scholarly journals Assessment of model-based data exchange between architectural design and structural analysis

2020 ◽  
Vol 32 ◽  
pp. 101589
Author(s):  
Goran Sibenik ◽  
Iva Kovacic
Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 605
Author(s):  
Goran Sibenik ◽  
Iva Kovacic ◽  
Valentinas Petrinas ◽  
Wendelin Sprenger

Building information modelling promises model-based collaboration between stakeholders in the project design stage. However, data exchange between physical and analytical building models used for architectural design and structural analysis respectively rarely takes place due to numerous differences in building element representation, especially the representation of geometry. This paper presents the realization of a novel data exchange framework between architectural design and structural analysis building models, based on open interpretations on central storage. The exchange is achieved with a new system architecture, where the program redDim was developed to perform the interpretations, including the most challenging transformations of geometry. We deliver a proof of concept for the novel framework with a prototype building model and verify it on two further building models. Results show that structural-analysis models can be correctly automatically created by reducing dimensionality and reconnecting building elements. The proposed data exchange provides a base for missing standardization of interpretations, which facilitates the non-proprietary automated conversion between physical and analytical models. This research fills the gap in the existing model-based communication that could lead to a seamless data exchange.


2021 ◽  
Vol 26 ◽  
pp. 39-57
Author(s):  
Goran Sibenik ◽  
Iva Kovacic

The heterogeneity of the architecture, engineering and construction (AEC) industry reflects on digital building models, which differ across domains and planning phases. Data exchange between architectural design and structural analysis models poses a particular challenge because of dramatically different representations of building elements. Existing software tools and standards have not been able to deal with these differences. The research on inter-domain building information modelling (BIM) frameworks does not consider the geometry interpretations for data exchange. Analysis of geometry interpretations is mostly project-specific and is seldom reflected in general data exchange frameworks. By defining a data exchange framework that engages with varying requirements and representations of architectural design and structural analysis in terms of geometry, which is open to other domains, we aim to close the identified gap. Existing classification systems in software tools and standards were reviewed in order to understand architectural design and structural analysis representations and to identify the relationships between them. Following the analysis, a novel data management framework based on classification, interpretation and automation was proposed, implemented and tested. Classification is a model specification including domain-specific terms and relationships between them. Interpretations consist of inter-domain procedures necessary to generate domain-specific models from a provided model. Automation represents the connection between open domain-specific models and proprietary models in software tools. Practical implementation with a test case demonstrated a possible realization of the proposed framework. The innovative contribution of the research is a novel framework based on the system of open domain-specific classifications and procedures for the inter-domain interpretation, which can prepare domain-specific models on central storage. The main benefit is a centrally prepared domain-specific model, relieving software developers from so-far-unsuccessful implementation of complex inter-domain interpretations in each software tool, and providing end users with control over the data exchange. Although the framework is based on the exchange between architectural design and structural analysis, the proposed central data management framework can be used for other exchange processes involving different model representations.


Author(s):  
Adarsh Venkiteswaran ◽  
Sayed Mohammad Hejazi ◽  
Deepanjan Biswas ◽  
Jami J. Shah ◽  
Joseph K. Davidson

Industries are continuously trying to improve the time to market through automation and optimization of existing product development processes. Large companies vow to save significant time and resources through seamless communication of data between design, manufacturing, supply chain and quality assurance teams. In this context, Model Based Definition/Engineering (MBD) / (MBE) has gained popularity, particularly in its effort to replace traditional engineering drawings and documentations with a unified digital product model in a multi-disciplinary environment. Widely used 3D data exchange models (STEP AP 203, 214) contains mere shape information, which does not provide much value for reuse in downstream manufacturing applications. However, the latest STEP AP 242 (ISO 10303-242) “Managed model based 3D engineering” aims to support smart manufacturing by capturing semantic Product Manufacturing Information (PMI) within the 3D model and also helping with long-term archival. As a primary, for interoperability of Geometric Dimensions & Tolerances (GD&T) through AP 242, CAx Implementor Forum has published a set of recommended practices for the implementation of a translator. In line with these recommendations, this paper discusses the implementation of an AP 203 to AP 242 translator by attaching semantic GD&T available in an in-house Constraint Tolerance Graph (CTF) file. Further, semantic GD&T data can be automatically consumed by downstream applications such as Computer Aided Process Planning (CAPP), Computer Aided Inspection (CAI), Computer Aided Tolerance Systems (CATS) and Coordinate Measuring Machines (CMM). Also, this paper will briefly touch base on the important elements that will constitute a comprehensive product data model for model-based interoperability.


