BIM-based description of wastewater treatment plants

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to describing wastewater treatment plants, enabling BIM-based collaborative ... Open BIM, by contrast, is based on non-proprietary, neutral file ... treated water and sludge, the substance remaining from biological ..... https://www.bmvi.de/SharedDocs/DE/Anlage/Digitales/strategiepapier-masterplan-bauen.pdf?blob=publ.
BIM-based description of wastewater treatment plants Heinrich Söbke1, Michael Theiler2, Eike Tauscher3 and Kay Smarsly4 1) Post-doctoral researcher, Chair of Computing in Civil Engineering, Bauhaus University Weimar, Germany. Email: [email protected] 2) Ph.D. Candidate, Chair of Computing in Civil Engineering, Bauhaus University Weimar, Germany. Email: [email protected] 3) Lecturer, Chair of Computing in Civil Engineering, Bauhaus University Weimar, Germany. Email: [email protected] 4) Professor, Chair of Computing in Civil Engineering, Bauhaus University Weimar, Germany. Email: [email protected]

Abstract Building information modeling (BIM) advances the efficiency of planning, construction, and operation of buildings. A prerequisite for life cycle use of building information is a standardized data format. The Industry Foundation Classes (IFC), a standard approved by the International Organization for Standardization (ISO), are a data format proposed to describe building information models and to provide interoperability between BIM software packages. Although the IFC enable digital descriptions of information relevant to large parts of the construction industry (such as buildings and infrastructure), wastewater treatment plants are not sufficiently supported by the IFC. This paper presents a semantic data model for describing wastewater treatment plants and provides a conceptual framework for implementing the semantic data model into the IFC schema. The semantic data model, which has been developed following German standards for wastewater infrastructure, focuses on specific classes and attributes necessary for planning wastewater treatment plants. The semantic data model proposed in this study serves as a basis for domain-specific extensions of the IFC schema with entities relevant to describing wastewater treatment plants, enabling BIM-based collaborative planning and reliable information exchange of wastewater treatment plants. Keywords: Building information modeling (BIM), Industry Foundation Classes (IFC), information modeling, metamodeling, semantic modeling, wastewater treatment plants 1. INTRODUCTION A wastewater treatment plant (WWTP) is a complex engineering structure, whose planning and operation take into account multiple material processes related to fluid mechanics, microbiology, and chemistry. Therefore, planning and operation of wastewater treatment plants requires close collaboration of engineers of several disciplines. Effective and reliable information management, including acquisition, storage and digital exchange of information, is imperative for successful planning and operation. Building information modeling (BIM) is a methodology established as an integrated information management tool in the construction industry for storing and exchanging information throughout the life cycles of buildings (Azhar, 2011; Krischler, 2017). BIM becomes increasingly important because of the digitization of building processes. In many countries, BIM has become a recommended methodology to address the increasing complexity of information management. For example, by 2020 the German Federal Ministry of Transport and Digital Infrastructure requires BIM as a mandatory methodology for all publicly funded infrastructure projects (BMVI, 2015, 2017). Building information modeling can be categorized into closed BIM and open BIM. Closed BIM is characterized by a BIM environment, in which the same software of a BIM application (and sometimes the same version of the software) is used by all participants. An example of closed BIM in the field of wastewater treatment is the expansion of the Liverpool wastewater treatment plant (Bezant, 2017). When planning the Liverpool wastewater treatment plant, about 400 digital models across all disciplines involved in the planning process have been coupled based on the same software. A so-called “BIM station”, supporting the collaboration, has enabled planners to navigate through the models. Open BIM, by contrast, is based on non-proprietary, neutral file formats, i.e., on standardized BIM data formats that facilitate information exchange independent from specific BIM tools and applications. Thus, any BIM software package capable of managing information according to standardized BIM data formats may be used as a basis for open BIM projects. Currently, the only standardized BIM data format are the Industry Foundation Classes (IFC). The IFC are widely recognized as a standard approved by the International Organization for Standardization (ISO), by the German Institute for Standardization (DIN), and by the European Committee for Standardization (DIN, 2017). The IFC standard provides a general data schema, the IFC schema, which enables information exchange between proprietary software applications.

