Resilience-oriented design for complex MEP systems in BIM

Normal operation of a Mechanical, Electrical, and Plumbing (MEP) system under random and intentional attacks is important to a building. A systematic research framework is proposed to analyze the resilience of an MEP system and optimize its design. The resilience magnitude in this research measures the ability of the MEP system to keep standard operation when component failures appear. First, the MEP model in Building Information Modelling (BIM) environment is extracted to a graph database by using Revit API, which represents the complex network of an MEP system. Second, the importance of the components and the resilience of the MEP system is analyzed based on the network theory and topological metrics. Third, the failure simulation is carried out by attacking the node of the system randomly and intentionally. Finally, the genetic algorithm is used to optimize the design of the MEP system by adding new edges. The results show that: (i) the graph database is a good representation of the MEP system, and it can convert the 3D model to a format that can be analyzed by data analysis measures, (ii) the same component in the MEP system could have different importance from different perspectives, (iii) the proposed network is more resilient with bridge ratio index and average path length improved by 6.16% and 40.58%, respectively, and (iv) the proposed intentional attack strategy is more conform to reality, and it can cause more severe results to a system. The research can contribute to the implementation of the resilience design theory in the MEP discipline, and create a bond between the 3D model and data analysis.     

基于知识管理的 BIM 模型建筑设计合规性自动检查系统研究

建筑设计合规性自动检查对保证建筑信息模型(BIM)符合设计规范要求,增加规范 检查自动化程度具有重要意义。结合合规性检查理论与专家系统方法,提出了以BIM 模型为检 查对象的合规性自动检查系统框架,以规则知识与推理机制分开的方式实现合规性检查过程。 以《住宅设计规范》为例,对规范中的条文进行知识分析,总结出规范知识表达式,构建规则 库和规则库访问机制;建立了逻辑策略下推理机制,将规则库中的规则信息与BIM 信息进行推 理,输出检查结果;最后构建了合规性检查系统验证平台,通过BIM 模型实例完成模型数据提 取及规则推理的过程,实现了合规性检查的功能,验证了合规性检查方法框架。该方法在一定 程度上能够指导后续的合规性检查相关研究,有效提高BIM 模型的建筑设计合规性检查效率, 保证检查质量,促进建筑工程领域信息化的发展。     

基于BIM模型的结构设计审查方法研究

建筑信息模型(BIM)作为建筑工程的数字化表达,正在成为实现建筑全生命期信息化、工业化和智能化的重要手段.以BIM模型作为设计交付成果是未来建筑设计领域发展趋势.然而,现阶段建筑结构设计的审查工作还是以人工手动审查为主,普遍存在主观、效率偏低且易出差错等问题.因此,以框架结构模型审查为实例,通过关系数据库方法解析BIM...     

BIM 支持的施工安全规范合规检查研究综述

 结合 BIM 的自动化安全规范检查可以提高安全管理效率,预防安全事故的出现, 减少安全事故的发生。目前,我国的建筑安全事故频发的现象仍未得到有效改善,建筑安全事 故严重危害了人民的人身和财产安全。近年来,安全管理的研究热度不断增高,但目前国内还 未有总结 BIM 支持安全检查的综述类文章。为此调研了近 10 年的相关文献,从相关技术和应 用层面对国内外 BIM 支持的安全检查的研究和平台进行了综述,重点归纳了规则翻译、模型准 备、执行检查和结果呈现的相关技术,并总结了安全规范检查的平台和应用领域。讨论了目前 安全检查过程中存在的问题,提出相应的解决办法,为安全检查进一步自动化的研究提供思路。     

Abstract Graph Transformation

Graphs may be used as representations of system states in operational semantics and model checking; in the latter context, they are being investigated as an alternative to bit vectors. The corresponding transitions are obtained as derivations from graph production rules.In this paper we propose an abstraction technique in this framework: the state graphs are contracted by collecting nodes that are sufficiently similar (resulting in smaller states and a finite state space) and the application of the graph production rules is lifted to this abstract level. Since graph abstractions and rule applications can all be computed completely automatically, we believe that this can be the core of a practically feasible technique for software model checking.     

