A Rule-Based Narai-Design System for CIM for Shipbuilding

Recently, a structural optimization design system linked with a FEM analysis system is going to be useful for a structural design, by a radical development of a computer environment. But, when structural engineers use this design system in practice, complicated operations are required to make an input-data. So this design system is not “a Practical Tool” for designers, we have to develop the structural optimization design system which is used easily for designers.Authors research the CIM for shipbuilding and develop a prototype CIM system. We call this system SODAS (System Of Design and Assembling for Shipbuilding). In the SODAS, designers can design a ship structure by design parameters and evaluate a designed structure by FEM directly.In this study, authors try to integrate a commercial structural optimization design system (GENESIS : which is developed in NASA) with the SODAS. We make relations clear between design parameters in the SODAS and design variables in the structural optimization design system. And we propose the method of system integration used by these relations. In the concrete, we develop the structural optimization design system based on the Product Model which supports designers powerfully by presenting optimal design-values.

Structural system design is the process of giving form to a set of interconnected components subjected to loads and design constraints while navigating a complex design space. While safe designs are relatively easy to develop, optimal designs are not. Modern computational optimization approaches employ population based metaheuristic algorithms to overcome challenges with the system design optimization landscape. However, the choice of the initial population, or ground structure, can have an outsized impact on the resulting optimization. This paper presents a new method of generating such ground structures, using a combination of topology optimization (TO) and a novel system extraction algorithm. Since TO generates monolithic structures, rather than systems, its use for structural system design and optimization has been limited. In this paper, truss systems are extracted from topologies through morphological analysis and artificial intelligence techniques. This algorithm, and its assessment, constitutes the key contribution of this paper. The structural systems obtained are compared with ground truth solutions to evaluate the performance of the algorithms. The generated structures are also compared against benchmark designs from the literature. The results indicate that the presented truss generation algorithm produces structures comparable to those generated through metaheuristic optimization, while mitigating the need for assumptions about initial ground structures.

Rule-based systems are relatively easier to explain to end users because rules can be expressed as if/else conditions. Indeed, at times there are multiple if/else conditions. Expert systems are deterministic in nature and very accurate, because they are driven by well-established rules and conditions. The need for explainability arises when multiple rules either conflict or are combined in such a way that it is difficult to interpret. In the field of artificial intelligence, an expert system is a program designed to simulate a real decision making process. Expert systems are designed to solve complex problems by simple reasoning and are represented as if/else/then conditions. Expert systems are designed to act like an inference engine. The role of an inference engine is to make decisions. Sometimes expert systems are simple, like a decision tree, and sometimes expert systems are very complex. Complex expert systems require a knowledge base. Sometimes these knowledge bases are an ontology, which is a form of a body of knowledge, through which a particular rule can be framed and inferencing can be done.

An approach to automate the design of fixed offshore structures

This paper presents a prototype for a structural analysis and design system by using the STEP for the representation and exchange of information on steel structures, by integrating the product model of steel framed structures of AP 230, the geometric and topological information of Part 42, and the detailed Finite Element Analysis information of Part 104 into an unified system. Thus, the STEP-based system makes engineering information more clearable and exchangeable between computer applications than any other conventional methods. This system may be further extended to incorporate such computer applications as detailed engineering and manufacturing information on steel structures.

Building-focused structural engineering has been an advanced user of computational technologies over the last 3 decades. During this time, there was still a lack of integration among the participants involved in the structural design, which obstructs advancements in the structural design process. To address this, the creation of an integrated structural process model (ISPM) was formulated to promote advances in the design of structural systems through collaboration and integration among participants. The resulting ISPM is overarching in nature in that it is not specific to a structural material or system, but its scope is comprehensive because it encompasses a project from planning through construction. Within the ISPM are tasks to complete the structural processes, data-driven information exchanges among participants, and holistic representations and descriptions for methods and tools to perform the processes. The broad architectural/engineering/construction (A/E/C) impact of the structural level...

