Domain model based hypertext for collaborative authoring

1997 ◽  
pp. 131-144 ◽  
Author(s):  
Weigang Wang ◽  
Claude Ghaoui ◽  
Roy Rada
Keyword(s):  
Domain Model ◽  
Model Based

mparison of model-based identification methods for reserve-capacity assessment of existing bridges

2018 ◽  
Author(s):  
Marco Proverbio ◽  
François-Xavier Favre ◽  
Ian F. C. Smith
Keyword(s):  
Parameter Identification ◽  
Structural Identification ◽  
Domain Model ◽  
Reserve Capacity ◽  
Steel Bridge ◽  
Model Based ◽  
Wrong Identification ◽  
Alternative Methodology ◽  
Existing Bridges ◽  
Residual Minimization

The goal of model-based structural identification is to find suitable values of parameters that affect structure behaviour. To this end, measurements are often compared with predictions of finiteelement models. Although residual minimization (RM) is a prominent methodology for structural identification, it provides wrong parameter identification when flawed model classes are adopted. Error-domain model falsification (EDMF) is an alternative methodology that helps identify candidate models – models that are compatible with behaviour measurements – among an initial model population. This study focuses on the comparison between RM and EDMF for the structural identification of a steel bridge in Exeter (UK). Advantages and limitations of both methodologies are discussed with reference to parameter identification and prognosis tasks such as quantification of reserve capacity. Results show that the employment of RM may lead to wrong identification and unsafe estimations of reserve capacity.

Model-Based Testing of Embedded Systems Exemplified for the Automotive Domain

2010 ◽  
pp. 377-413 ◽  
Author(s):  
Justyna Zander ◽  
Ina Schieferdecker
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Reference Signal ◽  
Test Methods ◽  
Domain Model ◽  
Test Method ◽  
Model Based ◽  
Test Models ◽  
Black Box Testing ◽  
Weak Points

The purpose of this chapter is to introduce the test methods applied for embedded systems addressing selected problems in the automotive domain. Model-based test approaches are reviewed and categorized. Weak points are identified and a novel test method is proposed. It is called model-in-the-loop for embedded system test (MiLEST) and is realized in MATLAB®/Simulink®/Stateflow® environment. Its main contribution refers to functional black-box testing based on the system and test models. It is contrasted with the test methods currently applied in the industry that form dedicated solutions, usually specialized in a concrete testing context. The developed signal-feature-oriented paradigm developed herewith allows the abstract description of signals and their properties. It addresses the problem of missing reference signal flows and allows for a systematic and automatic test data selection. Processing of both discrete and continuous signals is possible, so that the hybrid behavior of embedded systems can be handled.

Methodology for a Partly Automated Parameter Identification for the Validation of Multi-Domain Models

2014 ◽  
Author(s):  
D. Kruse ◽  
C. Schweers ◽  
A. Trächtler
Keyword(s):  
Parameter Identification ◽  
Domain Model ◽  
Domain Expert ◽  
Model Based ◽  
New Approaches ◽  
Domain Models ◽  
Identification Tool ◽  
The Way

The paper presents a methodology for a partly automated parameter identification that is to validate multi-domain models. To this end an identification tool under MATLAB has been developed. It enables a partly automated procedure that uses established methods to identify parameters from complex, nonlinear multi-domain models. In order to integrate such multi-domain models into the tool, an interface based on the Functional Mock-up Interface (FMI) standard can be used. The interface makes the required identification parameters from the multi-domain model automatically available to the identification tool. Additionally a guideline is developed which describes the way in which the respective domain expert has to mark the required identification parameters during modeling. The needs for this methodology as well as its application are shown by a practical example from the industry, using Dymola, the FMI-standard, and MATLAB. The practical example deals with the model-based development of a new washing procedure. The paper presents a partly automated parameter identification for the validation of the absorption part of the multi-domain model. Besides, new approaches to the modelling of this kind of absorption effects will be detailed.

scholarly journals Correcting Hierarchical Plans by Action Deletion

2021 ◽  
Author(s):  
Roman Barták ◽  
Simona Ondrčková ◽  
Gregor Behnke ◽  
Pascal Bercher
Keyword(s):  
Domain Model ◽  
Action Sequence ◽  
Hierarchical Task Network ◽  
Model Based ◽  
Verification Methods ◽  
Htn Planning

Hierarchical task network (HTN) planning is a model-based approach to planning. The HTN domain model consists of tasks and methods to decompose them into subtasks until obtaining primitive tasks (actions). There are recent methods for verifying if a given action sequence is a valid HTN plan. However, if the plan is invalid, all existing verification methods only say so without explaining why the plan is invalid. In the paper, we propose a method that corrects a given action sequence to form a valid HTN plan by deleting the minimal number of actions. This plan correction explains what is wrong with a given action sequence concerning the HTN domain model.

Dynamic Ship Domain Model Based on AIS Data for Inland Waterways

2020 ◽  
Author(s):  
Yankang He ◽  
Di Zhang ◽  
Jinfen Zhang ◽  
Bing Wu ◽  
Carlos Guedes Soares
Keyword(s):  
Open Water ◽  
Domain Model ◽  
Inland Waterways ◽  
Ship Traffic ◽  
Model Based ◽  
Proposed Model ◽  
Channel Boundary ◽  
Domain Models ◽  
Inland Rivers ◽  
Using Data

Abstract The existing ship domain models are mostly based on the navigation behavior of open water vessels, and they are not practicable to directly apply to inland rivers. Therefore, it is necessary to establish an inland ship safety domain model based on the ship traffic characteristic therein. Based on the AIS data in the Yangtze River, this paper establishes the functional relationship between these data through multiple regression analysis using data such as ship spacing, ship length, ship speed, and heading angle. Based on this, the safety distance between ships of different lengths in different situations and other ships is determined, so as to establish a dynamic ship domain model. At the same time, this paper explores the geographical relationship between ship and channel boundary and incorporates it into the ship domain model. Finally, a quantitative approach for ship collision risk is proposed, and the collision threat degree is calculated according to the relative heading of the ship and the position in the dynamic ship domain model. Two case studies, including crossing and overtaking situations, are performed to validate the proposed model.

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