Generic Metamodel Research Articles

Building energy performance metamodels for district energy management optimisation platforms

Reactive control strategies lack the flexibility necessary to optimize the operational costs of buildings and district systems. To overcome this limitation and to enable the transition to model predictive control strategies (MPC), the development of dedicated control platforms and models is required. Predictive models for district systems management should provide supply and demand side integrated modelling, high accuracy, generalization capacity and reduced computational times. However, traditionally available MPC solutions do not meet these requirements as simplified models offer short computational times but lack the required accuracy; detailed physics-based models provide satisfactory generalization but at the expense of high computational costs; and the generalization capacity of data models is constrained by the quality and availability of data. In contrast, metamodels developed through the combined use of physics-based models and machine learning techniques offer a powerful alternative at reduced computational cost. This paper describes an upgraded Integrated District Model concept developed through co-simulation coupling metamodels of buildings with a district heating infrastructure Modelica model. Furthermore, the process to produce the metamodels and optimization engine required to generate demand flexibility optimization functionalities for the buildings of the Stepa Stepanovic subnetwork (Belgrade) is depicted. Starting from the development of metamodels of instances of specific buildings (residential and educational use) the process was expanded to provide additional generalization to define, (1) a generic metamodel with the capacity to reproduce the behaviour of any instance of building of the residential typology, and (2) metamodels with generalization capacity in relation to operational settings. As part of this process the potential of several machine learning algorithms (e.g Support Vector Machines, etc) was evaluated including the latest ensemble boosting methods (e.g. Adaboost, Gradient Boosting and Extreme Gradient Boosting) with comparatively low use in the building simulation community. Finally, a virtual test bed consisting in metamodels coupled to an optimization engine based on genetic algorithms, was implemented, and compared to a traditional Physics-based model MPC solution (EnergyPlus-GENOPT), to evaluate the potential of the developed building level optimization functionalities. The metamodels and optimization engine were able to reproduce the optimized settings identified by the EnergyPlus-GENOPT MPC solution with cost savings potentials of 5–10%.

Toward Objective Assessment of Simulation Predictive Capability

Two different metrics quantifying model and simulator predictive capability are formulated and evaluated; both metrics exploit results from conducted validation experiments where simulation results are compared to the corresponding measured quantities. The first metric is inspired by the modified nearest neighbor coverage metric and the second by the Kullback–Liebler divergence. The two different metrics are implemented in Python and in a here-developed general metamodel designed to be applicable for most physics-based simulation models. These two implementations together facilitate both offline and online metric evaluation. Additionally, a connection between the two, here separated, concepts of predictive capability and credibility is established and realized in the metamodel. The two implementations are, finally, evaluated in an aeronautical domain context.

Meta-modelling the climate of dry tide-locked rocky planets

Context. Rocky planets hosted by close-in extrasolar systems are likely to be tidally locked in 1:1 spin-orbit resonance, a configuration where they exhibit a permanent dayside and nightside. Because of the resulting day-night temperature gradient, the climate and large-scale circulation of these planets are strongly determined by their atmospheric stability against collapse, which designates the runaway condensation of greenhouse gases on the nightside. Aims. To better constrain the surface conditions and climatic regime of rocky extrasolar planets located in the habitable zone of their host star, it is therefore crucial to elucidate the mechanisms that govern the day-night heat redistribution. Methods. As a first attempt to bridge the gap between multiple modelling approaches ranging from simplified analytical greenhouse models to sophisticated 3D general circulation models (GCMs), we developed a general circulation meta-model (GCMM) able to reproduce the closed-form solutions obtained in earlier studies, the numerical solutions obtained from GCM simulations, and solutions provided by intermediate models, assuming the slow rotator approximation. We used this approach to characterise the atmospheric stability of Earth-sized rocky planets with dry atmospheres containing CO2, and we benchmarked it against 3D GCM simulations using the THOR GCM. Results. We observe that the collapse pressure below which collapse occurs can vary by ~40% around the value predicted by analytical scaling laws depending on the mechanisms taken into account among radiative transfer, atmospheric dynamics, and turbulent diffusion. Particularly, we find (i) that the turbulent diffusion taking place in the dayside planetary boundary layer (PBL) globally tends to warm up the nightside surface hemisphere except in the transition zone between optically thin and optically thick regimes, (ii) that the PBL also significantly affects the day-night advection timescale, and (iii) that the slow rotator approximation holds from the moment that the normalised equatorial Rossby deformation radius is greater than 2.

