Ich habe an insgesamt 19 wissenschaftlichen Artikeln mitgewirkt und diese auf zahlreichen Konferenzen im In- und Ausland präsentiert. Alle meine Publikationen an denen ich als Erstautor, sowie Ko-Autor beteiligt war, sind nachfolgend chronologisch aufgelistet.
Model-based planning requires an extensive amount of information about the environment, inventory and requirements of the planned object. Thereby, temporal information is important to be considered for planning, construction and maintenance, but in current approaches temporal information is only defined through non-semantic datasets, which lack contextual meaning. To semantify time-data used in BIM projects, the authors propose the concept of combining existing models using ICDD and adding an Ontology for Chronological Construction Processes (OCCP) to record and implement structured temporal information of the entire life cycle and use it from the start of planning until deconstruction and even beyond.
Despite new technologies in machine vision allow for an automated damage detection, current practices in damage assessment rely mainly on manual evaluations by human experts. Although some new approaches propose a damage assessment via machine learning methods, essential contextual information about the damaged construction is not considered. Contrary to this, knowledge-based approaches have been researched. However, knowledge bases for damage assessment usually contain certain knowledge gaps that result in uncertainties, which still need to be solved manually by experts. Therefore, in this paper a new theoretical approach that utilizes case-based reasoning (CBR) is discussed as additional method for automated damage assessment, which could be utilized in conjunction with knowledge-based approaches. Thereby, the case base of the CBR system would be developed as ontology utilizing the Web Ontology Language (OWL) in order to be compatible with current knowledge-based approaches, especially the Damage Topology Ontology (DOT)
During the inspection and assessment of existing buildings, a large portion of the recorded data is stored in documents or models that are not computer interpretable. Managing this data digitally is a complex process because the evaluation of the building components and the affecting structural damages involves a significant amount of manual tasks that can be error-prone and time consuming. Therefore, a knowledge-based approach has been developed, which utilizes web ontologies to store building and damage information in a semantic representation and processes them in an automated assessment via predefined rulesets. The concept is specified and applied for structures made of natural stone and is specifically tested and verified on the common case of a damaged façade. A newly developed software platform is presented, which provides functions for managing and evaluating a damage ontology as well as linking damage information with a geometry-based BIM model by utilizing an Information Container for linked Document Delivery (ICDD) according to ISO 21597-1 and adapting a general-purpose BIMification approach for retrofitting.
Within the scope of non-destructive inspections, it frequently happens that damages within the construction structure or at inaccessible areas are not detected. Thus, human experts must assume these damages by evaluating relevant information about the construction and its surroundings, which could become a time consuming and error prone task. For this reason, a new approach is presented in this paper, in which a knowledge system has been developed utilizing Semantic Web Technologies to automatically infer new infor mation about potential undetected damage areas. Thereby, ontological models for defining information about the affected construction and the already inspected damages are used as data input and reasoned by applying predefined rules formalized in Description Logic. Furthermore, the possibility for occurrence of each assumed damage is determined by utilizing fuzzy set theory.
In the recent years, approaches that utilize Semantic Web Technologies for describing building information enabled the development of semantic representations of constructions and with it the separation of semantic and geometry-based models. Currently developed web ontologies provide functionality for defining a detailed topology, in which direct connections between various components are semantically described. However, a great proportion of tasks that require at least approximate information about the localization of objects in relation to connected components cannot be processed. This is especially a problem in the field of damage inspections, in which this information is mandatory for subsequent damage classification and assessment. To solve this problem, a newly developed ontological approach is presented in this paper, which aims for the semantic description of component areas, called Areas of Interest (AOI). Thereby, a new auxiliary ontology has been conceptualized, which aims for an uncomplicated integration in existing AEC-related ontologies. The paper presents the overall methodology of AOI as well as the corresponding conceptual ontology and the exemplary application for damage assessment utilizing the Damage Topology Ontology (DOT).
