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Metamodeling and multicriteria analysis for sustainable and passive residential building refurbishment: A case study of French housing stock

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Building Simulation 2022年第3期15卷 453-472页

作者： Zaid Romani Abdeslam Draoui Francis Allard LaRAT National School of Architecture of TetouanMorocco Team of Heat Transfer&Energetic FST of Tangier(UAE/U10FST) Abdelmalek Essaâdi UniversityMorocco LaSIE La Rochelle UniversityFrance

For the energy-related issues that the world is facing nowadays,the renovation of the building stock is one of the major challenges.The objective of this study is to present an approach that helps to develop a multi-criteria decision support tool dedicated to the rehabilitation of sustainable and passive energy housing by integrating heating energy needs,economic,social and environmental criteria throughout the life cycle stages of the building.The methodology consists of developing metamodels to predict heating energy needs from polynomial regression,design of experiments method and thermo-aeraulic simulations of building behavior.This metamodel is used to carry out a combinatorial study of real technical solutions.The methodology was applied to a real-life existing building located in La Rochelle city(France)based on an in-situ energy diagnosis.Three multicriteria analysis methods were studied and compared:weighted sum,Min-Max and Pareto concept.Furthermore,technical constraints as well as owner preferences and performance constraints have been studied.Optimal technical solutions have been obtained in order to meet the various criteria studied.In addition,window shading and natural ventilation have been proposed to reduce the thermal discomfort rate in summer.This study was extended to all French regions.Finally,this method can be transformed into a decision support tool which will be useful for architects,engineers and stockholders.

关键词： Metamodeling building refurbishment multi-criteria decision support sustainable building passive building

Building Modeling Tools Based on Metamodeling and Product Line Technologies

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Chinese Journal of Electronics 2014年第2期23卷 219-226页

作者： MA Zhiyi HE Xiao Software Institute School of Electronics Engineering and Computer Science Peking University Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of Education School of Computer and Communication Engineering University of Science and Technology Beijing

With the evolution of existing modeling languages and the emergence of more and more new modeling languages, it is necessary to rapidly build the corresponding software modeling tools with good quality. However, modeling tools for larger modeling languages are usually diversity in function and complexity in implementation technology. Taking building modeling tools as a domain,this paper presents an approach to building software modeling tools based on Metamodeling and product line technologies. The paper provides the concept system of the approach and a feature model from diverse functions of modeling tools in order to specify the commonality and variability of the tools by deeply making the domain analysis,discusses the design and implementation of a general tool framework that provides the conveniences for reusing components and generating code for components, and specifies the mapping between the feature model and the components for modeling tools.

关键词： Software modeling tool Metamodeling Software product line

A Metamodeling Method Based on Support Vector Regression for Robust Optimization

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Chinese Journal of Mechanical Engineering 2010年第2期23卷 242-251页

作者： XIANG Guoqi HUANG Dagui School of Mechatronics Engineering University of Electronic Science and Technology of China Chengdu 610054 China School of Mechanical Engineering Panzhihua University Panzhihua 617000 China

Metamodeling techniques have been used in robust optimization to reduce the high computational cost of the uncertainty analysis and improve the performance of robust optimization problems with computationally expensive simulation models. Existing metamodels main focus on polynomial regression（PR）, neural networks（NN） and Kriging models, these metamodels are not well suited for large-scale robust optimization problems with small size training sets and high nonlinearity. To address the problem, a reduced approximation model technique based on support vector regression（SVR） is introduced in order to improve the accuracy of metamodels. A robust optimization method based on SVR is presented for problems that involve high dimension and nonlinear. First appropriate design parameter samples are selected by experimental design theories, then the response samples are obtained from the simulations such as finite element analysis, the SVR metamodel is constructed and treated as the mean and the variance of the objective performance functions. Combining other constraints, the robust optimization model is formed which can be solved by genetic algorithm （GA）. The applicability of the method developed is demonstrated using a case of two-bar structure system study. The performances of SVR were compared with those of PR, Kriging and back-propagation neural networks（BPNN）, the comparison results show that the prediction accuracy of the SVR metamodel was higher than those of other metamodels under uncertainty. The robust optimization solutions are near to the real result, and the proposed method is found to be accurate and efficient for robust optimization. This reaserch provides an efficient method for robust optimization problems with complex structure.

关键词： support vector regression Metamodeling robust optimization genetic algorithm

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Energy and carbon performance of urban buildings using Metamodeling variable importance techniques

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Building Simulation 2021年第3期14卷 535-547页

作者： Yunliang Liu Wei Tian Xiang Zhou School of Mechanical Engineering Tongji UniversityShanghai 200092China Tianjin Key Laboratory of Integrated Design and On-line Monitoring for Light Industry&Food Machinery and Equipment College of Mechanical EngineeringTianjin University of Science and TechnologyTianjin 300222China Tianjin International Joint Research and Development Center of Low-Carbon Green Process Equipment Tianjin 300222China

Global urbanization causes more environmental stresses in cities and energy efficiency is one of major concerns for urban sustainability.The variable importance techniques have been widely used in building energy analysis to determine key factors influencing building energy use.Most of these applications,however,use only one type of variable importance approaches.Therefore,this paper proposes a procedure of conducting two types of variable importance analysis(predictive and variance-based)to determine robust and effective energy saving measures in urban buildings.These two variable importance methods belong to Metamodeling techniques,which can significantly reduce computational cost of building energy simulation models for urban buildings.The predictive importance analysis is based on the prediction errors of metamodels to obtain importance rankings of inputs,while the variance-based variable importance can explore non-linear effects and interactions among input variables based on variance decomposition.The campus buildings are used to demonstrate the application of the method proposed to explore characteristic of heating energy,cooling energy,electricity,and carbon emissions of buildings.The results indicate that the combination of two types of Metamodeling variable importance analysis can provide fast and robust analysis to improve energy efficiency of urban buildings.The carbon emissions can be reduced approximately 30%after using a few of effective energy efficiency measures and more aggressive measures can lead to the 60%of reduction of carbon emissions.Moreover,this research demonstrates the application of parallel computing to expedite building energy analysis in urban environment since more multi-core computers become increasingly available.

