TY - INPR A1 - Khosravi, Khabat A1 - Sheikh Khozani, Zohreh A1 - Mao, Luka T1 - A comparison between advanced hybrid machine learning algorithms and empirical equations applied to abutment scour depth prediction N2 - Complex vortex flow patterns around bridge piers, especially during floods, cause scour process that can result in the failure of foundations. Abutment scour is a complex three-dimensional phenomenon that is difficult to predict especially with traditional formulas obtained using empirical approaches such as regressions. This paper presents a test of a standalone Kstar model with five novel hybrid algorithm of bagging (BA-Kstar), dagging (DA-Kstar), random committee (RC-Kstar), random subspace (RS-Kstar), and weighted instance handler wrapper (WIHWKstar) to predict scour depth (ds) for clear water condition. The dataset consists of 99 scour depth data from flume experiments (Dey and Barbhuiya, 2005) using abutment shapes such as vertical, semicircular and 45◦ wing. Four dimensionless parameter of relative flow depth (h/l), excess abutment Froude number (Fe), relative sediment size (d50/l) and relative submergence (d50/h) were considered for the prediction of relative scour depth (ds/l). A portion of the dataset was used for the calibration (70%), and the remaining used for model validation. Pearson correlation coefficients helped deciding relevance of the input parameters combination and finally four different combinations of input parameters were used. The performance of the models was assessed visually and with quantitative metrics. Overall, the best input combination for vertical abutment shape is the combination of Fe, d50/l and h/l, while for semicircular and 45◦ wing the combination of the Fe and d50/l is the most effective input parameter combination. Our results show that incorporating Fe, d50/l and h/l lead to higher performance while involving d50/h reduced the models prediction power for vertical abutment shape and for semicircular and 45◦ wing involving h/l and d50/h lead to more error. The WIHW-Kstar provided the highest performance in scour depth prediction around vertical abutment shape while RC-Kstar model outperform of other models for scour depth prediction around semicircular and 45◦ wing. KW - maschinelles Lernen Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210311-43889 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/abs/pii/S0022169421001475?via%3Dihub ; https://doi.org/10.1016/j.jhydrol.2021.126100 ER - TY - JOUR A1 - Ibanez, Stalin A1 - Kraus, Matthias T1 - A Numerical Approach for Plastic Cross Cross-Sectional Analyses of Steel Members JF - ce/papers N2 - Global structural analyses in civil engineering are usually performed considering linear-elastic material behavior. However, for steel structures, a certain degree of plasticization depending on the member classification may be considered. Corresponding plastic analyses taking material nonlinearities into account are effectively realized using numerical methods. Frequently applied finite elements of two and three-dimensional models evaluate the plasticity at defined nodes using a yield surface, i.e. by a yield condition, hardening rule, and flow rule. Corresponding calculations are connected to a large numerical as well as time-consuming effort and they do not rely on the theoretical background of beam theory, to which the regulations of standards mainly correspond. For that reason, methods using beam elements (one-dimensional) combined with cross-sectional analyses are commonly applied for steel members in terms of plastic zones theories. In these approaches, plasticization is in general assessed by means of axial stress only. In this paper, more precise numerical representation of the combined stress states, i.e. axial and shear stresses, is presented and results of the proposed approach are validated and discussed. KW - Stahlkonstruktion KW - Plastizität KW - Strukturanalyse KW - Stahlbauteil KW - Axialspannung KW - Finite-Elemente-Methode Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220112-45622 UR - https://onlinelibrary.wiley.com/doi/full/10.1002/cepa.1527 VL - 2021 IS - Volume 4, issue 2-4 SP - 2098 EP - 2106 PB - Ernst & Sohn, a Wiley brand CY - Berlin ER - TY - THES A1 - Fauth, Judith T1 - A process-oriented decision model for determining the permitability of construction projects N2 - In recent years, the discussion of digitalization has arrived in the media, at conferences, and in committees of the construction and real estate industry. While some areas are producing innovations and some contributors can be described as pioneers, other topics still show deficits with regard to digital transformation. The building permit process can also be counted in this category. Regardless of how architects and engineers in planning offices rely on innovative methods, building documents have so far remained in paper form in too many cases, or are printed out after electronic submission to the authority. Existing resources – for example in the form of a building information model, which could provide