Domain Independent Characterization of Parametric and Geometric Problems in Embodiment Design

2000 ◽  
Author(s):  
Bernie Bettig ◽  
Jami J. Shah ◽  
Joshua D. Summers
Keyword(s):  
Data Exchange ◽  
Parametric Design ◽  
Canonical Representation ◽  
Domain Specific ◽  
Geometric Problems ◽  
Embodiment Design ◽  
Small Set ◽  
Constraint Problem ◽  
Manufacturing Applications ◽  
Domain Independent

Abstract In embodiment and detailed design one is often concerned with sizing and geometric arrangement. Constraint problems of satisfying certain relationships in feasible designs are often solved by domain specific procedures in design and manufacturing applications. This paper shows that a variety of such problems are reducible to a small set of generic problems solvable by domain-independent procedures. A taxonomy of constraint problem types is developed. The taxonomy is based on the types of entities, constraints, and tasks (reasoning or inquiry) that are to be performed. The “exemplar” is introduced as a new concept for describing complex situational patterns and extracting information of interest. Such a canonical representation of parametric problems is needed for designing cleaner interfaces between applications and generic solvers, as a basis for standardized data exchange between future CAD systems, and for providing the foundations for domain independent shells for parametric design.

Design Shell for Parametric Design at Embodiment Stage

2003 ◽  
Author(s):  
Adwait Vaidya ◽  
Jami Shah
Keyword(s):  
Parametric Design ◽  
Problem Definition ◽  
Design Stage ◽  
Embodiment Design ◽  
System Requirements ◽  
Parameter Values ◽  
Domain Independent

The embodiment design stage involves determination of geometric sizes, key parameter values, and matching of component variables to system requirements. This embodiment design stage can be parametrically represented as an iterative design-redesign problem. This paper presents a domain independent characterization of such problems; the characterization includes problem definition, design relations/procedures, and measures of goodness. The paper also discusses representation issues and solution techniques for design-redesign problems. Design tasks are differentiated as domain independent or problem specific and the scope of each design task with respect to the characterization is delineated. A Design Shell implemented on the basis of this characterization is described. This shell can be configured for evaluating designs in any domain. A case study illustrates the use of this Design Shell in characterizing a specific design problem and exploring its design space.

A Unified Representation of Geometric Constraint Problems to Support Design and Manufacturing Applications

1998 ◽  
Author(s):  
Bernie Bettig ◽  
Jami Shah
Keyword(s):  
Mechanical Design ◽  
Geometric Constraint ◽  
Levels Of Abstraction ◽  
Support Design ◽  
Geometric Problems ◽  
Design And Manufacturing ◽  
Finite Set ◽  
Small Set ◽  
Manufacturing Applications ◽  
High Level

Abstract This research is based on the premise that a large number of problems in a variety of mechanical design and manufacturing domains can be mapped to a finite set of generic geometric problems. This paper presents only the representation aspects, which include not only the entities and their relationships at several levels of abstraction but also geometric tasks. To induce comprehensiveness we start at a very high level, listing many queries/commands arising in mechanical design and manufacturing and generalize these into a small set of generic queries/commands. In doing this we find it necessary to devise a new type of high level entity, the geometry characterization which is described with examples. To ensure tractability we start at a low level, describing primitive entities and constraints, and functions, and work our way up through compound entities and constraints. The end goal of this project is to produce an application independent system for geometric constraint solving and querying that can be integrated with any design or manufacturing application using a standardized representation.

scholarly journals Distributed Simulation Platforms and Data Passing Tools for Natural Hazards Engineering: Reviews, Limitations, and Recommendations

2021 ◽  
Author(s):  
Lichao Xu ◽  
Szu-Yun Lin ◽  
Andrew W. Hlynka ◽  
Hao Lu ◽  
Vineet R. Kamat ◽  
...  
Keyword(s):  
Natural Hazards ◽  
Data Exchange ◽  
Distributed Simulation ◽  
Distributed Data ◽  
Interactive Simulation ◽  
Integrated Simulation ◽  
Domain Specific ◽  
Advantages And Disadvantages ◽  
High Level ◽  
Data Passing