关键词： urban buildings variable importance Metamodeling energy performance carbon emissions

An adaptive sequential experiment design method for model validation

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Chinese Journal of Aeronautics 2020年第6期33卷 1661-1672页

作者： Ke FANG Yuchen ZHOU Ping MA Control and Simulation Center Harbin Institute of TechnologyHarbin 150080China

Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.

关键词： Adaptive sequential experiment design Credibility distribution function Gaussian process model Metamodeling Model validation

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Model Transformation Using a Simplified Metamodel

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Journal of Software Engineering and Applications 2010年第7期3卷 653-660页

作者： Hongming Liu Xiaoping Jia College of Computing and Digital Media DePaul University

Model Driven Engineering (MDE) is a model-centric software development approach aims at improving the quality and productivity of software development processes. While some progresses in MDE have been made, there are still many challenges in realizing the full benefits of model driven engineering. These challenges include incompleteness in existing modeling notations, inadequate in tools support, and the lack of effective model transformation mechanism. This paper provides a solution to build a template-based model transformation framework using a simplified metamode called Hierarchical Relational Metamodel (HRM). This framework supports MDE while providing the benefits of readability and rigorousness of meta-model definitions and transformation definitions.

关键词： Model Driven Engineering Modeling Metamodeling Model Transformation

The Principal Component Transform of Parametrized Functions

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Applied Mathematics 2017年第4期8卷 453-475页

作者： Ilia Zabrodskii Arcady Ponosov Department of Science and Technology Norwegian University of Life Sciences &Aring s Norway

Many advanced mathematical models of biochemical, biophysical and other processes in systems biology can be described by parametrized systems of nonlinear differential equations. Due to complexity of the models, a problem of their simplification has become of great importance. In particular, rather challengeable methods of estimation of parameters in these models may require such simplifications. The paper offers a practical way of constructing approximations of nonlinearly parametrized functions by linearly parametrized ones. As the idea of such approximations goes back to Principal Component Analysis, we call the corresponding transformation Principal Component Transform. We show that this transform possesses the best individual fit property, in the sense that the corresponding approximations preserve most information (in some sense) about the original function. It is also demonstrated how one can estimate the error between the given function and its approximations. In addition, we apply the theory of tensor products of compact operators in Hilbert spaces to justify our method for the case of the products of parametrized functions. Finally, we provide several examples, which are of relevance for systems biology.

关键词： Principal Component Analysis Discretization of Functions Metamodeling Latent Parameters

Quality Requirements for Multimedia Interactive Informative Systems

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Journal of Software Engineering and Applications 2013年第8期6卷 416-425页

作者： Sylviane Levy Fernando Gamboa Centro de Ciencias Aplicadas y Desarrollo Tecnológico Universidad Nacional Autónoma de México México D.F. México Dirección General de Cómputo y de Tecnologías de Información y Comunicación Universidad Nacional Autónoma de México México D.F. México

Multimedia Interactive Informative Systems (MIIS) are software applications resulting from the convergence of multiples technologies such as audiovisual, computing and communication. They aim to transmit information to a large, diverse and dispersed public. As with other mass media, the fulfillment of MIIS goals depends largely on the quality of communication between the system and end users. Therefore, those systems should be developed in order to ensure that this quality requirement is satisfied. If MIIS are constructed according to usual software engineering practices, the analysis discipline of the development process includes requirements identification and specification;however, these techniques are focused on functional requirements, and they do not give much importance to non-functional requirements. In this paper, we propose a development process based on the production of videogames which has two different phases: preproduction and production. The first phase, corresponding to requirements identification, derives into the concept of system. In order to translate this concept into a specification, we propose the use of new communicational attributes and a MIIS metamodel. The establishment of MIIS non-functional specification is the result of analyzing class diagrams through quality attributes. In order to evaluate if the specifications are responding to communicational attributes, a functional prototype is built and evaluated with end users. The proposed methodology is applied to a real case study.

关键词： Multimedia Interactive Informative Systems Multimedia Quality Model in Use Quality Requirements Metamodeling

End to End Development Engineering

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Journal of Software Engineering and Applications 2011年第4期4卷 195-216页

作者： Abdelgaffar Hamed Robert M. Colomb College of Computer Science and Information Technology Sudan University of Science and Technology Khartoum Sudan Faculty of Computer Science and Information Systems Universiti Technologi Malaysia Skudai Malaysia

Raising software abstraction and re-use levels are key success factors for producing quality software products. Model-driven architecture (MDA) is an OMG initiative following this trend by mapping a conceptual model of application specified in platform independent model (PIM), to one or more platform specific models (PSM) automatically. Because there is little previous work tackling the development problem from specification through to implementation, this paper proposes End to End Development engineering (E2EDE) method using MDA methodology. E2EDE is intended to fill the mapping gap between PIM and PSM in MDA. The notion of variability is utilized from software product line and used to model design decisions in PSM. PIM is equipped with Nonfunctional requirements which borrowed from Design pattern to inform design decisions;thereby guiding the mapping process. In addition we have developed a strategic PSM for messaging systems can be configured to produce different applications such as the helpdesk system which is used as a case study.

关键词： End to End Engineering MDA Metamodeling Domain Engineering