrete Borel–Pompeiu formula, as well as discrete Hardy spaces for general bounded domains are constructed. Finally, several discrete Hilbert problems are considered. KW - Dirac-Operator KW - Randwertproblem KW - Funktionentheorie KW - discrete Dirac operator KW - discrete monogenic functions KW - discrete boundary value problems Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44746 UR - https://link.springer.com/article/10.1007/s11785-020-01047-6 VL - 2021 IS - Volume 15, article 4 SP - 1 EP - 32 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Becher, Lia A1 - Völker, Conrad A1 - Rodehorst, Volker A1 - Kuhne, Michael T1 - Background-oriented schlieren technique for two-dimensional visualization of convective indoor air flows JF - Optics and Lasers in Engineering N2 - This article focuses on further developments of the background-oriented schlieren (BOS) technique to visualize convective indoor air flow, which is usually defined by very small density gradients. Since the light rays deflect when passing through fluids with different densities, BOS can detect the resulting refractive index gradients as integration along a line of sight. In this paper, the BOS technique is used to yield a two-dimensional visualization of small density gradients. The novelty of the described method is the implementation of a highly sensitive BOS setup to visualize the ascending thermal plume from a heated thermal manikin with temperature differences of minimum 1 K. To guarantee steady boundary conditions, the thermal manikin was seated in a climate laboratory. For the experimental investigations, a high-resolution DLSR camera was used capturing a large field of view with sufficient detail accuracy. Several parameters such as various backgrounds, focal lengths, room air temperatures, and distances between the object of investigation, camera, and structured background were tested to find the most suitable parameters to visualize convective indoor air flow. Besides these measurements, this paper presents the analyzing method using cross-correlation algorithms and finally the results of visualizing the convective indoor air flow with BOS. The highly sensitive BOS setup presented in this article complements the commonly used invasive methods that highly influence weak air flows. KW - Raumklima KW - Raumluftströmungen KW - Flow visualization KW - Convective indoor air flow KW - Background-oriented schlieren KW - Human thermal plume KW - Cross-correlation Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220810-46972 N1 - This article is published by Elsevier in Optics and Lasers in Engineering 134 (2020) 106282 and may be found at https://doi.org/10.1016/j.optlaseng.2020.106282 Copyright © 2020 Elsevier Ltd. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the authors and Elsevier Ltd. VL - 2020 IS - Volume 134, article 106282 ER - TY - JOUR A1 - Seichter, Cosima Zita A1 - Neßler, Miriam A1 - Knopf, Paul T1 - Mapping In-Betweenness. The Refugee District in Belgrade in the Context of Migration, Urban Development, and Border Regimes JF - Movements. Journal for Critical Migration and Border Regime Studies N2 - The contribution explores the migratory situation on the Balkans and more specifically in the so-called Refugee District in Belgrade from a spatial perspective. By visualizing the areas of tensions in the Refugee District, the city of Belgrade, Serbia and Europe it aims to disentangle the political and socio-spatial levels that lead to the stuck situation of in-betweenness at the gates of the European Union. KW - Europäische Union KW - Balkan KW - Flüchtlingspolitik KW - Balkanroute Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210806-44807 UR - http://movements-journal.org/issues/08.balkanroute/11.seichter,nessler,knopf--mapping-in-betweenness.html VL - 2020 IS - Volume 5, Issue 1 SP - 1 EP - 9 CY - Göttingen ER - TY - JOUR A1 - Wolf, Mario A1 - Londong, Jörg T1 - Transformation der Siedlungswasserwirtschaft – Steuerungsmechanismen im Diskurs ressourcenorientierter Systemansätze am Beispiel von Thüringen T1 - Transformation of the wastewater sector – The ability of state level controlling mechanisms to enhance the implementation