KB3: computer program for automatic generation of fault trees

1999 ◽  
Author(s):  
I. Renault ◽  
M. Pilliere ◽  
N. Villatte ◽  
P. Mouttapa
Keyword(s):  
Computer Program ◽  
Automatic Generation ◽  
Fault Trees

The Automatic Generation of a Mathematical Model for Machinery Systems

1973 ◽  
Vol 95 (2) ◽  
pp. 629-635 ◽  
Author(s):  
D. A. Smith ◽  
M. A. Chace ◽  
A. C. Rubens
Keyword(s):  
Mathematical Model ◽  
Graph Theory ◽  
Computer Program ◽  
Mechanical System ◽  
Input Data ◽  
Automatic Generation ◽  
Electrical Networks ◽  
Lagrange’S Equation ◽  
Detailed Explanation ◽  
Independent Loops

This paper presents a detailed explanation of a technique for automatically generating a mathematical model for machinery systems. The process starts from a relatively small amount of input data and develops the information required to model a mechanical system with Lagrange’s equation. The technique uses elements of graph theory which were developed for electrical networks. The basic identifications required for mechanical systems are: paths from ground to mass centers, the independent loops of parts, if any, and paths associated with applied force effects. The techniques described in this paper have been used successfully in a generalized computer program, DAMN.

Automatic Fault Tree Generation From Multidisciplinary Dependency Models for Early Failure Propagation Assessment

2018 ◽  
Author(s):  
Nikolaos Papakonstantinou ◽  
Joonas Linnosmaa ◽  
Jarmo Alanen ◽  
Bryan O'Halloran
Keyword(s):  
Failure Modes ◽  
Cooling System ◽  
Fault Tree ◽  
System Engineering ◽  
Automatic Generation ◽  
Worst Case ◽  
Fault Trees ◽  
Starting Point ◽  
Failure Propagation ◽  
Event Trees

Safety engineering for complex systems is a very challenging task and the industry has a firm basis and trust on a set of established methods like the Probabilistic Risk Assessment (PRA). New methodologies for system engineering are being proposed by academia, some related to safety, but they have a limited chance for successful adoption by the safety industry unless they provide a clear connection and benefit in relation to the traditional methodologies. Model-Based System Engineering (MBSE) has produced multiple safety related applications. In past work system models were used to generate event trees, failure propagation scenarios and for early human reliability analyses. This paper extends previous work, on a high-level interdisciplinary system model for early defense in depth assessment, to support the automatic generation of fault tree statements for specific critical system components. These statements can then be combined into fault trees using software already utilized by the industry. The fault trees can then be linked to event trees in order to provide a more complete picture of an initiating event, the mitigating functions and critical components that are involved. The produced fault trees use a worst-case scenario approach by stating that if a dependency exists then the failure propagation is certain. Our proposed method doesn’t consider specific failure modes and related probabilities, a safety expert can use them as a starting point for further development. The methodology is demonstrated with a case study of a spent fuel pool cooling system of a nuclear plant.

scholarly journals Artificial intelligence and copyright

2021 ◽  
pp. 15-22
Author(s):  
Daryna Prylypko
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Key Words ◽  
Automatic Generation ◽  
The Other ◽  
International Level ◽  
Human Agent ◽  
Foreign Countries ◽  
The One ◽  
Justice Practice

Key words: copyright, work, artificial intelligence, computer program In the article, the problemsof legislation of Ukraine regarding the issues of copyright on works created due to artificialintelligence were analyzed. Particularly, who is the owner of copyright ofworks created due to artificial intelligence. On the one hand, it could be a developer ofa computer program, from the other hand, it could be a client or an employer. Because,it could happen that there is a situation when robots created something newand original, e.g., how it happened with the project “New Rembrandt”. In this case,computers created a unique portrait of Rembrandt. And here is a question, where isin this portrait original and intellectual works of developers of these computers andprograms. In the contrast, this portrait could be created without people who developedspecial machines, programs, and computers. The article’s author proposes to addinto Ukrainian legislation with following norm: the owner of the copyright createddue to artificial intelligence should be a natural person who uses artificial intelligencefor these purposes within the official relationship or on the basis of a contract. In caseof automatic generation of such work by artificial intelligence, the owner of copyrightshould be the developer.Also, another question arises, particularly, who will be responsible for the damagecaused by the artificial intelligence. As an example, of the solution for this issue Resolution2015/2103 (INL) was given, where is mentioned that human agent could be responsiblefor the caused damage. Because, it is not always a developer is responsiblefor the damage.Also, the legislation and justice practice of foreign countries was explored. Theways of overcoming mentioned problems in legislation of Ukraine were proposed.Such as changing our legislation and giving the exact explanation in who is the ownerof copyright on works created due to artificial intelligence and in which cases this personcould become an owner of the copyright. However, probably, these issues shouldbe resolved at international level regarding globalization.

scholarly journals Development of rules of generation of nominal word forms for new-written variants of the Karelian language

2020 ◽  
Vol 10 (4) ◽  
pp. 679-691
Author(s):  
I. P. Novak ◽  
◽  
N. B. Krizhanovskaya ◽  
T. P. Boyko ◽  
N. A. Pellinen ◽  
...  
Keyword(s):  
Computer Program ◽  
Automatic Generation ◽  
Electronic Version ◽  
Parts Of Speech ◽  
Basic Word ◽  
Word Forms ◽  
Semantic Markup

Introduction: linking of words of texts (tokens) with meanings of lemmas in the dictionary of VepKar corpus significantly facilitates further work on semantic markup of texts. In 2019, inflectional rules were developed for the Vepsian subcorpora VepKar. To the corpus on the base of these rules a function for generation of a complete paradigm on basic word forms was added. VepKar editors need to enter a large number of word forms when they create dictionary entries in three Karelian subcorpora (about 30 for names and 150 for verbs). Therefore, the development of an algorithm and a computer program for generation of word forms of the Karelian language turned out to be timely. Objective: to illustrate how you can use the list of the stems of the nominal parts of speech of two new-written dialects of the Karelian language to create rules for automatic generation of word forms. Research materials: lemmas and word forms from the Open corpus of the Vepsian and Karelian languages, the Corpus of Border Karelia, and the electronic version of the Dictionary of the Karelian language. Results and novelty of the research: grammatical patterns were studied over many years from theoretical sources, and they were also discovered through experiments. Thanks to this, the list of stems and pseudo-stems of word forms was formed for the nominal parts of speech, the system of rules for generation of word forms was developed, and the corresponding computer program is written and tested. The scientific novelty of the study lies in the first attempt to develop uniform rules for the automatic generation of word forms for two dialects of the Karelian language.

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