This paper considers the possible enhancement of the capabilities of an expert system tool. Most of the commercial tools currently available are not particularly suitable for developing expert systems that involve routine design calculations. To overcome this drawback for engineering applications, numerical computations may be carried out by conventional computer programs which can be linked to an expert system tool through its external program interface. This type of expert systems is called a "hybrid" or "coupled" expert system. Practicing engineers will, sooner or later, face the need to use hybrid expert systems. This paper presents a case study which shows how the capabilities of a commercial expert system tool can be enhanced by integrating it with a conventional computer program. The hybrid expert system developed by the authors for illustration purpose can be used for the analysis of plane steel trusses and the evaluation of member design forces. It utilizes an in-house program called “Manager” to integrate two commercial software packages: an expert system tool called KES and a structural analysis package named PFRAME. The capabilities of the hybrid system appear to exceed those of the individual software packages. Key words: knowledge based expert systems, expert system building tools, hybrid expert systems, structural analysis, structural design.

Knowledge-based Systems and Expert Systems, in particular, are expensive to build and difficult to validate and debug because of their complexity and dynamism. Therefore, it is not easy for knowledge engineer and domain expert to identify the gaps and mistakes in knowledge base. Unit testing is unable to cover validation process at all stages, in many cases manual thorough review of decision process is needed. In this paper we spot main approaches to validation and verification issue and describe a component that helps to debug a knowledge base by visualising execution of rules that derive a particular result. This component is developed for Knowledge-based Systems built on Drools Platform1 and we demonstrate application of this component in a knowledge-based engineering system for structural optical design.

This paper proposes a new integrated design method to simultaneously optimize the coupled structural parameters and controllers of mechanical systems by combining decentralized control techniques and Riccati-based control theories. The proposed integrated design method aims at minimizing the closed-loop H2 norm from the disturbance to the system cost. In this paper, the integrated design problems have been formulated in the cases of full state-feedback controllers and full order output-feedback controllers. We extend the current linear time invariant (LTI) control system to a more general framework suitable for the needs of integrated design, where the structural design is treated as a passive control optimization tackled by decentralized control techniques with static output feedback, while the active controller is optimized by solving modified Riccati equations. By using this dual-loop control system framework, the original integrated design problem is transferred to a constrained structural design problem with some additional Riccati-equation based constraints simultaneously integrating the controller synthesis. This reduces the independent design variables from the structural design parameters and the parameters of the controller to the structural design parameters only. As a result, the optimization efficiency is significantly improved. Then the constrained structural design problem is reformed as an unconstrained optimization problem by introducing Lagrange multipliers and a Lagrange function. The corresponding optimal conditions for the integrated design are also derived, which can be efficiently solved by gradient-based optimization algorithms. Later, two design examples, an active–passive vehicle suspension system and an active–passive tuned mass damper (TMD) system, are presented. The improvement of the overall system performance is also presented in comparison with conventional design methods.

This paper presents a planning methodology using an application of a mathematical and a rule-based expert system (ES) to expand the transmission network in a deregulated environment. In this methodology, the ES suggests a realistic set of generation additions with proper economic signals to the participants, before proceeding with the transmission expansion. A feasible list of transmission alternatives is then assumed to accommodate the proposals for generation. A mathematical method is performed based on marginal cost allocation to optimize the location for the new generation and its transmission expansion scheme simultaneously for each alternative. The optimum alternative that minimizes the overall system's cost function and satisfies the future demand is obtained. The ES interacts with the power system planning tools to produce the optimum expansion plan. A practical application is given to demonstrate the effectiveness of the developed prototype system.