of resource-oriented sanitation systems JF - Raumforschung und Raumordnung N2 - Neuartige Sanitärsysteme zielen auf eine ressourcenorientierte Verwertung von Abwasser ab. Erreicht werden soll dies durch die separate Erfassung von Abwasserteilströmen. In den Fachöffentlichkeiten der Wasserwirtschaft und Raumplanung werden neuartige Sanitärsysteme als ein geeigneter Ansatz für die zukünftige Sicherung der Abwasserentsorgung in ländlichen Räumen betrachtet. Die Praxistauglichkeit dieser Systeme wurde zwar in Forschungsprojekten nachgewiesen, bisher erschweren jedoch für Abwasserentsorger vielfältige Risiken die Einführung einer ressourcenorientierten Abwasserbewirtschaftung. Ausgehend von einer Untersuchung der Kontexte bei der Umsetzung eines neuartigen Sanitärsystems im ländlichen Raum Thüringens wird in diesem Beitrag der Frage nachgegangen, wie auf Landesebene mit dem abwasserwirtschaftlichen Instrumentarium die Einführung von ressourcenorientierten Systemansätzen unterstützt werden kann. Zentrale Elemente des Beitrags sind die Darstellung der wesentlichen Transformationsrisiken in Bezug auf die Einführung innovativer Lösungsansätze, eine Erläuterung der spezifischen abwasserwirtschaftlichen Instrumente sowie die Darlegung von Steuerungsansätzen,mit denen die Einführung von neuartigen Sanitärsystemen gefördert werden kann. Im Ergebnis wird die Realisierbarkeit von neuartigen Sanitärsystemen durch den strategischen Einsatz des Instrumentariums deutlich, gleichwohl die Wasserwirtschaft durch die Erweiterung der bisherigen Systemgrenzen auf die Kooperation mit anderen Bereichen der Daseinsvorsorge angewiesen ist. N2 - New sanitary systems are an intelligent way to approach wastewater management in the face of demographic and climatic changes. It is also compatible with the emerging paradigm of a resource-oriented management of wastewater. While the general technical applicability of resource-oriented systems has been proven in various projects, the realisation is still on hold. The reasons can be found in several risks for wastewater disposal companies that are linked to the implementation process. Based on an analysis of the general context of an implementation of a new sanitary system in a typical rural area of Eastern Germany, this paper analyses to which extend the implementation of such innovative approaches can be facilitated by the regulation system and which steps need to be taken. According to this aim, risks that can hamper the transformation of the wastewater sector are identified, major administrative controlling mechanisms outlined and depicted in which strategic approach these could be used in order to foster the implementation of resource-oriented sanitary systems. As a result, the feasibility of the implementation of new alternative sanitary systems through the strategic application of the controlling mechanisms is generally proven. However, collaborations of the wastewater sectors with stakeholders of other sectors are required. KW - Raumordnung KW - Abwasserwirtschaft KW - Neuartige Sanitärsysteme KW - Instrument KW - Transformation KW - Siedlungswasserwirtschaft KW - Steuerungsansätze KW - Transformationsrisiken KW - Wastewater manegement KW - Transformation risks KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201022-42731 UR - https://content.sciendo.com/view/journals/rara/78/4/article-p397.xml VL - 2020 IS - Band 78, Heft 4 SP - 397 EP - 411 PB - Sciendo ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Kumari, Vandana A1 - Jadhav, Kirti A1 - Raj Das, Rohan A1 - Rasulzade, Shahla A1 - Lahmer, Tom T1 - A Machine Learning Framework for Assessing Seismic Hazard Safety of Reinforced Concrete Buildings JF - Applied Sciences N2 - Although averting a seismic disturbance and its physical, social, and economic disruption is practically impossible, using the advancements in computational science and numerical modeling shall equip humanity to predict its severity, understand the outcomes, and equip for post-disaster management. Many buildings exist amidst the developed metropolitan areas, which are senile and still in service. These buildings were also designed before establishing national