Graph Transformation in Relational Databases

We present a novel approach to implement a graph transformation engine based on standard relational database management systems (RDBMSs). The essence of the approach is to create database views for each rules and to handle pattern matching by inner join operations while negative application conditions by left outer join operations. Furthermore, the model manipulation prescribed by the application of a graph transformation rule is also implemented using elementary data manipulation statements (such as insert, delete, update).     

Automated BIM data validation integrating open-standard schema with visual programming language

A building design must comply with a wide spectrum of requirements stipulated by building codes, normative standards, owner’s specifications, industry’s guidelines, and project requirements. The current rule-based compliance checking practice is a costly bottleneck in a building project, and thus, there is a demand for a design evaluation process that incorporates automated checking capabilities to address the inefficiency and the error-prone nature of the current manual checking practice. The inherent complexity of building design rules and impracticability of existing automated checking approaches are two key challenges that must be addressed to enable practical compliance checking automation. This research study proposes a new modularized framework that integrates the emerging open standard, LegalRuleML, with a Visual Programming Language. The framework allows a standardized method of defining design rules in a machine-readable and executable format. The proposed approach encompasses the entire compliance checking process from the interpretation of natural language-based requirements to machine-readable rules, rule categorization, rule parameterization, and the execution of the rules on the ISO-standard building information model. This modularized BIM-based design validation framework is expected to help automatically and iteratively evaluate the level of quality and defects of information conveyed in a given building model as an essential part of the early design process.     

A novel Data-Driven framework based on BIM and knowledge graph for automatic model auditing and Quantity Take-off

Model auditing is a critical step before conducting Building Information Modeling (BIM)-based Quantity Take-off (QTO) because these models may contain various human errors and mistakes, leading to insufficient semantic information and inconsistent modeling style in BIM models. The traditional object-oriented approach has difficulties in representing unstructured BIM data (e.g., interrelationships), while rule-based methods involve tremendous human efforts to develop rule sets, lacking flexibility for different requirements. Therefore, this study aims to establish a novel data-driven framework based on BIM and knowledge graph (KG) to represent unstructured BIM data for automatic inferences of auditing results of BIM model mistakes. It starts by establishing a BIM-KG data model via identifying required information for auditing purposes. Subsequently, BIM data is automatically transformed into the BIM-KG representations, the embeddings of which are trained using a knowledge graph embedding model. Automatic mechanisms are then developed to utilize the computable embeddings to effectively identify mistake BIM elements. The framework is validated using illustrative examples and the results show that 100% mistake elements can be identified successfully without human intervention.     

GSO:基于图神经网络的深度学习计算图子图替换优化框架

深度学习在各种实际应用中取得了巨大成功,如何有效提高各种复杂的深度学习模型在硬件设备上的执行效率是该领域重要的研究内容之一.深度学习框架通常将深度学习模型表达为由基础算子构成的计算图,为了提高计算图的执行效率,传统的深度学习系统通常基于一些专家设计的子图替换规则,采用启发式搜索算法来优化计算图.它们的不足主要有:1)搜...     

基于元模型的Simulink静态分析技术

为解决目前Simulink模型规则检查工具对国内如飞行控制等一些特定领域的标准规范覆盖不完善的问题,设计了41条建模准则,并基于元模型理论,提出了一种共性的解析和检查框架,在此基础上实现了Simulink模型规则检查工具SimREG。该方法通过一种无编译的方式来实现对Simulink模型的静态规则检查,在Simulink模型到元模型的映射过程中提取针对每条准则执行检查时需要的模型信息,并将模型重构为有向图的形式,然后在遍历过程中,对图中每个节点进行选定准则的分析处理,完成检查过程。SimREG完成了全部41条建模准则的检查过程,在与三个有代表性的规则检查工具的对比实验中取得了更好的检查结果。SimREG工具将元模型理论应用于Simulink模型的规则检查过程中,在检查速度更快的同时获得了更低的漏报率和误报率。     