A Novel Progressive Response Surface Method for High-order polynomial Metamodel

The response surface method (RSM) model as a general metamodel has already widely been applied to many practical problems. However, the majority of studies only focus on the 2nd-order terms RSM model instead of how to determine the high-order terms. This paper introduced a novel progressive response surface method (NPRSM) combining optimal Latin hypercube design (OLHD), moving least square method (MLSM) and statistical test. This NPRSM model can decide the high-order terms by progressive procedure. Then three numerical function can be proposed to validate the accuracy and the approximated performance of the NPRSM model.

Formalizing model transformation patterns

AbstractModel transformation has become an established field, and it is important to improve the quality of specifications written in transformation languages. Different transformation patterns have been introduced in the model‐driven engineering (MDE) community to improve the quality of transformation specifications. However, due to the different definitions of pattern concepts by different authors, it is difficult for practitioners to understand how to apply patterns in practice. Therefore, there is a need to unify transformation pattern concepts by presenting a generic metamodel and formalizing patterns in terms of this metamodel, to define the meaning of pattern application. In this research a general metamodel for definition of different design patterns in model transformation is provided. The metamodel presents clear description of common aspects of transformation patterns, which facilitates the application of patterns on model transformations by validating the application against the underlying formalism. Additionally, a unified and precise terminology for the application and verification of model transformation patterns by using a formal model of model transformation patterns in the Z notation is presented. To show the applicability of the proposed formalism, four well‐known model transformation patterns are specified.

Uncertainty Modelling in Metamodels for Fire Risk Analysis

In risk-related research of fire safety engineering, metamodels are often applied to approximate the results of complex fire and evacuation simulations. This approximation may cause epistemic uncertainties, and the inherent uncertainties of evacuation simulations may lead to aleatory uncertainties. However, neither the epistemic ‘metamodel uncertainty’ nor the aleatory ‘inherent uncertainty’ have been included in the results of the metamodels for fire safety engineering. For this reason, this paper presents a metamodel that includes metamodel uncertainty and inherent uncertainty in the results of a risk analysis. This metamodel is based on moving least squares; the metamodel uncertainty is derived from the prediction interval. The inherent uncertainty is modelled with an original approach, directly using all replications of evacuation scenarios without the assumption of a specific probability distribution. This generic metamodel was applied on a case study risk analysis of a road tunnel and showed high accuracy. It was found that metamodel uncertainty and inherent uncertainty have clear effects on the results of the risk analysis, which makes their consideration important.

A generic metamodel for data extraction and generic ontology population

As the next step in the development of intelligent computing systems is the addition of human expertise and knowledge, it is a priority to build strong computable and well-documented knowledge bases. Ontologies partially respond to this challenge by providing formalisms for knowledge representation. However, one major remaining task is the population of these ontologies with concrete application. Based on Model-Driven Engineering principles, a generic metamodel for the extraction of heterogeneous data is presented in this article. The metamodel has been designed with two objectives, namely (1) the need of genericity regarding the source of collected pieces of knowledge and (2) the intent to stick to a structure close to an ontological structure. As well, an example of instantiation of the metamodel for textual data in chemistry domain and an insight of how this metamodel could be integrated in a larger automated domain independent ontology population framework are given.

CHECKSUM: tracking changes and measuring contributions in cooperative systems modeling

Models are often used to represent various types of systems. This is especially true for software systems, where cooperating teams create models using a modeling language (e.g., UML). In cooperative modeling scenarios, it is useful to identify contributions and changes performed by individuals and teams. This paper presents a technique called CHECKSUM, which monitors the cooperative work done on models and maintains an immutable changelog. CHECKSUM uses its changelog to measure contributions based on points, time, and quality, and to enable the auditing of a model’s change-history. This paper also presents GEneric Meta-Model (GEMM). The latter unifies the underlying representation of different types of models that follow varying visualization patterns including box and line, container, and interleaving. GEMM enables CHECKSUM to support an extensible variety of model types. We developed a prototype tool that realizes CHECKSUM’s concepts and integrates it into two existing modeling tools. We conducted two studies to evaluate CHECKSUM from two perspectives: technical and user. The studies yielded positive results concerning various qualities including integrability into existing tools, effectiveness, efficiency, usability, and usefulness.

Engaging end-user driven recommender systems: personalization through web augmentation

In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.