seismic codes or without the introduction of construction regulations. In that case, risk reduction is significant for developing alternatives and designing suitable models to enhance the existing structure’s performance. Such models will be able to classify risks and casualties related to possible earthquakes through emergency preparation. Thus, it is crucial to recognize structures that are susceptible to earthquake vibrations and need to be prioritized for retrofitting. However, each building’s behavior under seismic actions cannot be studied through performing structural analysis, as it might be unrealistic because of the rigorous computations, long period, and substantial expenditure. Therefore, it calls for a simple, reliable, and accurate process known as Rapid Visual Screening (RVS), which serves as a primary screening platform, including an optimum number of seismic parameters and predetermined performance damage conditions for structures. In this study, the damage classification technique was studied, and the efficacy of the Machine Learning (ML) method in damage prediction via a Support Vector Machine (SVM) model was explored. The ML model is trained and tested separately on damage data from four different earthquakes, namely Ecuador, Haiti, Nepal, and South Korea. Each dataset consists of varying numbers of input data and eight performance modifiers. Based on the study and the results, the ML model using SVM classifies the given input data into the belonging classes and accomplishes the performance on hazard safety evaluation of buildings. KW - Erdbeben KW - Vulnerability KW - Earthquake KW - damaged buildings KW - earthquake safety assessment KW - soft computing techniques KW - rapid visual screening KW - Machine Learning KW - vulnerability assessment KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201022-42744 UR - https://www.mdpi.com/2076-3417/10/20/7153 VL - 2020 IS - Volume 10, issue 20, article 7153 PB - MDPI CY - Basel ER - TY - JOUR A1 - Alsaad, Hayder A1 - Völker, Conrad T1 - Der Kühlungseffekt der personalisierten Lüftung T1 - The cooling effect of personalized ventilation systems JF - Bauphysik N2 - Personalisierte Lüftung (PL) kann die thermische Behaglichkeit sowie die Qualität der eingeatmeten Atemluft verbessern, in dem jedem Arbeitsplatz Frischluft separat zugeführt wird. In diesem Beitrag wird die Wirkung der PL auf die thermische Behaglichkeit der Nutzer unter sommerlichen Randbedingungen untersucht. Hierfür wurden zwei Ansätze zur Bewertung des Kühlungseffekts der PL untersucht: basierend auf (1) der äquivalenten Temperatur und (2) dem thermischen Empfinden. Grundlage der Auswertung sind in einer Klimakammer gemessene sowie numerisch simulierte Daten. Vor der Durchführung der Simulationen wurde das numerische Modell zunächst anhand der gemessenen Daten validiert. Die Ergebnisse zeigen, dass der Ansatz basierend auf dem thermischen Empfinden zur Evaluierung des Kühlungseffekts der PL sinnvoller sein kann, da bei diesem die komplexen physiologischen Faktoren besser berücksichtigt werden. N2 - Personalized ventilation (PV) can improve thermal comfort and inhaled air quality by supplying air to each workstation separately. This study investigates the impact of PV on the thermal state of the users under summer boundary conditions. Two approaches to evaluating the cooling effect of PV were investigated, based on equivalent temperature and based on thermal sensation. Both approaches implemented measured and simulated values of the cooling effect of PV. Before conducting the simulations, the numerical model was first validated against measured data collected in a climate chamber equipped with a thermal manikin. Results indicated that the thermal sensation approach can be more suitable for evaluating the cooling effect of PV due to the complex physiological factors it considers. KW - Lüftung KW - Strömung KW - Raumklima KW - Temperatur KW - personalized ventilation KW - computational fluid dynamics KW - Simulation KW - personalisierte Lüftung KW - äquivalente Temperatur KW - thermisches Empfinden Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201020-42723 UR - https://onlinelibrary.wiley.com/doi/abs/10.1002/bapi.202000018 N1 - © 2020 Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH & Co. KG, Berlin. Dieser Artikel kann für den persönlichen Gebrauch heruntergeladen werden. Andere Verwendungen bedürfen der vorherigen Zustimmung der Autoren und des Verlags Ernst & Sohn. Der folgende Artikel erschien in der Bauphysik 42 (2020), Heft 5, 218-225, DOI: 10.1002/bapi.202000018 VL - 2020 IS - volume 42, issue 5 SP - 218 EP - 225 PB - Ernst & Sohn bei John Wiley & Sons CY - Hoboken ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Lahmer, Tom A1 - Rasulzade, Shahla T1 - Earthquake Hazard Safety Assessment of Existing Buildings Using Optimized Multi-Layer Perceptron Neural Network JF - Energies N2 - The latest earthquakes have proven that several existing buildings, particularly in developing countries, are not secured from damages of earthquake. A variety of statistical and machine-learning approaches have been proposed to identify vulnerable buildings for the prioritization of retrofitting. The present work aims to investigate earthquake susceptibility through the combination of six building performance variables that can be used to obtain an optimal prediction of the damage state of reinforced concrete buildings using artificial neural network (ANN). In this regard, a multi-layer perceptron network is trained and optimized using a database of 484 damaged buildings from the Düzce earthquake in Turkey. The results demonstrate the feasibility and effectiveness of the selected ANN approach to classify concrete structural damage that can be used as a preliminary assessment technique to identify vulnerable buildings in disaster risk-management programs. KW - Erdbeben KW - Maschinelles Lernen KW - earthquake damage KW - seismic vulnerability KW - artificial neural network KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200504-41575 UR - https://www.mdpi.com/1996-1073/13/8/2060/htm VL - 2020 IS - Volume 13, Issue 8, 2060 PB - MDPI CY - Basel ER - TY - JOUR A1 - Häfner, Lukas T1 - Common Ground. Kommentar zu Lisa Vollmer und Boris Michel „Wohnen in der Klimakrise. Die Wohnungsfrage als ökologische Frage“ BT - Kommentar zu Lisa Vollmer und Boris Michel „Wohnen in der Klimakrise. Die Wohnungsfrage als ökologische Frage“ JF - sub\urban. zeitschrift für kritische stadtforschung N2 - Die im Jahr 2020 in Deutschland praktizierte Siedlungs- und Wohnungspolitik erhält in Anbetracht ihrer Auswirkungen auf die soziale und ökologische Lage einen bitteren Beigeschmack. Arm und Reich triften weiter auseinander und einer zielgerichteten ökologischen Transformation der Art und Weise, wie Stadtentwicklung und Wohnungspolitik gestaltet werden,stehen noch immer historisch und systemisch bedingte Pfadabhängigkeiten im Weg. Diese werden nur durch eine integrierte Betrachtung sozialer und ökonomischer Aspekte sichtbar und deuten auf eine der ursprünglichen Fragen linker Gesellschaftsforschung hin: Die Auseinandersetzung mit dem Verhältnis von Eigentum und Gerechtigkeit. Im Ergebnis stehen drei wesentliche Befunde: Der Diskurs zum Schutz des Klimas und der Biodiversität berührt direkt die Parameter Dichte, Nutzungsmischung und Flächeninanspruchnahme; zweitens steigt letztere relativ mit erhöhtem, individuell verfügbaren Kapital und insbesondere im selbstgenutztem Eigentum gegenüber Mietwohnungen; und drittens wächst der Eigentumsanteil mit fortschreitender Finanzialisierung des Wohnungsmarktes, sodass das Risiko sozialer und ökologischer Krisen sich verschärft. N2 - The settlement and housing policy practised in Germany in 2020 is given a bitter taste in view of its impact on the social and ecological situation. Poor and rich are drifting further apart and a targeted ecological transformation of the way in which urban development and housing policy is designed is still hindered by historical and systemic path dependencies. These only become visible through an integrated consideration of social and economic aspects and point to one of the original questions of left-wing social research: The examination of the relationship between property and justice. As a result, there are three main findings: The discourse on climate protection