基于 BIM 和本体的建筑不规则类型审查

建筑不规则类型审查是建筑抗震审查的重要组成部分,对建筑抗震安全有重要意义。为提高审查 效率和准确性,提出一套基于建筑信息模型(BIM)和本体的建筑不规则类型审查方法。首先解析梳理建筑不规则 类型审查规范条文,然后将规范条文转译成计算机可识别的语义审查规则,并根据审查逻辑构建建筑不规则类型 审查本体;其次从待审查建筑的 BIM 文件中抽取审查信息,如楼层开洞面积,基于模板匹配算法从结构计算书 自动抽取审查所需计算结果参数,如扭转位移比;接着基于建筑不规则类型审查本体组织审查信息,利用审查规 则推理获得审查结果,进而生成审查报告。最后以某建筑为例验证了该方法的可行性和较强地扩展能力,为进一 步实现建筑抗震审查的自动化奠定了技术基础。     

A graph grammars based framework for querying graph-like data

The widespread use of graph-based models for representing data collections (e.g. object-oriented data, XML data, etc.) has stimulated the database research community to investigate the problem of defining declarative languages for querying graph-like databases. In this paper, a new framework for querying graph-like data based on graph grammars is proposed. The new paradigm allows us to verify structural properties of graphs and to extract sub-graphs. More specifically, a new form of query (namely graph query) is proposed, consisting in a particular graph grammar which defines a class of graphs to be matched on the graph representing the database. Thus, differently from path queries, the answer of a graph query is not just a set of nodes, but a subgraph, extracted from the input graph, which satisfies the structural properties defined by the graph grammar. Expressiveness and complexity of different forms of graph queries are discussed, and some practical applications are shown.     

Clash context representation and change component prediction based on graph convolutional network in MEP disciplines

Clash management, including clash detection and resolution, is critical for construction project success. While clash detection has been automatically conducted by Building Information Modeling (BIM) tools, the clash resolution process is still being conducted manually. This process includes predicting clash change components and determining change methods. Previous studies predict clash change components based on single clash features while ignoring the interdependency between building components and clashes. This paper proposes to use a graph convolutional network (GCN) to improve clash change component prediction by considering the interdependency nature of building components. Instead of assuming each clash is independent, the GCN model uses a component dependency graph as the input to determine whether to make changes to a particular component based on both 1) its features and 2) its impacts on related components, which is transferred through the spatial dependency structure. To further decide what kind of spatial dependency is more informative for clash change component prediction, this study compares different dependency settings. We experiment on the BIM model of a real-world project and then use the Kruskal-Wallis test to compare model accuracy in different settings. The result shows that integrating dependency information into consideration can significantly improve model prediction accuracy, and the clash relation is the most critical factor for clash change component prediction.     

A meta-heuristic solution for automated refutation of complex software systems specified through graph transformations

One of the best approaches for verifying software systems (especially safety critical systems) is the model checking in which all reachable states are generated from an initial state. All of these states are searched for errors or desirable patterns. However, the drawback for many real and complex systems is the state space explosion in which model checking cannot generate all the possible states. In this situation, designers can use refutation to check refusing a property rather than proving it. In refutation, it is very important to handle the state space for finding errors efficiently. In this paper, we propose an efficient solution to implement refutation in complex systems modeled by graph transformation. Since meta-heuristic algorithms are efficient solutions for searching in the problems with very large state spaces, we use them to find errors (e.g., deadlocks) in systems which cannot be verified through existing model checking approaches due to the state space explosion. To do so, we employ a Particle Swarm Optimization (PSO) algorithm to consider only a subset of states (called population) in each step of the algorithm. To increase the accuracy, we propose a hybrid algorithm using PSO and Gravitational Search Algorithm (GSA). The proposed approach is implemented in GROOVE, a toolset for designing and model checking graph transformation systems. The experiments show improved results in terms of accuracy, speed and memory usage in comparison with other existing approaches.     

基于图割理论和极几何约束的图像匹配算法

提出了一种基于图割理论和极几何约束的图像匹配算法。利用极几何约束对两幅待匹配图像进行矫正,使得它们的极线处在同一扫描线上,从而将二维匹配简化成一维匹配;利用基于图割的一维匹配算法获取视差数据,此时匹配中能量函数的标号是一维的,大大减少了搜索范围,并且提高了匹配的速度。     

Multiple path exploration for graph matching

The graph matching problem is a hot topic in machine vision. Although a myriad of matching algorithms have been proposed during decades of investigation, it is still a challenging issue because of the combinatorial nature. As one of the outstanding graph matching algorithms, the graduated nonconvexity and concavity procedure follows the path following algorithm. The main drawback of this approach lies that there may exist singular points which violate the smoothness of the solution path and thus harm the accuracy of matching. Addressing this problem, we develop a novel algorithm to bypass this pitfall to improve the matching accuracy. We design an effective method of singular point discovering by checking the smoothness of the path and subsequently explore multiple smooth curves at detected points for better matching results. For evaluation, we make comparisons between our approach and several outstanding matching algorithms on three popular benchmarks, and the results reveal the advantage of our approach.     