Heritage Science and Cultural Heritage: standards and tools for establishing cross-domain data interoperability

This paper describes a system for documenting scientific data produced in Heritage Sciences. The system is built around a general meta-model, flexible enough to provide descriptions, in a formal language, of the datasets produced by scientific research. Resulting metadata can be re-encoded and published in multiple formats. The underlying metadata schema is inspired by CIDOC CRM principles for data modelling and maintains a full compatibility with CIDOC CRM ontology to capture provenance and foster interoperability with Cultural Heritage information. The use of a wide set of thesauri and controlled vocabularies guarantees internal coherence at data and metadata level. Applicability tests are underway at different institutions and a set of user interfaces has been designed to simplify and speed up the process of data gathering and metadata definition.

Architectural Modelling of Cyber Physical Systems Using UML

Cyber-physical systems (CPS) is an exciting emerging research area that has drawn the attention of many researchers. However, the difficulties of computing and physical paradigm introduce a lot of trials while developing CPS, such as incorporation of heterogeneous physical entities, system verification, security assurance, and so on. A common or unified architecture plays an important role in the process of CPS design. This article introduces the architectural modeling representation of CPS. The layers of models are integrated from high level to lower level to get the general Meta model. Architecture captures the essential attributes of a CPS. Despite the rapid growth in IoT and CPS a general principled modeling approach for the systematic development of these new engineering systems is still missing. System modeling is one of the important aspects of developing abstract models of a system wherein, each model represents a different view or perspective of that system. With Unified Modeling Language (UML), the graphical analogy of such complex systems can be successfully presented.

Project Management Metamodel Construction Regarding IT Departments

Given the fast technological progress, the need for project management continues to grow in terms of methodology and new concepts. In this article, we will build a framework of generating a metamodel that we will apply on the project management to generate a generic metamodel of project management, in this approach we will be based on two methodologies of project management; predictive method (ex: PRINCE 2), Agile method (ex: SCRUM). The goal of this research is to validate and apply this methodology on all the components of IT Governance then to aggregate the metamodels to restore a global metamodel for all IT Governance domains.

Dynamic Metamodel Approach for Government Enterprise Architecture Model Management

Enterprise Architecture (EA) is widely adopted by many organisations to align their business and IT together to ensure the resources optimization is achieved. This recent EA development not only brings positive impacts to the business organisation but the government organisation as well. Nevertheless, during the implementation of EA, one of the challenges is to create a standardised and dynamic metamodel that able to integrate the government agencies business models. To date, it is still yet to find any dynamic metamodel that designed for this purpose. Therefore, this paper aims to propose an EA dynamic metamodel design based on complex cognitive activities (CCA) concept. This study starts with an investigation of EA metamodel concept and current practice through literature review and preliminary interviews, followed by the design on EA dynamic metamodel for government agencies with a selection of Malaysian education EA Reference as a pilot case study. As a result, a Dynamic EA Metamodel by using CCA concept is proposed by utilizing the four layers of dynamic design using cognitive action (physical, perceptual, functional, conceptual) and Archimate generic metamodel schema. This is a new contribution to EA Body of Knowledge (EABoK) and EA practice as it helps for better management of EA models especially for a large and complex organisation of the government sector. This model will allow the EA team in multiple organisations to design and develop their EA models according to their own business process but yet still following the EA metamodel set by the top EA office.

An approach for business process model registration based on ISO/IEC 19763-5

To facilitate business collaboration and interoperation among enterprises, it is critical to discover and reuse appropriate business processes modeled in different languages and stored in different repositories. However, the formats of business process models are very different, which makes it a challenge to fuse them in a unified way without changing their original representations and semantics. To solve this problem, this paper uses semantic interoperability technique which is able to transform heterogeneous process models into uniform registered items. Based on the general and unambiguous metamodel for process model registration (PMR for short) in ISO/IEC 19763-5 that we proposed before, in this article, we provide a generic process model registration framework for registering heterogeneous business process models to facilitate semantic discovery of business processes across enterprises, and promote process interoperation and business collaboration. Considering that Event-driven Process Chain (EPC) is a popular process model widely used in the industry, we focus on the mapping rules and related specific transformation algorithms from EPC to PMR as an instantiation of our framework and develop an automatic process model registration tool for EPC. Moreover, we conduct a series of experiments to verify the correctness and efficiency of our proposed framework by leveraging the real data set of 604 EPCs from SAP.

DALTON: a Generic Meta-Model to Support Business Rules and Requirements Engineering in a PLM System

This paper deals with the management of business rules and requirements to be integrated to a PLM system during the SE process. It proposes a rule and requirement management process made of four stages: the expression of the rule, the activation of the rule, the application of the rule and the checking of the requirement. To support this process, a generic meta-model is presented. The proposed model is called DALTON for “DAta Linked Through Occurrences Network” because it is based on a data network. The model is validated with a use case taken from the nuclear industry, and algorithms in Java were developped to implement the associated reasoning automating the process of rules and requirements engineering.