Since its introduction, the IFC have been extended in several directions, for example towards describing information about heating systems and electric equipment (Degen and Liebich, 2007), information relevant to the life cycle of buildings (Valande et al., 2008), or parametric information about bridge models (Ji et al., 2013; Kuloyants, 2014). Another major research topic is the integration of sensor data and information about sensors into the IFC. For example, data warehouse technology-supported analyses of IFC-integrated sensor data have been a subject of research (Hoerster & Menzel, 2015; Mo et al, 2013). Similarly, the integration of data from radio frequency identification (RFID) devices into the IFC has been investigated by Motamedi et al. (2016). Furthermore, the integration of information about sensor systems of cyber-physical systems has been proposed (Legatiuk et al., 2017; Smarsly et al. 2017), and the IFC-based description of information related to structural health monitoring has also been reported (Theiler et al., 2017; Theiler and Smarsly, 2018). Further research initiatives have been focusing on the description of civil infrastructure through the IFC (Amann and Borrmann, 2016). Although the IFC have been established in many disciplines for describing buildings and infrastructure, the description of wastewater treatment plants with the IFC has received little attention. Planning and operation of wastewater treatment plants is not fully supported by open BIM concepts when using the current IFC schema as a basis. An IFC schema capable of describing information relevant to planning and operation of wastewater treatment plants (“WWTP-related information”) will support the collaborative efforts of the various disciplines involved in all phases of the life cycle of wastewater treatment plants. This paper presents a semantic data model for describing wastewater treatment plants. Exemplarily, in this paper the presentation of the semantic data model is inclined towards dimensioning wastewater treatment plants, a specific activity of planning wastewater treatment plants. More specifically, dimensioning a specific WWTP component, the secondary settlement tank, serves as an illustrative example. Finally, the semantic data model builds a foundation for an IFC schema extension towards IFC-compliant description of WWTP-related information. The paper is organized as follows. The next section describes the development of the semantic data model, with particular focus emphasized on the WWTP-related information to be described by the semantic data model. Then, the conceptual framework for implementing the semantic data model into the IFC schema (IFC schema extension) is presented. Finally, the conceptual framework and potential future work are discussed, followed by a summary of the study presented herein. 2. A SEMANTIC DATA MODEL FOR WASTEWATER TREATMENT PLANTS This section presents the semantic data model for describing wastewater treatment plants. First, the scope of the semantic data model is defined. Then, the knowledge sources serving as a basis for the semantic data model are discussed. Finally, the semantic data model is illuminated focusing on dimensioning a secondary settlement tank (also known as clarifier). Dimensioning wastewater treatment plants aims, e.g., at calculating basin sizes and pump performances. Dimensioning is performed along the WWTP components that are represented in a so-called “flowchart”, a schematic description of the wastewater flow through the WWTP components, from the inlet to the outlet. The secondary settlement tank is the basin located almost at the end of the flowchart, in which treated water and sludge, the substance remaining from biological purification processes, are separated from each other. The sludge settles on the floor of the basin, and the treated water passes the overflow of the basin. Directly located before the secondary settlement tank, the aeration tank (also known as activated sludge tank) is required for the biological purification processes, i.e. dimensioning of the secondary settlement must be coordinated with dimensioning of the aeration tank. 2.1 Knowledge sources for semantic modeling of wastewater treatment plants The quality of the semantic data model primarily depends on the reliability of the knowledge sources used to define the semantic data model. In the following paragraphs, the knowledge sources used for defining the semantic data model are discussed. Standardized data formats are candidates for reliable knowledge sources, because standardized data formats, representing formal results of standardization processes, include semantic information. Standardized data formats for water infrastructure are summarized by Ackermann & Bock (2017). Most data formats, however, do not describe data of wastewater treatment plants. For example, the ISYBAU data format (BMUB, 2013), designed for exchanging data between participants of construction projects, focuses on sewer systems rather than on wastewater treatment plants. In summary, there are no standardized data formats available that can be reused for defining the semantic data model of wastewater treatment plants. Further knowledge sources are standards for wastewater infrastructure. The German Association for Water, Wastewater and Waste (DWA) is responsible for wastewater infrastructure in Germany and provides standards commonly for planning, construction, and maintenance of wastewater infrastructure. One standard relevant to define the semantic data model is entitled “A 131” (DWA, 2016). The A 131 standard describes “Dimensioning of Single-Stage Activated Sludge Plants” (DWA, 2000). Further, the A 131 standard refers to the specifications