and biodiversity directly touches on the parameters of density, mix of uses and land consumption; secondly, the latter increases relatively with heightened, individually available capital and especially in owner-occupied property as compared to rented housing; and thirdly, the share of ownership increases with the progressive financialisation of the housing market, so that the risk of social and ecological crises becomes more acute. KW - Umweltgerechtigkeit KW - Umweltbelastung KW - Flächenverbrauch KW - Wohnraum KW - Wohnungseigentum KW - Responsibilisierung KW - Mieten KW - Selbstgenutztes Wohneigentum KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200507-41655 UR - https://zeitschrift-suburban.de/sys/index.php/suburban/issue/view/43/30 VL - 2020 IS - Band 8, Heft 1/2 SP - 177 EP - 182 PB - Sub\urban e.V. CY - Leipzig ER - TY - JOUR A1 - Sadeghzadeh, Milad A1 - Maddah, Heydar A1 - Ahmadi, Mohammad Hossein A1 - Khadang, Amirhosein A1 - Ghazvini, Mahyar A1 - Mosavi, Amir Hosein A1 - Nabipour, Narjes T1 - Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network JF - Nanomaterials N2 - In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Text KW - Wärmeleitfähigkeit KW - Fluid KW - Neuronales Netz KW - Thermal conductivity KW - Nanofluid KW - Artificial neural network Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200421-41308 UR - https://www.mdpi.com/2079-4991/10/4/697 VL - 2020 IS - Volume 10, Issue 4, 697 PB - MDPI CY - Basel ER - TY - JOUR A1 - Alsaad, Hayder A1 - Völker, Conrad T1 - Performance evaluation of ductless personalized ventilation in comparison with desk fans using numerical simulations JF - Indoor Air N2 - The performance of ductless personalized ventilation (DPV) was compared to the performance of a typical desk fan since they are both stand-alone systems that allow the users to personalize their indoor environment. The two systems were evaluated using a validated computational fluid dynamics (CFD) model of an office room occupied by two users. To investigate the impact of DPV and the fan on the inhaled air quality, two types of contamination sources were modelled in the domain: an active source and a passive source. Additionally, the influence of the compared systems on thermal comfort was assessed using the coupling of CFD with the comfort model developed by the University of California, Berkeley (UCB model). Results indicated that DPV performed generally better than the desk fan. It provided better thermal comfort and showed a superior performance in removing the exhaled contaminants. However, the desk fan performed better in removing the contaminants emitted from a passive source near the floor level. This indicates that the performance of DPV and desk fans depends highly on the location of the contamination source. Moreover, the simulations showed that both systems increased the spread of exhaled contamination when used by the source occupant. KW - Behaglichkeit KW - Raumklima KW - Strömungsmechanik KW - Fluid KW - computational fluid dynamics KW - desk fan KW - ductless personalized ventilation KW - IAQ KW - thermal comfort Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200422-41407 UR - https://onlinelibrary.wiley.com/doi/full/10.1111/ina.12672 VL - 2020 PB - John Wiley & Sons Ltd ER - TY - JOUR A1 - Saadatfar, Hamid A1 - Khosravi, Samiyeh A1 - Hassannataj Joloudari, Javad A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin T1 - A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning JF - Mathematics N2 - The K-nearest neighbors (KNN) machine learning algorithm is a well-known non-parametric classification method. However, like other traditional data mining methods, applying it on big data comes with computational challenges. Indeed, KNN determines the class of a new sample based on the class of its nearest neighbors; however, identifying the neighbors in a large amount of data imposes a large computational cost so that it is no longer applicable by a single computing machine. One of the proposed techniques to make classification methods applicable on large datasets is pruning. LC-KNN is an improved KNN method which first clusters the data into some smaller