AbstractThere has been a strong need for simulation environments that are capable of modeling deep interdependencies between complex systems encountered during natural hazards, such as the interactions and coupled effects between civil infrastructure systems response, human behavior, and social policies, for improved community resilience. Coupling such complex components with an integrated simulation requires continuous data exchange between different simulators simulating separate models during the entire simulation process. This can be implemented by means of distributed simulation platforms or data passing tools. In order to provide a systematic reference for simulation tool choice and facilitating the development of compatible distributed simulators for deep interdependent study in the context of natural hazards, this article focuses on generic tools suitable for integration of simulators from different fields but not the platforms that are mainly used in some specific fields. With this aim, the article provides a comprehensive review of the most commonly used generic distributed simulation platforms (Distributed Interactive Simulation (DIS), High Level Architecture (HLA), Test and Training Enabling Architecture (TENA), and Distributed Data Services (DDS)) and data passing tools (Robot Operation System (ROS) and Lightweight Communication and Marshalling (LCM)) and compares their advantages and disadvantages. Three specific limitations in existing platforms are identified from the perspective of natural hazard simulation. For mitigating the identified limitations, two platform design recommendations are provided, namely message exchange wrappers and hybrid communication, to help improve data passing capabilities in existing solutions and provide some guidance for the design of a new domain-specific distributed simulation framework.

Semantic Interoperability of GD&T Data Through ISO 10303 Step AP242

2016 ◽  
Author(s):  
Adarsh Venkiteswaran ◽  
Sayed Mohammad Hejazi ◽  
Deepanjan Biswas ◽  
Jami J. Shah ◽  
Joseph K. Davidson
Keyword(s):  
Data Exchange ◽  
Smart Manufacturing ◽  
Context Model ◽  
Product Model ◽  
Shape Information ◽  
Computer Aided Process Planning ◽  
Model Based ◽  
Computer Aided ◽  
Iso 10303 ◽  
Manufacturing Applications

Industries are continuously trying to improve the time to market through automation and optimization of existing product development processes. Large companies vow to save significant time and resources through seamless communication of data between design, manufacturing, supply chain and quality assurance teams. In this context, Model Based Definition/Engineering (MBD) / (MBE) has gained popularity, particularly in its effort to replace traditional engineering drawings and documentations with a unified digital product model in a multi-disciplinary environment. Widely used 3D data exchange models (STEP AP 203, 214) contains mere shape information, which does not provide much value for reuse in downstream manufacturing applications. However, the latest STEP AP 242 (ISO 10303-242) “Managed model based 3D engineering” aims to support smart manufacturing by capturing semantic Product Manufacturing Information (PMI) within the 3D model and also helping with long-term archival. As a primary, for interoperability of Geometric Dimensions & Tolerances (GD&T) through AP 242, CAx Implementor Forum has published a set of recommended practices for the implementation of a translator. In line with these recommendations, this paper discusses the implementation of an AP 203 to AP 242 translator by attaching semantic GD&T available in an in-house Constraint Tolerance Graph (CTF) file. Further, semantic GD&T data can be automatically consumed by downstream applications such as Computer Aided Process Planning (CAPP), Computer Aided Inspection (CAI), Computer Aided Tolerance Systems (CATS) and Coordinate Measuring Machines (CMM). Also, this paper will briefly touch base on the important elements that will constitute a comprehensive product data model for model-based interoperability.

scholarly journals Decision-Theoretic Planning with non-Markovian Rewards

2006 ◽  
Vol 25 ◽  
pp. 17-74 ◽  
Author(s):  
S. Thiebaux ◽  
C. Gretton ◽  
J. Slaney ◽  
D. Price ◽  
F. Kabanza
Keyword(s):  
Decision Process ◽  
Single Interface ◽  
Reward Function ◽  
Domain Specific ◽  
Current State ◽  
Markovian Decision Process ◽  
Solution Methods ◽  
Control Knowledge ◽  
Search Control ◽  
Domain Independent