support in the building permit process – are not being taken advantage of. In order to use digital tools to support decision-making by the building permit authorities, it is necessary to understand the current situation and to question conditions before pursuing the overall automation of internal authority processes as the sole solution. With a substantive-organizational consideration of the relevant areas that influence building permit determination, an improvement of the building permit procedure within authorities is proposed. Complex areas – such as legal situations, the use of technology, as well as the subjective alternative action – are determined and structured. With the development of a model for the determination of building permitability, both an understanding of influencing factors is conveyed and an increase in transparency for all parties involved is created. In addition to an international literature review, an empirical study served as the research method. The empirical study was conducted in the form of qualitative expert interviews in order to determine the current state in the field of building permit procedures. The collected data material was processed and subsequently subjected to a software-supported content analysis. The results were processed, in combination with findings from the literature review, in various analyses to form the basis for a proposed model. The result of the study is a decision model that closes the gap between the current processes within the building authorities and an overall automation of the building permit review process. The model offers support to examiners and applicants in determining building permit eligibility, through its process-oriented structuring of decision-relevant facts. The theoretical model could be transferred into practice in the form of a web application. KW - Baugenehmigung KW - Entscheidungsmodell KW - Bauantrag KW - Prozessmanagement KW - Projektmanagement KW - Building permit KW - Building application KW - Decision-making KW - Process management KW - Project management Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220309-46020 UR - https://e-pub.uni-weimar.de/opus4/frontdoor/index/index/docId/4509 N1 - This work is a translation of the original dissertation (German language) which is accessible at: https://doi.org/10.25643/bauhaus-universitaet.4509 and deposited here as URL link. ER - TY - JOUR A1 - Alkam, Feras A1 - Lahmer, Tom T1 - A robust method of the status monitoring of catenary poles installed along high-speed electrified train tracks JF - Results in Engineering N2 - Electric trains are considered one of the most eco-friendly and safest means of transportation. Catenary poles are used worldwide to support overhead power lines for electric trains. The performance of the catenary poles has an extensive influence on the integrity of the train systems and, consequently, the connected human services. It became a must nowadays to develop SHM systems that provide the instantaneous status of catenary poles in- service, making the decision-making processes to keep or repair the damaged poles more feasible. This study develops a data-driven, model-free approach for status monitoring of cantilever structures, focusing on pre-stressed, spun-cast ultrahigh-strength concrete catenary poles installed along high-speed train tracks. The pro-posed approach evaluates multiple damage features in an unfied damage index, which leads to straightforward interpretation and comparison of the output. Besides, it distinguishes between multiple damage scenarios of the poles, either the ones caused by material degradation of the concrete or by the cracks that can be propagated during the life span of the given structure. Moreover, using a logistic function to classify the integrity of structure avoids the expensive learning step in the existing damage detection approaches, namely, using the modern machine and deep learning methods. The findings of this study look very promising when applied to other types of cantilever structures, such as the poles that support the power transmission lines, antenna masts, chimneys, and wind turbines. KW - Fahrleitung KW - Catenary poles KW - SHM KW - Model-free status monitoring KW - Sigmoid function KW - High-speed electric train KW - Schaden KW - OA-Publikationsfonds2021 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20211011-45212 UR - https://www.sciencedirect.com/science/article/pii/S2590123021000906?via%3Dihub VL - 2021 IS - volume 12, article 100289 SP - 1 EP - 8 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Kumari, Vandana A1 - Jadhav, Kirti A1 - Rasulzade, Shahla A1 - Lahmer, Tom A1 - Raj Das, Rohan T1 - A Synthesized Study Based on Machine Learning Approaches for Rapid Classifying Earthquake Damage Grades to RC Buildings JF - Applied Sciences N2 - A vast number of existing buildings were constructed before the development and enforcement of seismic design codes, which run into the risk of being severely damaged under the action of seismic excitations. This poses not only a threat to the life of people