partitions using the K-means clustering method; and then applies the KNN for each new sample on the partition which its center is the nearest one. However, because the clusters have different shapes and densities, selection of the appropriate cluster is a challenge. In this paper, an approach has been proposed to improve the pruning phase of the LC-KNN method by taking into account these factors. The proposed approach helps to choose a more appropriate cluster of data for looking for the neighbors, thus, increasing the classification accuracy. The performance of the proposed approach is evaluated on different real datasets. The experimental results show the effectiveness of the proposed approach and its higher classification accuracy and lower time cost in comparison to other recent relevant methods. KW - Maschinelles Lernen KW - Machine learning KW - K-nearest neighbors KW - KNN KW - classifier KW - big data KW - clustering KW - cluster shape KW - cluster density KW - classification KW - reinforcement learning KW - data science KW - computation KW - artificial intelligence KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200225-40996 UR - https://www.mdpi.com/2227-7390/8/2/286 VL - 2020 IS - volume 8, issue 2, article 286 PB - MDPI ER - TY - JOUR A1 - Ahmadi, Mohammad Hossein A1 - Baghban, Alireza A1 - Sadeghzadeh, Milad A1 - Zamen, Mohammad A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin A1 - Kumar, Ravinder A1 - Mohammadi-Khanaposhtani, Mohammad T1 - Evaluation of electrical efficiency of photovoltaic thermal solar collector JF - Engineering Applications of Computational Fluid Mechanics N2 - In this study, machine learning methods of artificial neural networks (ANNs), least squares support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction models for thermal performance of a photovoltaic-thermal solar collector (PV/T). In the proposed models, the inlet temperature, flow rate, heat, solar radiation, and the sun heat have been considered as the input variables. Data set has been extracted through experimental measurements from a novel solar collector system. Different analyses are performed to examine the credibility of the introduced models and evaluate their performances. The proposed LSSVM model outperformed the ANFIS and ANNs models. LSSVM model is reported suitable when the laboratory measurements are costly and time-consuming, or achieving such values requires sophisticated interpretations. KW - Fotovoltaik KW - Erneuerbare Energien KW - Solar KW - Deep learning KW - Machine learning KW - Renewable energy KW - neural networks (NNs) KW - adaptive neuro-fuzzy inference system (ANFIS) KW - least square support vector machine (LSSVM) KW - photovoltaic-thermal (PV/T) KW - hybrid machine learning model KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200304-41049 UR - https://www.tandfonline.com/doi/full/10.1080/19942060.2020.1734094 VL - 2020 IS - volume 14, issue 1 SP - 545 EP - 565 PB - Taylor & Francis ER - TY - JOUR A1 - Shamshirband, Shahaboddin A1 - Babanezhad, Meisam A1 - Mosavi, Amir A1 - Nabipour, Narjes A1 - Hajnal, Eva A1 - Nadai, Laszlo A1 - Chau, Kwok-Wing T1 - Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants JF - Engineering Applications of Computational Fluid Mechanics N2 - A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR. KW - Maschinelles Lernen KW - Machine learning KW - Bubble column reactor KW - ant colony optimization algorithm (ACO) KW - flow pattern KW - computational fluid dynamics (CFD) KW - big data KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200227-41013 UR - https://www.tandfonline.com/doi/full/10.1080/19942060.2020.1715842 VL - 2020 IS - volume 14, issue 1 SP - 367 EP - 378 PB - Taylor & Francis ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Jadhav, Kirti A1 - Mohammad, Kifaytullah A1 - Aghakouchaki Hosseini, Seyed Ehsan A1 - Lahmer, Tom T1 - A Comparative Study of MCDM Methods Integrated with Rapid Visual Seismic Vulnerability Assessment of Existing RC Structures JF - Applied Sciences N2 - Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared. KW - Erdbebensicherheit KW - damaged buildings KW - earthquake safety assessment KW - soft