During the life-cycle of constructions various influences induce material defects that could affect the behavior of the structural system. Therefore, anomalies that affect heavily stressed constructions, such as bridges, need to be inspected and evaluated regarding their impact on the structural capacity. By using new technologies in the field of damage detection, e.g. laser scanners or unmanned aircraft systems (UAS), this process can be facilitated. However, the classification and assessment of detected anomalies must still be performed in a manual way by human experts due to the lack of machine-processable evaluation methods. In this paper an approach is proposed towards a machine-based damage evaluation, applying semantic web technologies on a new developed method for damage detection on constructions. Thereby, anomalies are detected based on a large amount of high-resolution images from which georeferenced point clouds are calculated by using photogrammetric methods. Using the geometric relations among the image positions and reconstructed points, image features such as anomalies are localized on a 3 dimensional surface. Based on these image features, a web ontology as semantic representation of the recorded damages is generated and linked with an ontology that contains information about the affected construction and its environment. By using predefined rules based on expert knowledge, the detected anomalies are classified and assessed automatically. The inferred information is then used to generate damage representations in a structural analysis model. Furthermore, the geometrical data, which are represented in a model created according to Building Information Modeling (BIM) standards, the semantic data as well as the structural data are linked by utilizing the Multimodel approach.
Nowadays building works, especially of historic buildings with facades out of natural stone, require continuous maintenance, repair and retrofit works. In order to fulfil the needs for a completely digitized natural stone retrofit process, works are to be projected, planned, conducted and cleared with instrumentation of Building Information Modeling (BIM). Due to this need, a novel knowledge-based stone damage identification system focused on natural stone damage on the basis of BIM is developed, which will present implicitly existing knowledge and information from the building survey explicitly and objectively by using semantic data structures. BIM-SIS is an adaptive damage identification system for natural stone, which allows to virtually merge different natural stone damages, recorded by different information systems and with different procedures, into a holistic damage model. This model is used to assess the damages integrative and in detail, supported by knowledge-based methods, and to develop a uniform and cost-stable remediation strategy. Therefore, the BIM-SIS methodology consists of BIMification for information processes, Ontologies for knowledge representation and Multimodels for data interoperability. The so formed continuous interoperable digital construction representation consists of separate but interlinked domain models. This model structure is then extended for remediation execution management and allows to simply incorporate subsequently detected defects during execution. The complete damage profile is the basis for all further retrofit-creation and calculation processes in BIM-SIS which will automatically lead to user customed retrofit variants presented in VR and AR.
Modern as well as historic buildings with façades out of natural stone material require maintenance, repair und retrofit works after several decades. Nowadays such building works are to be projected, planned, conducted and cleared with instrumentation of Building Information Modeling (BIM). A novel, knowledge-based stone damage identification system focused on natural stone damage due to the natural aging process is developed. In process consists of three stages (1) identifying damage types, (2) merging them into damage systems and (3) breaking them down to stone dimensions and joints, completing the damage profile. New BIM processes are develop to facilitate individual steps of damage phenomena und damage cause identification. This is achived by a continuous interoperable digital construction representation consisting of separate but interlinked domain models. This will be continued for remediation execution management and augmented with a dynamic multi-model methodology so that defects detected later during execution can simply be incorporated without problem. BIM-SIS (Schadens Identifikations System) is an adaptive knowledge based information system for identification of stone damages for the rehabilitation of stone building components with feedback on bidding and change management embedded in BIM processes.
Currently, utilizing digital representations of bridge constructions is still limited to geometry-based models with none or only little semantic data. Consequently, assessing these models requires the interpretation of external sources, e.g. relational databases or reports. Despite new approaches in the Building Information Modeling (BIM) domain such as the IFC-Bridge extension for the Industry Foundation Classes (IFC) try to provide models where geometric and semantic data are combined, a great proportion of information from current and future domains that are relevant for the bridge industry are not covered. For this reason, an extensible web ontology inspired from the Building Topology On-tology (BOT) for buildings has been developed, which functions as a core ontol-ogy for bridge representations and therefore covers all necessary general information used in this domain. The developed core ontology is interlinked with multiple domain specific bridge extensions in a bridge ontology framework that is applied on a test scenario. In this paper, the components of the bridge ontology framework are explained as well as the application on the test case. In addition, ontology alignments for BOT and ifcOWL are proposed as well as shapes for ontology validation. Furthermore, the functionality of a developed software prototype is described that generates the bridge ontology from a given IFC model.
To assess detected anomalies as well as assume undetected damages of an existing construction, a knowledge-based approach for damage evaluation is presented, whereby data from multiple web ontologies are linked via Linksets that are stored in an Information Container for Data Delivery (ICDD). In the ICDD, an ontological model that represents the assessed construction is linked with a damage ontology, which is necessary to identify various damage types that could affect the construction. Additionally, the web ontology representing the construction is linked with a Building Information Model (BIM) in the IFC-Format to enable access to the geometrical data of the components. Similarly, the damage objects are linked with either recorded geometry data or a manually created geometry model. Predefined rules are applied on the assertion components of the web ontology for reasoning damage types of each detected anomaly and damage assessment. Furthermore, the existence of undetected damages can be reasoned based on information about the construction, environment and previously classified damages. The developed web ontologies in this research use the principles of Linked Data and are serialized in the data format OWL. This enables the utilization of already existing Linked Data ontologies as well as supporting the implementation and development of future ones.