A metamodel for building energy performance

There is a growing use of metamodels to evaluate building energy performance. However, current metamodeling approaches lack a common foundation. The aim of this work was to develop a general metamodel for building energy performance. Based on the premise that each building element can have an impact on energy performance, our general metamodel assumes that the overall impact is a polynomial function of the individual impacts. The model includes time-dependent parameters such as the solar heat gain coefficient and energy system efficiency. A model derived from the general model was tested on an office located in Paris. Energy needs and consumption, the cost of energy consumption and the CO2 emissions for heating and cooling were analyzed. The study highlighted the significant impact of the choice of the performance criteria in evaluating the efficiency of building design solutions. The metamodel represents a fast way to perform calculations with an accuracy close to that of dynamic simulations. It can be used as a basis to perform parametric studies and for future building energy regulations.

Towards a Platform Independent Graphical User Interface

In classical software development processes, graphical user interfaces cannot be reused across development platforms. In addition, in MDA-based processes, they are integrated only after making the transformation of the PIM to the PSM since they belong to the target platform and hence have the same problem. They are considered part of the PSM, which deprives us from reusing them as we do for the business logic. In this paper, we aim at proposing a common platform independent graphical user interface library that represents the presentation logic in terms of inputs and outputs. This is achievable through proposing a generic metamodel for basic GUI controls that focus on getting and presenting data rather than those of ergonomic purposes. This metamodel will enable us to build generic graphical interfaces that can be transformed to any of the market libraries such as AWT, SWING, WinForms, Tkinter. That is why we built metamodels for those libraries and defined mappings between the generic metamodel and those libraries metamodels. Finally, the generic GUI library is used to make PIM-GUIs that are kept with business-PIMs and that can together be reused in a way that is independent from any development platform. Final mappings transforms these PIM-GUIs into platform bound GUIs or PSM-GUIs such those we mentioned earlier or any future graphical library.

Towards a Meta-Model for Real-Time Embedded Systems

Embedded real-time systems are combinations of hardware and software fully integrated into the systems they control. Due to the continuous technological evolution in the hardware and software and the diversity of the targeted areas of application, these systems have become omnipresent in our professional and personal lives. Thus, various approaches based on model driven engineering (MDE) have been proposed in order to control the inefficiency of the methods of their current design. Each of these approaches has its own meta-model and its corresponding UML profile, specialized or adapted to a particular category of these systems. Indeed, in this paper we will propose a generic meta-model, taking advantage of a large number of these meta-models, which can be adapted to the majority of embedded real-time systems.

Toward a Generic Metamodel for Model Composition Using Transformation

One of the recent trends used in the iterative software development is a model presenting the system at the different levels of abstraction. In this context, model composition is assumed to take one or more models as its input and integrated output model. This paradigm is considered as a crucial activity in Model Driven Architecture (MDA). In this paper we present a generic metamodel for model composition and its farther implementation using Atlas Transformation language (ATL) in order to automate the composition process offered.

Using Discrete Event Simulation Models to Evaluate Resilience of an Emergency Department

Hospitals are critical infrastructures which are vulnerable to natural disasters, such as earthquakes, man-made disasters and mass causalities events. During the emergency, the hospital might also incur in structural and non-structural damage, have limited communication and resources, so they might not be able to treat the large number of incoming patients. For this reason, the majority of medium- and large-size hospitals have an emergency plan that expands their services quickly beyond normal operating conditions to meet an increased demand for medical care, but it is impossible for them to test it before an emergency occurs. The objective of this article is to develop a simplified model that could describe the ability of the Hospital Emergency Department to provide service to all patients after a natural disaster or any other emergency. The waiting time is the main response parameter used to measure hospital resilience to disasters. The analytical model has been built using the following steps. First, a discrete event simulation model of the Emergency Department in a hospital located in Italy is developed taking into account the hospital resources, the emergency rooms, the circulation patterns and the patient codes. The results of the Monte Carlo simulations show that the waiting time for yellow codes, when the emergency plan is applied, are reduced by 96%, while for green codes by 75%. Then, using the results obtained from the simulations, a general metamodel has been developed, which provides the waiting times of patients as function of the seismic input and the number of the available emergency rooms. The proposed metamodel is general and it can be applied to any type of hospital.