Analyzing Defense-in-Depth Properties of Nuclear Power Plant Instrumentation and Control System Architectures Using Ontologies

The overall instrumentation and control (I&C) architecture of a nuclear power plant (NPP) is comprised of several I&C systems and their dependencies. The architecture needs to fulfil the principle of defense in depth (DiD). Defense-in-depth is the principal method for preventing accidents and mitigating the potential consequences of accidents. The levels of DiD should be independent of each other. The primary means to achieve independence are diversity, physical separation, and functional isolation. Approaches with extensive tool support for ensuring that the design solutions of nuclear overall I&C architectures realize relevant DiD properties are scarce. An ontology of the semantic web is a specification of a representational vocabulary for a shared domain of discourse, containing definitions of classes, individuals, and their relationships. An ontology-based knowledge base, built on named graphs, enables a computer to combine pieces of information into valuable knowledge based on queries. In this paper, we present an ontology-based approach for assessing that an NPP I&C architecture fulfils different DiD properties. In our approach, we aim at checking requirements related to physical separation, electrical isolation, communication independence, diversity, safety classification, and failure tolerance. We also discuss the developed work process and tool chain for ontology-based analysis. We demonstrate the use of the ontology and the work process based on two case studies

L-Py: An L-System Simulation Framework for Modeling Plant Architecture Development Based on a Dynamic Language

The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom

Modular Coordination and BIM: Development of Rule Based Smart Building Components

The introduction of computing tools to Architecture, Engineering & Construction (AEC) industry has enabled the professionals to navigate successfully from traditional design/drafting to Computer Aided Design/Drafting (CADD). Furthermore, the industry is slowly transitioning towards sophisticated Building Information Modelling (BIM), which necessitates the integration of domain specific knowledge into the BIM authoring tools. The approach presented in this paper elucidates the development of rule-based BIM objects which allows a designer to create building models within the rules of Modular Coordination (MC). With this development, a designer will be able to use MC standards to size and locate building objects in a modular reference frame. Integration of rules of MC with BIM authoring tool will enhance the design process and allow designers to automate some complex modelling/documentation activities requiring no design expertise. The development of rule-based BIM objects exploits the parametric modelling capabilities of BIM authoring tools in addition to visual programming tool to automate the modelling process. The research first explains development of rule based BIM objects which is extended to streamline the overall design process. The presented approach discusses the customization of BIM authoring tool for modelling a residential facility in MC using axial planning of structural elements. In the prototype system, the designer is guided by specific rules and constraints while providing sufficient options to develop variegated configuration. The integration of design rules of MC standards with BIM application will be influential to increase radical use of BIM for built environment especially in the prefabrication industry. © 2015 The Authors. Published by Elsevier Ltd

Simplifying the Formal Verification of Safety Requirements in Zone Controllers through Problem Frames and Constraints based Projection

Formal methods have been applied widely to verifying the safety requirements of Communication-Based Train Control (CBTC) systems, while the problem situations could be much simplified. In industrial practices of CBTC systems, however, huge complexity arises, which renders those methods nearly impossible to apply. In this paper, we aim to reduce the state space of formal verification problems in Zone Controller, a sub-system of a typical CBTC. We achieve the simplification goal by reducing the total number of device variables. To do this, two projection methods are proposed based on Problem Frames and constraints, respectively. The Problem Frames based method decomposes the system according to sub-properties through functional decomposition, whilst the constraints based projection method removes redundant variables. Our industrial case study demonstrates the feasibility though an evaluation, confirming that these two methods are effective in reducing the state spaces of complex verification problems in this application domain

Fuzzy Logic Control Application: Design and Simulation for Washing Machine

This paper aims to model and simulate washing machine based on user expert knowledge using fuzzy logic. Fuzzy logic inference process to control washing machine in this study use Mamdani method. The method has four steps Fuzzification of linguistic variable, rule evaluation (based on expert experience), aggregation of the rules outputs and final defuzzification. Input linguistic variable used are dirtiness of the clothes, type of fabric, type of dirt and amount of the clothes and the output variable is washing time, washing speed, water intake and water temperature. The system is designed and simulated using Fuzzy logic toolbox on MATLAB. Result show that the washing machine inference relate to user expert perception. The main advantage of using fuzzy logic in washing machine is that it reduce water and electricity consumption also good time management

Computer Aided Industrial Design

None provided

On the modelling and optimisation of urban energy fluxes

Around 3/4 of global resources are currently consumed in urban settlements, with corresponding adverse environmental consequences. According to population forecasts this situation will worsen in the coming years. It is therefore imperative that we understand how to design less resource intensive urban settlements. Software for the modelling and optimisation of resource flows are of interest to support urban designers in achieving this objective. To this end we have, in the first instance, tackled the problem of optimising the layout and form of buildings for the utilisation of solar radiation by using a multi-objective evolutionary algorithm. This new methodology facilitates a considerably more exhaustive search of the parameter space than manual trial and error which has been favoured in past studies. However, multi-objective optimisers involve many redundant evaluations when only one objective (the energy consumption) and analytical constraints (the volume of the urban form has to remain within bounds) are taken into account. To resolve this, we developed a new evolutionary algorithm that avoids evaluations of potential solutions that violate constraints. This is a hybrid based of the CMA-ES and HDE evolutionary algorithms. This hybrid algorithm achieves 100% convergence to the global minimum relating to two highly multi-modal benchmark functions and good results compared to the multi-objective evolutionary algorithm previously used and to a hybrid of heuristic and direct search methods (PSO/HJ) for real-world problems. Key contributions have also been made to the development of a new urban energy modelling tool: CitySim. These contributions include a mono and multi-zone thermal model, which is linked to an HVAC model that takes into account the increased energy demands due to the use of air as medium for heating, cooling and fresh air supply. In order to complete the provision of heating/cooling as well as electricity, the most commonly used energy conversion systems are modelled. Outputs from these systems may also be coupled with a model of sensible/latent heat storage. Finally the new hybrid evolutionary algorithm was used to optimise the energy performance of a case study of 26 buildings in the Matthäus district (Basel) using CitySim as the energy modelling tool. The results indicated that air conditioning plant should not be necessary in Switzerland if occupants behave appropriately. Concrete strategies for minimising the primary energy demand for the case study were also identified subject to constrained investment capital. This demonstrated that optimally (environmentally) sustainable solutions can be found at the urban scale, to help guide urban designers' decisions