Die Erstellung von Repräsentationen eines Bauwerks beschränkt sich im Brückenbau derzeit noch auf semantikarme Modelle. Unter anderem ist die auf die fehlende Software-Unterstützung eines offiziellen Building Information Modeling (BIM)-Standards für Brücken zurückzuführen. Eine Lösungsmöglichkeit hierfür wäre die Verwendung von Linked Data Technologien, die die Erstellung einer einheitlichen Datenrepräsentation sowohl in menschen-, als auch in maschinenlesbarer Form ermöglichen. Momentan beschränkt sich die Entwicklung von Linked Data Anwendungen im Bauwesen hauptsächlich auf den Hochbau und eine umfassende Struktur zur Repräsentation einer Brückenkonstruktion wurde noch nicht erarbeitet. In diesem Paper wird ein erstes Konzept zur Modellierung von Brücken in unter Verwendung der W3C standardisierten Ontology Web Language (OWL) vorgestellt. Dabei liegt der Fokus auf einer semantischen Anreicherung von IFC-Brückenmodellen unter Verwendung einer OWL-Ontologie die mittels Multimodell-Ansatz verlinkt wird. Hierbei wurden terminologische Komponenten (TBox) für Brücken in Spannbeton- und Verbundbauweise erstellt. Zu Testzwecken wurden ebenfalls assertionale Komponenten (ABox) basierend auf der TBox erstellt sowie mit einem IFC-Modell verlinkt. Es wurden Abfragen unter Verwendung der standardisierten SPARQL Protocol And RDF Query Language (SPARQL) definiert und auf die Ontologie angewendet um diese auf Konsistenz und Anwendbarkeit zu überprüfen.
Zur Realisierung eines digitalisierten Planungsprozesses für den Rückbau von Kernkraftwerken wird ein Konzept zur Anwendung eines cyberphysikalischen Systems vorgestellt. Dieses nutzt die RFID-Technologie zur Identifikation und Ortung der einzelnen abgebauten Elemente. Die benötigten Informationen werden innerhalb des Systems zentral über ein 3D-Modell verwaltet, das unter Verwendung des Building Information Modeling (BIM) neben der Gebäudegeometrie auch noch weitere semantische Daten beinhaltet. Zu beachten ist, dass in gegenwärtiger BIM-Software eine beliebige Zerstückelung der Bauteilrepräsentationen zu einem Semantikverlust führt. Um diesen zu umgehen, werden für die Tragwerksnachweise der Reststruktur zunächst vollständige Bauteile virtuell entfernt. Anschließend erfolgt die Zuordnung der mit RFID-Tags versehenen Bauteile zu ihren im Modell demontierten Repräsentationen. Unter Verwendung des Multimodell-Ansatzes werden während des gesamten Abbauprozesses die einzelnen Datenelemente unterschiedlicher Modelle miteinander verlinkt, wodurch eine computergestützte Verarbeitung und Interpretation in einer heterogenen Datenumgebung unterstützt wird. Eine Aktualisierung zuletzt passierter RFID-Gates für jedes Bauteil wird ebenfalls unterstützt. Durch eine gezielte Abfrage im Multimodell ist die Ausgabe der für die Materialflussplanung benötigten Informationen möglich.
A large proportion of the data created during the inspection and assessment of stone facades and their damages is recorded in formats that are not machine-readable and thus cannot be further processed or managed digitally. Consequently, this increases the risk of data loss and incorrect information due to human misinterpretation. Therefore, a Multimodel-based approach has been developed in which stone facades of existing buildings are digitized as IFC-model by using proxy entities and linked with web ontologies for semantic enrichment. Additionally, detected anomalies in the stone structure are implemented and linked with geometrical representations. By utilizing additional rules and inference mechanisms, the anomalies can be classified, and a knowledge-based damage assessment is processed.