This eight-volume report presents guidelines for performing verification and validation (V&V) on Artificial Intelligence (Al) systems with nuclear applications. The guidelines have much broader application than just expert systems; they are also applicable to object-oriented programming systems, rule-based systems, frame-based systems, model-based systems, neural nets, genetic algorithms, and conventional software systems. This is because many of the components of AI systems are implemented in conventional procedural programming languages, so there is no real distinction. The report examines the state of the art in verifying and validating expert systems. V&V methods traditionally applied to conventional software systems are evaluated for their applicability to expert systems. One hundred fifty-three conventional techniques are identified and evaluated. These methods are found to be useful for at least some of the components of expert systems, frame-based systems, and object-oriented systems. A taxonomy of 52 defect types and their delectability by the 153 methods is presented. With specific regard to expert systems, conventional V&V methods were found to apply well to all the components of the expert system with the exception of the knowledge base. The knowledge base requires extension of the existing methods. Several innovative static verification and validation methods for expert systems have been identified and are described here, including a method for checking the knowledge base {open_quotes}semantics{close_quotes} and a method for generating validation scenarios. Evaluation of some of these methods was performed both analytically and experimentally. A V&V methodology for expert systems is presented based on three factors: (1) a system`s judged need for V&V (based in turn on its complexity and degree of required integrity); (2) the life-cycle phase; and (3) the system component being tested.

A fundamental shift in the preferred approach to building applied artificial intelligence (AI) systems has taken place since the late 1960s. Previous work focused on the construction of general-purpose intelligent systems; the emphasis was on powerful inference methods that could function efficiently even when the available domain-specific knowledge was relatively meager. Today the emphasis is on the role of specific and detailed knowledge, rather than on reasoning methods. The first successful application of this method, which goes by the name of knowledge-based or expert-system research, was the DENDRAL program at Stanford, a long-term collaboration between chemists and computer scientists for automating the determination of molecular structure from empirical formulas and mass spectral data. The key idea is that knowledge is power, for experts, be they human or machine, are often those who know more facts and heuristics about a domain than lesser problem solvers. The task of building an expert system, therefore, is predominantly one of “teaching” a system enough of these facts and heuristics to enable it to perform competently in a particular problem-solving context. Such a collection of facts and heuristics is commonly called a knowledge base. Knowledge-based systems are still dependent on inference methods that perform reasoning on the knowledge base, but experience has shown that simple inference methods like generate and test, backward-chaining, and forward-chaining are very effective in a wide variety of problem domains when they are coupled with powerful knowledge bases. If this methodology remains preeminent, then the task of constructing knowledge bases becomes the rate-limiting factor in expert-system development. Indeed, a major portion of the applied AI research in the last decade has been directed at developing techniques and tools for knowledge representation. We are now in the third generation of such efforts. The first generation was marked by the development of enhanced AI languages like Interlisp and PROLOG. The second generation saw the development of knowledge representation tools at AI research institutions; Stanford, for instance, produced EMYCIN, The Unit System, and MRS. The third generation is now producing fully supported commercial tools like KEE and S.1. Each generation has seen a substantial decrease in the amount of time needed to build significant expert systems. Ten years ago prototype systems commonly took on the order of two years to show proof of concept; today such systems are routinely built in a few months. Three basic methodologies—frames, rules, and logic—have emerged to support the complex task of storing human knowledge in an expert system. Each of the articles in this Special Section describes and illustrates one of these methodologies. “The Role of Frame-Based Representation in Reasoning,” by Richard Fikes and Tom Kehler, describes an object-centered view of knowledge representation, whereby all knowldge is partitioned into discrete structures (frames) having individual properties (slots). Frames can be used to represent broad concepts, classes of objects, or individual instances or components of objects. They are joined together in an inheritance hierarchy that provides for the transmission of common properties among the frames without multiple specification of those properties. The authors use the KEE knowledge representation and manipulation tool to illustrate the characteristics of frame-based representation for a variety of domain examples. They also show how frame-based systems can be used to incorporate a range of inference methods common to both logic and rule-based systems. "Rule-Based Systems,” by Frederick Hayes-Roth, chronicles the history and describes the implementation of production rules as a framework for knowledge representation. In essence, production rules use IF conditions THEN conclusions and IF conditions THEN actions structures to construct a knowledge base. The autor catalogs a wide range of applications for which this methodology has proved natural and (at least partially) successful for replicating intelligent behavior. The article also surveys some already-available computational tools for facilitating the construction of rule-based knowledge bases and discusses the inference methods (particularly backward- and forward-chaining) that are provided as part of these tools. The article concludes with a consideration of the future improvement and expansion of such tools. The third article, “Logic Programming, ” by Michael Genesereth and Matthew Ginsberg, provides a tutorial introduction to the formal method of programming by description in the predicate calculus. Unlike traditional programming, which emphasizes how computations are to be performed, logic programming focuses on the what of objects and their behavior. The article illustrates the ease with which incremental additions can be made to a logic-oriented knowledge base, as well as the automatic facilities for inference (through theorem proving) and explanation that result from such formal descriptions. A practical example of diagnosis of digital device malfunctions is used to show how significantand complex problems can be represented in the formalism. A note to the reader who may infer that the AI community is being split into competing camps by these three methodologies: Although each provides advantages in certain specific domains (logic where the domain can be readily axiomatized and where complete causal models are available, rules where most of the knowledge can be conveniently expressed as experiential heuristics, and frames where complex structural descriptions are necessary to adequately describe the domain), the current view is one of synthesis rather than exclusivity. Both logic and rule-based systems commonly incorporate frame-like structures to facilitate the representation of large amounts of factual information, and frame-based systems like KEE allow both production rules and predicate calculus statements to be stored within and activated from frames to do inference. The next generation of knowledge representation tools may even help users to select appropriate methodologies for each particular class of knowledge, and then automatically integrate the various methodologies so selected into a consistent framework for knowledge.