of the A 198 standard (ATV-DVWK, 2003a, 2003b). Thus, the A 131 standard and the A 198 standard are used as knowledge sources in this study to define the semantic data model. In addition to these standards, further scientific resources are used as knowledge sources, such as the German standard DIN 4261 (DIN, 2010) and the A 222 standard proposed by DWA (DWA, 2011). Besides data formats and standards, educational resources are considered as knowledge sources for the semantic data model (Water and the Environment, 2006). 2.2 Semantic data model for describing wastewater treatment plants Focusing on dimensioning secondary settlement tanks, this subsection showcases the semantic data model for wastewater treatment plants. In the semantic data model, all information is described, which is needed to determine the size of WWTP structures and technical capacities of the equipment. Using object-oriented analysis (Booch et al., 2007), classes and attributes are identified from the knowledge sources. Figure 1 shows the main classes of the semantic data model as a UML class diagram with two generalized classes. The class Structure includes all buildings of wastewater treatment plants, and the class TechnicalEquipment is the super class for all technical installations of wastewater treatment plants, such as pumps and mixers.

Figure 1. Class diagram of the semantic data model for wastewater treatment plants Besides classes for wastewater treatment plants, parameters for dimensioning wastewater treatment plants are included in the semantic data model. The parameters are represented in terms of attributes of the corresponding classes. As mentioned earlier, due to the interrelation of secondary settlement tanks and aeration tanks, dimensioning of both tanks is done concurrently, i.e. iteratively, until termination conditions are met. With respect to dimensioning secondary settlement tanks, Figure 2 exemplarily shows the attributes of the class SecondarySettlementTank, which is a subclass of the class Basin. The class Basin, super class of different types of tanks, is a subclass of the class Structure. The attributes of Basin and Structure (populationEquivalent, combinedWaterInflow, dryWeatherInflow, volume and surface) describe parameters for dimensioning wastewater treatment plants, through inheritance usable by Secondary SettlementTank.

Figure 2. Arrangement of the SecondarySettlementTank class in the semantic data model The attributes most relevant to dimensioning secondary settlement tanks include parameters that   

define planning specifications (e.g., population Equivalent and combinedWaterInflow determine the technical capacity for a WWTP), describe design decisions (e.g., geometry is a derived attribute, which describes the basic shape and thus the flow characteristics of tanks), and provide calculation guidelines (e.g., sludgeVolumeIndex describes the sludge consistence).

For clarity, some attributes are mirrored from other classes. For example, operationModeDenitrification refers to a technical feature of the aeration tank, also (indirectly) required for dimensioning secondary settlement tanks. Table 1 summarizes the attributes of the class SecondarySettlementTank. 3. A CONCEPTUAL FRAMEWORK FOR IFC SCHEMA EXTENSION To describe wastewater treatment plants using the IFC standard, an IFC schema extension is proposed that adds information related to dimensioning wastewater treatment plants to the IFC schema. It should be noted that, as an alternative to extending the IFC schema, generic mapping mechanisms, such as proxy elements, object type definitions and user-defined property sets, can be used to describe wastewater treatment plants (Smarsly et al., 2017). Figure 3 shows a BIM visualization of the attributes of the class SecondarySettlement Tank defined through user-defined property sets. However, using generic mapping mechanisms may cause a loss of semantic information (Theiler et al., 2017). Therefore, an IFC schema extension (instead of generic mapping mechanisms) is pursued in this study to describe wastewater treatment plants. When extending the IFC schema with WWTP-relevant information, some wastewater treatment plant classes of the semantic data model can be implemented through IFC entities that already exist in the current IFC schema (e.g., IfcPump, IfcBuildingElement, and IfcFooting). For other wastewater treatment plant classes, new entities must be defined.

Table 1. Attributes of the class SecondarySettlementTank Values/Unit Description flow (String) Vertical/ The type of throughflow (vertical/horizontal) Horizontal influences the geometry of secondary settlement tanks. geometry (String) Round/ The basic shape of the secondary settlement tank Rectangular impacts dimensioning, as it determines the flow characteristics. thickeningTime (double) h The time required for thickening of sludge until the sludge consistency necessary for subsequent processing is reached. sludgeVolumeDilution l/m³ Product of sludge volume index and total solids of Method (double) sludge. totalSolidsReturnSludge kg/m³ Total solids of return sludge. Attribute (Data type)