The Damage Topology Ontology (DOT) is presented, a web ontology that provides terminology to represent construction-related damages and their topology as well as relations to affected construction elements and spatial zones. Besides the topology, classes and properties for documentation management and a minimal structural assessment have been proposed in DOT. In this regard , DOT provides all classes and properties needed for practical use in construction inspections and damage assessment. The ontology is developed to be used with the modular Linked Building Data ontologies structure, where DOT works as core damage ontology which can be extended with multiple modules related to detailed damage classification, damage assessment, mechanical degradation and other application scenarios. Geometrical damage representations are separated from the topology, so that it is possible to initially record damages during the inspection without any geometrical properties and link it later with a corresponding representation using terminology from geometry-related ontologies. In conclusion , DOT can be applied as a stand-alone web ontology to represent damages in a machine-interpretable format and replace conventional record approaches. Therefore, a generic terminology is used that enables the inclusion of various types of damage, which can be extended with domain-specific information.
Over the last decade, the possibilities of detecting structural damage have significantly increased, due to new techniques like identifying material cracks through scanners, drones or other advanced measuring instruments. Nevertheless, the methods of storing the measured data are still limited to graphical representations of the damage or datasets which have no context to the building. Due to this, the damage of structures must be evaluated and categorized manually by experts. The possibilities of a computer-aided analysis, in which tools for filtering or reasoning could be executed are restricted because of a missing data model for structural damage. Therefore, a model to digitalize structural damage is developed and discussed in this article. The data of the structure is stored in a BIM model which uses a standardized data format, the Industry Foundation Classes (IFC) and by using a multi model approach, both models are connected.
Zur Integrierung von BIM in der Tragwerksplanung und-analyse für Brücken wurde ein Konzept entwickelt, das aus den Entwurfsdaten eines IFC-Modells ein statisches System generiert. Hierbei werden die Proxy-Klassen eines zuvor erstellten Brückenmodells mittels Annotation semantisch angereichert, wodurch statisch relevante Entitäten identifiziert werden können. Es wurde ein Software-Prototyp entwickelt, der die Annotationen verwertet und Alignment -Objekte zur Repräsentation der Trasse, sowie ein Tragwerksystem generiert. Zur Analyse von geschädigten Brücken können Daten aus einem separaten Schadensmodell hinzugefügt werden. Ebenso werden weitere Parameter, die sich nicht aus IFC herleiten lassen, manuell in das Modell integriert, wie z B. Lastdaten oder mechanische Querschnittswerte.
Although, catalogues and collections exist which contain knowledge about damage and common patterns that could enable the application of software assessment methods, recorded damage data must still be evaluated by experts. For this reason, an approach is developed and discussed in this article that allows the semi-automatic conclusion of damage causations by the input of inspection data and vice versa. Therefore, an ontology is created by using the Web Ontology Language (OWL) which is structured in the three knowledge domains for damage-, structure-, and causational elements, so that unidentified information could be retrieved by using semantic reasoning. Furthermore, the damage is structured in reference damage patterns which allow computer-aided modelling of damage based on predefined conditions or parameters. Additionally, retrieved data can be mapped to a generic damage model, which can be linked with external data sources such as measurement datasets as well as BIM models.
The Structural Health Monitoring of bridge structures is becoming increasingly important. Due to new developments in the field of sensor and data processing technology, a new method will be introduced, which enables prognosis of the bridge lifespan through system identification based on the monitoring process. Therefore, the damages of the bridge, which are modelled in an appropriate damage model, will be linked with its BIM Model. The damage data will then be variated by using a separate Variation Model. Using this method results in the automatized creation of numerous input models for mass simulation. This forms the basis for a multi‐stage procedure, which identifies the structural bridge state by using the simulation results for a numerical best‐fit method. Thereby engineers can utilize the evaluated models to make more precise decisions and improve the Structural Health Monitoring of bridge structures.
Für eine Nutzung des Building Information Modeling (BIM) im Bereich des Monitorings und der Instandhaltung von Bauwerken, genügt es in der Regel nicht, Modelle zu verwen-den, die lediglich den ungeschädigten Bauzustand wiedergeben. Insbesondere Risse im Material verdienen hierbei besondere Beachtung, da sie maßgeblich das Tragwerkverhalten beeinflussen können. Die Definition von Rissen und anderen Bauschäden wird allerdings im standardisierten Datenformat für BIM-Modelle, den Industry Foundation Classes (IFC) nicht unterstützt. Aus diesem Grund wird eine Methode in Form eines separaten Modells entwickelt, um Risse innerhalb von BIM zu beschreiben und sie mit einem IFC-Modell zu verknüpfen.