but also affects the socio-economic stability in the affected area. Therefore, it is necessary to assess such buildings’ present vulnerability to make an educated decision regarding risk mitigation by seismic strengthening techniques such as retrofitting. However, it is economically and timely manner not feasible to inspect, repair, and augment every old building on an urban scale. As a result, a reliable rapid screening methods, namely Rapid Visual Screening (RVS), have garnered increasing interest among researchers and decision-makers alike. In this study, the effectiveness of five different Machine Learning (ML) techniques in vulnerability prediction applications have been investigated. The damage data of four different earthquakes from Ecuador, Haiti, Nepal, and South Korea, have been utilized to train and test the developed models. Eight performance modifiers have been implemented as variables with a supervised ML. The investigations on this paper illustrate that the assessed vulnerability classes by ML techniques were very close to the actual damage levels observed in the buildings. KW - Maschinelles Lernen KW - Neuronales Netz KW - Machine learning KW - Building safety assessment KW - artificial neural networks KW - supervised learning KW - damaged buildings KW - rapid classification KW - OA-Publikationsfonds2021 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210818-44853 UR - https://www.mdpi.com/2076-3417/11/16/7540 VL - 2021 IS - Volume 11, issue 16, article 7540 SP - 1 EP - 33 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schwerzmann, Katia T1 - Abolish! Against the Use of Risk Assessment Algorithms at Sentencing in the US Criminal Justice System JF - Philosophy & Technology N2 - In this article, I show why it is necessary to abolish the use of predictive algorithms in the US criminal justice system at sentencing. After presenting the functioning of these algorithms in their context of emergence, I offer three arguments to demonstrate why their abolition is imperative. First, I show that sentencing based on predictive algorithms induces a process of rewriting the temporality of the judged individual, flattening their life into a present inescapably doomed by its past. Second, I demonstrate that recursive processes, comprising predictive algorithms and the decisions based on their predictions, systematically suppress outliers and progressively transform reality to match predictions. In my third and final argument, I show that decisions made on the basis of predictive algorithms actively perform a biopolitical understanding of justice as management and modulation of risks. In such a framework, justice becomes a means to maintain a perverse social homeostasis that systematically exposes disenfranchised Black and Brown populations to risk. KW - Biopolitik KW - Soziale Gerechtigkeit KW - Algorithmus KW - predictive algorithms KW - cybernetics KW - criminal justice KW - social justice KW - biopolitics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20211207-45417 UR - https://link.springer.com/article/10.1007/s13347-021-00491-2 VL - 2021 SP - 1 EP - 22 ER - TY - JOUR A1 - Lashkar-Ara, Babak A1 - Kalantari, Niloofar A1 - Sheikh Khozani, Zohreh A1 - Mosavi, Amir T1 - Assessing Machine Learning versus a Mathematical Model to Estimate the Transverse Shear Stress Distribution in a Rectangular Channel JF - Mathematics N2 - One of the most important subjects of hydraulic engineering is the reliable estimation of the transverse distribution in the rectangular channel of bed and wall shear stresses. This study makes use of the Tsallis entropy, genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) methods to assess the shear stress distribution (SSD) in the rectangular channel. To evaluate the results of the Tsallis entropy, GP and ANFIS models, laboratory observations were used in which shear stress was measured using an optimized Preston tube. This is then used to measure the SSD in various aspect ratios in the rectangular channel. To investigate the shear stress percentage, 10 data series with a total of 112 different data for were used. The results of the sensitivity analysis show that the most influential parameter for the SSD in smooth rectangular channel is the dimensionless parameter B/H, Where the transverse coordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one. Based on the analysis, it can be concluded that the use of GP and ANFIS algorithms is more effective in estimating shear stress in smooth rectangular channels than the Tsallis entropy-based equations. KW - Maschinelles Lernen KW - smooth rectangular channel KW - Tsallis entropy KW - genetic programming KW - artificial intelligence KW - machine learning KW - big data KW - computational hydraulics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210504-44197 UR - https://www.mdpi.com/2227-7390/9/6/596 VL - 2021 IS - Volume 9, Issue 6, Article 596 PB - MDPI CY - Basel ER - TY - THES A1 - Alabassy, Mohamed Said Helmy T1 - Automated Approach for Building Information Modelling of Crack Damages via Image Segmentation and