computing techniques KW - rapid visual screening KW - seismic risk estimation KW - Multi-criteria decision making KW - vulnerability assessment KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200918-42360 UR - https://www.mdpi.com/2076-3417/10/18/6411/htm VL - 2020 IS - Volume 10, issue 18, article 6411 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin A1 - Esmaeilbeiki, Fatemeh A1 - Zarehaghi, Davoud A1 - Neyshabouri, Mohammadreza A1 - Samadianfard, Saeed A1 - Ghorbani, Mohammad Ali A1 - Nabipour, Narjes A1 - Chau, Kwok-Wing T1 - Comparative analysis of hybrid models of firefly optimization algorithm with support vector machines and multilayer perceptron for predicting soil temperature at different depths JF - Engineering Applications of Computational Fluid Mechanics N2 - This research aims to model soil temperature (ST) using machine learning models of multilayer perceptron (MLP) algorithm and support vector machine (SVM) in hybrid form with the Firefly optimization algorithm, i.e. MLP-FFA and SVM-FFA. In the current study, measured ST and meteorological parameters of Tabriz and Ahar weather stations in a period of 2013–2015 are used for training and testing of the studied models with one and two days as a delay. To ascertain conclusive results for validation of the proposed hybrid models, the error metrics are benchmarked in an independent testing period. Moreover, Taylor diagrams utilized for that purpose. Obtained results showed that, in a case of one day delay, except in predicting ST at 5 cm below the soil surface (ST5cm) at Tabriz station, MLP-FFA produced superior results compared with MLP, SVM, and SVM-FFA models. However, for two days delay, MLP-FFA indicated increased accuracy in predicting ST5cm and ST 20cm of Tabriz station and ST10cm of Ahar station in comparison with SVM-FFA. Additionally, for all of the prescribed models, the performance of the MLP-FFA and SVM-FFA hybrid models in the testing phase was found to be meaningfully superior to the classical MLP and SVM models. KW - Bodentemperatur KW - Algorithmus KW - Maschinelles Lernen KW - Neuronales Netz KW - firefly optimization algorithm KW - soil temperature KW - artificial neural networks KW - hybrid machine learning KW - OA-Publikationsfonds2019 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200911-42347 UR - https://www.tandfonline.com/doi/full/10.1080/19942060.2020.1788644 VL - 2020 IS - Volume 14, Issue 1 SP - 939 EP - 953 ER - TY - JOUR A1 - Amirinasab, Mehdi A1 - Shamshirband, Shahaboddin A1 - Chronopoulos, Anthony Theodore A1 - Mosavi, Amir A1 - Nabipour, Narjes T1 - Energy‐Efficient Method for Wireless Sensor Networks Low‐Power Radio Operation in Internet of Things JF - electronics N2 - The radio operation in wireless sensor networks (WSN) in Internet of Things (IoT)applications is the most common source for power consumption. Consequently, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. Among essential factors affecting radio operation, the time spent for checking the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in radio duty cycles and ContikiMAC. ContikiMAC is a low‐power radio duty‐cycle protocol in Contiki OS used in WakeUp mode, as a clear channel assessment (CCA) for checking radio status periodically. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Furthermore, we propose a lightweight CCA (LW‐CCA) as an extension to ContikiMAC to reduce the Radio Duty‐Cycles in false WakeUps and idle listening though using dynamic received signal strength indicator (RSSI) status check time. The simulation results in the Cooja simulator show that LW‐CCA reduces about 8% energy consumption in nodes while maintaining up to 99% of the packet delivery rate (PDR). KW - Internet der Dinge KW - Internet of things KW - wireless sensor networks KW - ContikiMAC KW - energy efficiency KW - duty-cycles KW - clear channel assessments KW - fog computing KW - smart sensors KW - signal processing KW - received signal strength indicator KW - OA-Publikationsfonds2020 KW - RSSI Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40954 UR - https://www.mdpi.com/2079-9292/9/2/320 VL - 2020 IS - volume 9, issue 2, 320 PB - MDPI ER -