Author(s):  
Alireza Pourshahid ◽  
Liam Peyton ◽  
Sepideh Ghanavati ◽  
Daniel Amyot ◽  
Pengfei Chen ◽  
...  

Validation should be done in the context of understanding how a business process is intended to contribute to the business strategies of an organization. Validation can take place along a variety of dimensions including legal compliance, financial cost, customer value, and service quality. A business process modeling tool cannot anticipate all the ways in which a business process might need to be validated. However, it can provide a framework for extending model elements to represent context for a business process. It can also support information exchange to facilitate validation with other tools and systems. This chapter demonstrates a model-based approach to validation using a hospital approval process for accessing patient data in a data warehouse. An extensible meta-model, a flexible data exchange layer, and linkage between business processes and enterprise context are shown to be the critical elements in model-based business process validation.


2020 ◽  
Vol 9 (4) ◽  
pp. 394-409
Author(s):  
Saikiran Gopalakrishnan ◽  
Nathan W. Hartman ◽  
Michael D. Sangid

AbstractThe digital transformation of manufacturing requires digitalization, including automatic and efficient data exchange. Model-based definitions (MBDs) capture digital product definitions, in order to eliminate error-prone information exchange associated with traditional paper-based drawings and to provide contextual information through additional metadata. The flow of MBDs extends throughout the product lifecycle (including the design, analysis, manufacturing, in service life, and retirement stages) and can be extended beyond the typical geometry and tolerance information within a computer-aided design. In this paper, the MBDs are extended to include materials information, via dynamic linkages. To this end, a model-based feature information network (MFIN) is created to provide a comprehensive framework that facilitates storing, updating, searching, and retrieving of relevant information across a product’s lifecycle. The use case of a damage tolerant analysis for a compressor bladed-disk (blisk) is demonstrated, in Ti-6Al-4V blade(s) linear friction welded to the Ti-6Al-4V disk, creating well-defined regions exhibiting grain refinement and high residuals stresses. By capturing the location-specific microstructure and residual stress values at the weld regions, this information is accessed within the MFIN and used for downstream damage tolerant analysis. The introduction of the MFIN framework facilitates access to dynamically evolving data for use within physics-based models (resulting in the opportunity to reduce uncertainty in subsequent prognosis analyses), thereby enabling a digital twin description of the component or system.


Author(s):  
Jonathan Byrne ◽  
Michael Fenton ◽  
Erik Hemberg ◽  
James McDermott ◽  
Michael O’Neill ◽  
...  

2016 ◽  
Vol 6 (6) ◽  
pp. 1260
Author(s):  
Liang Zhao

The acquisition of the verb past tense has often been used to help to figure out children’s real process of language acquisition. This paper aims to make a comparison between Charles Yang’s Rules and Competition Model (the RC model) and Steven Pinker’s Words and Rules Model (the WR model) based on real language acquisition data selected from CHILDES (Child Language Data Exchange System). Chomsky’s Universal grammar is the foundation of both models. The comparison has been done from three aspects: the role of input frequency, overregularization errors, and the origin of irregular past tense. The finding of the study indicates that the RC model can well explain the role of input frequency in verb classes and the similarity between verb and the past tense while the WR model’s explanation is vague in this point. Overregularization errors are more like an inevitable learning phenomenon that sheds light on phonological rules in the RC model instead of simple memory failures in the WR model. The WR model well explains the origin of irregular past tense while the RC model does not mention this point.


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