Image-based 3D Reconstruction N2 - As machine vision-based inspection methods in the field of Structural Health Monitoring (SHM) continue to advance, the need for integrating resulting inspection and maintenance data into a centralised building information model for structures notably grows. Consequently, the modelling of found damages based on those images in a streamlined automated manner becomes increasingly important, not just for saving time and money spent on updating the model to include the latest information gathered through each inspection, but also to easily visualise them, provide all stakeholders involved with a comprehensive digital representation containing all the necessary information to fully understand the structure’s current condition, keep track of any progressing deterioration, estimate the reduced load bearing capacity of the damaged element in the model or simulate the propagation of cracks to make well-informed decisions interactively and facilitate maintenance actions that optimally extend the service life of the structure. Though significant progress has been recently made in information modelling of damages, the current devised methods for the geometrical modelling approach are cumbersome and time consuming to implement in a full-scale model. For crack damages, an approach for a feasible automated image-based modelling is proposed utilising neural networks, classical computer vision and computational geometry techniques with the aim of creating valid shapes to be introduced into the information model, including related semantic properties and attributes from inspection data (e.g., width, depth, length, date, etc.). The creation of such models opens the door for further possible uses ranging from more accurate structural analysis possibilities to simulation of damage propagation in model elements, estimating deterioration rates and allows for better documentation, data sharing, and realistic visualisation of damages in a 3D model. KW - Building Information Modeling KW - BIM KW - IFC KW - Damage Information Modelling KW - Cracks Segmentation KW - Cracks 3D Modelling KW - Netscape Internet Foundation Classes Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20230818-64162 ER - TY - JFULL A1 - Dolff-Bonekämper, Gabi A1 - Paulus, Jörg A1 - Sellmann, Annika A1 - Vogel, Carolin A1 - Bargholz, Ortrun A1 - Herrmann, Moritz Peter A1 - Löffler, Beate A1 - Kretschmann, Schirin A1 - Lotter, Stefanie A1 - Ehrenpreis, David A1 - Bockelmann, Leo A1 - Langner, Sigrun A1 - Schönberger, Sonya A1 - Majdzadeh, Bahar ED - Bogner, Simone ED - Dolff-Bonekämper, Gabi ED - Meier, Hans-Rudolf T1 - Collecting Loss N2 - Wer sich mit "Identität" und "Erbe" befasst, also mit dem Zusammenhang zwischen der Konstituierung und Stabilität von Gemeinwesen und dem Bewahren von Gütern, Orten und Überlieferungen, kommt nicht umhin, sich auch mit Verlusten zu befassen. Verlust bezeichnet hier nicht die Abwesenheit eines Gutes, das Erbe war oder hätte werden können, sondern die soziale Beziehung zu dem verlorenen Gut und zu den Umständen seines Verlorengehens oder auch den Versuchen, es wiederzugewinnen. T3 - Schriftenreihe des DFG-Graduiertenkollegs 2227 "Identität und Erbe" - 1 KW - Verlust KW - Sammeln KW - Identität KW - Kulturerbe KW - Archiv Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201221-43217 PB - Bauhaus-Universitätsverlag CY - Ilmtal-Weinstraße ER - TY - THES A1 - Al Khatib, Khalid T1 - Computational Analysis of Argumentation Strategies N2 - The computational analysis of argumentation strategies is substantial for many downstream applications. It is required for nearly all kinds of text synthesis, writing assistance, and dialogue-management tools. While various tasks have been tackled in the area of computational argumentation, such as argumentation mining and quality assessment, the task of the computational analysis of argumentation strategies in texts has so far been overlooked. This thesis principally approaches the analysis of the strategies manifested in the persuasive argumentative discourses that aim for persuasion as well as in the deliberative argumentative discourses that aim for consensus. To this end, the thesis presents a novel view of argumentation strategies for the above two goals. Based on this view, new models for pragmatic and stylistic argument attributes are proposed, new methods for the identification of the modelled attributes have been developed, and a new set of strategy principles in texts according to the identified attributes is presented and explored. Overall, the thesis contributes to the theory, data, method, and evaluation aspects of the analysis of argumentation strategies. The models, methods, and principles developed and explored in this thesis can be regarded as essential for promoting the applications mentioned above, among others. KW - Argumentation KW - Natürliche Sprache KW - Argumentation Strategies KW - Sprachverarbeitung KW - Natural Language Processing KW - Computational Argumentation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210719-44612 ER -