A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decision-theoretic planning, where many desirable behaviours are more naturally expressed as properties of execution sequences rather than as properties of states, NMRDPs form a more natural model than the commonly adopted fully Markovian decision process (MDP) model. While the more tractable solution methods developed for MDPs do not directly apply in the presence of non-Markovian rewards, a number of solution methods for NMRDPs have been proposed in the literature. These all exploit a compact specification of the non-Markovian reward function in temporal logic, to automatically translate the NMRDP into an equivalent MDP which is solved using efficient MDP solution methods. This paper presents NMRDPP (Non-Markovian Reward Decision Process Planner), a software platform for the development and experimentation of methods for decision-theoretic planning with non-Markovian rewards. The current version of NMRDPP implements, under a single interface, a family of methods based on existing as well as new approaches which we describe in detail. These include dynamic programming, heuristic search, and structured methods. Using NMRDPP, we compare the methods and identify certain problem features that affect their performance. NMRDPP's treatment of non-Markovian rewards is inspired by the treatment of domain-specific search control knowledge in the TLPlan planner, which it incorporates as a special case. In the First International Probabilistic Planning Competition, NMRDPP was able to compete and perform well in both the domain-independent and hand-coded tracks, using search control knowledge in the latter.

Mining Domain Terminologies Using Search Engine's Query Log

2021 ◽  
Vol 20 (6) ◽  
pp. 1-32
Author(s):  
Weijian Ni ◽  
Tong Liu ◽  
Qingtian Zeng ◽  
Nengfu Xie
Keyword(s):  
Language Processing ◽  
Heterogeneous Network ◽  
Transductive Learning ◽  
Query Log ◽  
Domain Specific ◽  
Novel Approach ◽  
Commercial Search Engine ◽  
Domain Expertise ◽  
Traditional Approaches ◽  
Domain Independent

Domain terminologies are a basic resource for various natural language processing tasks. To automatically discover terminologies for a domain of interest, most traditional approaches mostly rely on a domain-specific corpus given in advance; thus, the performance of traditional approaches can only be guaranteed when collecting a high-quality domain-specific corpus, which requires extensive human involvement and domain expertise. In this article, we propose a novel approach that is capable of automatically mining domain terminologies using search engine's query log—a type of domain-independent corpus of higher availability, coverage, and timeliness than a manually collected domain-specific corpus. In particular, we represent query log as a heterogeneous network and formulate the task of mining domain terminology as transductive learning on the heterogeneous network. In the proposed approach, the manifold structure of domain-specificity inherent in query log is captured by using a novel network embedding algorithm and further exploited to reduce the need for the manual annotation efforts for domain terminology classification. We select Agriculture and Healthcare as the target domains and experiment using a real query log from a commercial search engine. Experimental results show that the proposed approach outperforms several state-of-the-art approaches.

Quantifying the Impact of Domain Knowledge and Problem Framing on Sequential Decisions in Engineering Design

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Murtuza Shergadwala ◽  
Ilias Bilionis ◽  
Karthik N. Kannan ◽  
Jitesh H. Panchal
Keyword(s):  
Engineering Design ◽  
Information Acquisition ◽  
Design Problem ◽  
Domain Knowledge ◽  
Optimization Problem ◽  
Domain Specific ◽  
Problem Framing ◽  
Design Solutions ◽  
The Impact ◽  
Domain Independent

Many decisions within engineering systems design are typically made by humans. These decisions significantly affect the design outcomes and the resources used within design processes. While decision theory is increasingly being used from a normative standpoint to develop computational methods for engineering design, there is still a significant gap in our understanding of how humans make decisions within the design process. Particularly, there is lack of knowledge about how an individual's domain knowledge and framing of the design problem affect information acquisition decisions. To address this gap, the objective of this paper is to quantify the impact of a designer's domain knowledge and problem framing on their information acquisition decisions and the corresponding design outcomes. The objective is achieved by (i) developing a descriptive model of information acquisition decisions, based on an optimal one-step look ahead sequential strategy, utilizing expected improvement maximization, and (ii) using the model in conjunction with a controlled behavioral experiment. The domain knowledge of an individual is measured in the experiment using a concept inventory, whereas the problem framing is controlled as a treatment variable in the experiment. A design optimization problem is framed in two different ways: a domain-specific track design problem and a domain-independent function optimization problem (FOP). The results indicate that when the problem is framed as a domain-specific design task, the design solutions are better and individuals have a better state of knowledge about the problem, as compared to the domain-independent task. The design solutions are found to be better when individuals have a higher knowledge of the domain and they follow the modeled strategy closely.

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