Introduction. Expert witness reports, prepared with the aim of quantifying fault rates among parties, play an important role in a court's final decision. However, conflicting fault rates assigned by different expert witness boards lead to iterative objections raised by the related parties. This unfavorable situation mainly originates due to the subjectivity of expert judgments and unavailability of objective information about the causes of accidents. As a solution to this shortcoming, an expert system based on a rule-based system was developed for the quantification of fault rates in construction fall accidents. The aim of developing DsSafe is decreasing the subjectivity inherent in expert witness reports. Methodology. Eighty-four inspection reports prepared by the official and authorized inspectors were examined and root causes of construction fall accidents in Turkey were identified. Using this information, an evaluation form was designed and submitted to the experts. Experts were asked to evaluate the importance level of the factors that govern fall accidents and determine the fault rates under different scenarios. Based on expert judgments, a rule-based expert system was developed. The accuracy and reliability of DsSafe were tested with real data as obtained from finalized court cases. Result. DsSafe gives satisfactory results.

"The main aims of this thesis were to investigate the main aspects of the design and implementation of rubble-mound structures as a form of shoreline stabilisation and coastal defence. An emphasis has been placed on the Irish context of how these structures have been implemented in the past. The intention was that this work would improve the understanding of the use of these structures for future projects both in Ireland and internationally. This work required a literature review which investigated the general aspects of rubble-mound structures, the coastal environment, and the theory of designing the structures’ layout, cross-section and impact upon the local shoreline as well as the subsequent environmental, economic and social impacts such a project might have. Furthermore detailed case studies have been undertaken on beaches in Ireland where rubble-mound beach stabilisation structures have been proposed or implemented. A computer programme has been developed capable of designing the structural layout and cross section for two forms of rubble-mound shoreline stabilisation structures, namely offshore breakwaters and groynes. The Rubble-mound Structure Analysis and Design System is also capable of predicting the shoreline response and the carbon footprint and cost of both structural systems. This system is based on the information presented in the literature review. RSADS has facilitated a detailed study into the sizing of Rubble-mound structure armour units which are the primary structural element of this form of coastal defence. This work has culminated in a detailed study of Youghal Beach in County Cork. This study has involved a beach level survey, and a detailed review of the coastal processes and existing coastal structures. Coastal structures which have been proposed for Youghal by Malachy Walsh & Partners have also been reviewed. Finally RSADS has been implemented to carry out a full design for the shoreline at Youghal resulting in a final proposal of a rock armoured rubble-mound groyne field. Finally the conclusions on the work carried out, future work and the topic in general are presented in the final chapter of this thesis."

Conceptual design of structural systems based on topology optimization and prefabricated components