(double) totalSolidsInlet (double) totalSolidsFloorSludge (double) returnSludgeFlow (double)

kg/m³

Total solids of inlet stream.

kg/m³

Total solids of floor sludge.

m³/h

Quantity of return sludge stream returned from secondary settlement tanks to the aeration tanks. Key figure for sedimentation behavior of activated sludge. The area loading is the quotient of the tank inflow and the surface area of the tank. The surface feed is the quotient of storm water inflow and permissible area loading rate. Determines if the aeration tank upstream features a denitrification stage, which affects dimensioning of secondary settlement tanks indirectly. The operation mode of denitrification (aeration tank upstream) affects dimensioning of secondary settlement tank indirectly.

sludgeVolumeIndex (double)

l/kg

surfaceLoadingRate (double)

m/h

sludgeVolumeSurface LoadingRate (double)

l/(m2 h)

denitrification (boolean)

Yes/No

operationMode Denitrification (String)

E.g., pre-anoxic zone, step-feed, or simultaneous denitrification process

4. DISCUSSION AND POTENTIAL FUTURE WORK The standards of DWA, serving as main knowledge sources for creating the semantic data model (and the IFC schema extension) refer to the specifics of German wastewater infrastructure, but the semantics inherent to the DWA standards are applicable to wastewater treatment plants independent from the country. Nevertheless, further knowledge sources will be considered to broaden the basis for the semantic data model, such as the standard DIN SPEC 91400 (Schiller et al., 2017), the international quasi standard of Metcalf & Eddy Inc. (2014), and the Xanadu data format (data exchange format for the wastewater industry) (Schütze et al., 2004). Also, software packages are considered as knowledge sources, such as the software packages design2treat (ISA, 2017) and Activated Sludge Expert (Fröse, 2012), representing quasi standards for dimensioning wastewater treatment plants. For further expanding the semantic data model, besides using additional knowledge sources, experts from the technical domain will be involved. As for the conceptual framework for the IFC schema extension, further considerations are of interest regarding the implementation of sematic data models into the IFC schema. Since the semantic data model has been developed for describing all WWTP components along the WWTP flowchart, the IFC concept of port nesting, allowing modeling of substance flows through connected model elements, seem appropriate to be considered for IFC-based descriptions of WWTP components. Moreover, because the semantic data model describes wastewater treatment plants partially, the concept of model view definitions (MVD) may be applied for IFC-based descriptions of WWTP components, e.g., materialized in a WWTP flowchart-based MVD for dimensioning wastewater treatment plants.

The IFC schema is a rigid structure, given that changes to the IFC schema require a standardization process. Although the water industry is regarded technologically mature, technical changes are still common. For example, in the technical community it is discussed to add a further component to wastewater treatment plants, the so-called “fourth purification stage”, to eliminate micro pollutants, such as residues of pharmaceuticals and personal care products. These technical changes must be mapped to the underlying data formats, entailing further extensions of the IFC schema.

Figure 3. Visualization of a secondary settlement tank model using user-defined property sets (APSTEX, 2017) 5. SUMMARY AND CONCLUSIONS The description of wastewater treatment plants using standardized BIM data formats is restricted to basic building information, such as geometry and material, but it does not support BIM-based collaborative planning and reliable information exchange. This paper has proposed a semantic data model for describing wastewater treatment plants and a conceptual framework for implementing the semantic data model into the IFC schema. For illustration, the semantic data model is focused on WWTP dimensioning of secondary settlement tanks, and it has been developed using reliable knowledge sources, such as German standards A 131 und A 198 for dimensioning wastewater treatment plants. The conceptual framework proposed for implementing the semantic data model into the IFC schema includes new IFC entities, such as scraper installations. It can be concluded that the proposed semantic data model and the conceptual framework proposed for implementing the semantic data model into the IFC schema advances BIM-based collaborative planning and reliable information exchange of wastewater treatment plants. ACKNOWLEDGMENTS The authors would like to acknowledge the financial support of the German Federal Ministry of Education and Research (BMBF) through grant FKZ 01IS17007C. This work has also been partially supported by the German Research Foundation (DFG) under grant SM 281/7-1, which is gratefully acknowledged. Finally, the authors would like to thank Dr. Martin Armbruster and Dr. André Spindler of hydrograv GmbH (Dresden, Germany), whose valuable advice and suggestions are also gratefully appreciated. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of institutions mentioned above.

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