Optimizing the Cray Graph Engine for performant analytics on cluster,SuperDome Flex,Shasta systems and cloud deployment

We present updates to the Cray Graph Engine, a high performance in-memory semantic graph database, which enable performant execution across multiple architectures as well as deployment in a container to support cloud and as-a-service graph analytics. This paper discusses the changes required to port and optimize CGE to target multiple architectures, including Cray Shasta systems, large shared-memory machines such as SuperDome Flex (SDF), and cluster environments such as Apollo systems. The porting effort focused primarily on removing dependences on XPMEM and Cray PGAS and replacing these with a simplified PGAS library based upon POSIX shared memory and one-sided MPI, while preserving the existing Coarray-C++ CGE code base. We also discuss the containerization of CGE using Singularity and the techniques required to enable container performance matching native execution. We present early benchmarking results for running CGE on the SDF, Infiniband clusters and Slingshot interconnect-based Shasta systems.     

Fast parallel algorithms for graph similarity and matching

This paper addresses the problem of global graph alignment on supercomputer-class clusters. We define the alignment of two graphs, as a mapping of each vertex in the first graph to a unique vertex in the second graph so as to optimize a given similarity-based cost function.¹ Using a state of the art serial algorithm for the computation of vertex similarity scores called Network Similarity Decomposition (NSD), we derive corresponding parallel formulations. Coupling this parallel similarity algorithm with a parallel auction-based bipartite matching technique, we obtain a highly efficient and scalable graph matching pipeline. We validate the performance of our integrated approach on a large parallel platform and on diverse graph instances (including Protein Interaction, Wikipedia and Web networks). Experimental results demonstrate that our algorithms scale to large machine configurations (thousands of cores) and problem instances, enabling the alignment of networks of sizes two orders of magnitude larger than reported in the current literature.     

Using Markov Chain Based Estimation of Distribution Algorithm for Model-Based Safety Analysis of Graph Transformation

The ability to assess the reliability of safety-critical systems is one of the most crucial requirements in the design of modern safety-critical systems where even a minor failure can result in loss of life or irreparable damage to the environment. Model checking is an automatic technique that verifies or refutes system properties by exploring all reachable states (state space) of a model. In large and complex systems, it is probable that the state space explosion problem occurs. In exploring the state space of systems modeled by graph transformations, the rule applied on the current state specifies the rule that can perform on the next state. In other words, the allowed rule on the current state depends only on the applied rule on the previous state, not the ones on earlier states. This fact motivates us to use a Markov chain (MC) to capture this type of dependencies and applies the Estimation of Distribution Algorithm (EDA) to improve the quality of the MC. EDA is an evolutionary algorithm directing the search for the optimal solution by learning and sampling probabilistic models through the best individuals of a population at each generation. To show the effectiveness of the proposed approach, we implement it in GROOVE, an open source toolset for designing and model checking graph transformation systems. Experimental results confirm that the proposed approach has a high speed and accuracy in comparison with the existing meta-heuristic and evolutionary techniques in safety analysis of systems specified formally through graph transformations.     

Implementing a Graph Transformation Engine in Relational Databases

We present a novel approach to implement a graph transformation engine based on standard relational database management systems (RDBMSs). The essence of the approach is to create database views for each rule and to handle pattern matching by inner join operations while handling negative application conditions by left outer join operations. Furthermore, the model manipulation prescribed by the application of a graph transformation rule is also implemented using elementary data manipulation statements (such as insert, delete). As a result, we obtain a robust and fast transformation engine especially suitable for (1) extending modeling tools with an underlying RDBMS repository and (2) embedding model transformations into large distributed applications where models are frequently persisted in a relational database and transaction handling is required to handle large models consistently.