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Qualitative reasoning about fluids and mechanics
 UNIVERSITY
, 1993
"... Understanding people's commonsense knowledge about physical world is a fundamental problem in building intelligent systems. If this knowledge can be represented and used by computers, they can duplicate people's ability to understand and interact with the world. Qualitative physics is the ..."
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Understanding people's commonsense knowledge about physical world is a fundamental problem in building intelligent systems. If this knowledge can be represented and used by computers, they can duplicate people's ability to understand and interact with the world. Qualitative physics is the attempt to capture and formalize this knowledge. An important aspect of qualitative reasoning is the ability to derive the possible behaviors of a given physical system from the structure of the system, using minimal initial information. This thesis investigates qualitative domain theories and reasoning techniques which will enable computers to analyze the qualitative behaviors of physical systems which include both mechanical mechanisms and fluids, such as internal combustion engines and hydraulic lift pumps. We have developed a domain theory which integrates richer models of mechanics, fluids, and geometry than previous research in qualitative physics. These theories and inference techniques are embodied in QSA, a program that produces possible behaviors of physical systems.
Artificial Intelligence Research Issues in Computational Simulation of Physical System Behavior
, 1992
"... Computational simulation is an important tool for predicting the behavior of physical systems. Many powerful simulation programs exist today. However, using these programs to reliably analyze a physical situation requires considerable human effort and expertise to set up a simulation, determine whet ..."
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Computational simulation is an important tool for predicting the behavior of physical systems. Many powerful simulation programs exist today. However, using these programs to reliably analyze a physical situation requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but also raises significant AI research issues in the areas of spatial reasoning and deep models of expert reasoning about physics and numerical analysis. Computer Science Department Rutgers University New Brunswick, NJ Contents 1 Introduction 2 2 Domains 3 2.1 Design of Racing Yachts : : : : : : : : : : : : : : : : : : : : : 4 2.2 Clockwork Mechanisms : : : : : : : : : : : : : : : : : : : : : : 5 3 Processes to be Automated 6 3.1 Setting up a Computational Simulation : : : : : : : : : : : :...
Automated Model Generation and Simulation
, 1994
"... Understanding or predicting the behavior of a complex physical system requires the construction and execution of a model of the system. Such a model is often handcrafted by the person studying the system, and the modeling process is not formalized to be reusable by others. We describe a method ..."
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Understanding or predicting the behavior of a complex physical system requires the construction and execution of a model of the system. Such a model is often handcrafted by the person studying the system, and the modeling process is not formalized to be reusable by others. We describe a method which uses first principles to automatically create models and simulators for complex motions, and an implemented system called Oracle. Given a description of a problem involving a physical system, Oracle automatically identifies relevant model fragments, instantiates them for the particular entities and physical phenomena in the problem, composes the instantiated fragments to form a model, and executes the model. Knowledge of physical phenomena is represented with general model fragments which can be shared and reused by many models. Experimental results show that the method is capable of generating correct models of several different types of physical systems if enough doma...
Automated Modeling in Computational Heat Transfer
 In E. Kant (Ed.), AAAI Fall Symposium on Intelligent Scientific Computation
, 1992
"... This paper describes a framework and a system for generating mathematical models (i.e. sets of equations) for analyzing physical systems. The models are derived from physical principles, and include not only models based on algebraic and ordinary differential equations (i.e. "lumped " mod ..."
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This paper describes a framework and a system for generating mathematical models (i.e. sets of equations) for analyzing physical systems. The models are derived from physical principles, and include not only models based on algebraic and ordinary differential equations (i.e. "lumped " models), but also those based on partial differential equations (i.e. "distributed " models). We are motivated the need for analysis models to be used in designing artifacts, and focus on the domMn of thermal manufacturing. Our framework involves three sequential subtasks: identify regions of interest on the artifact, determine and identify the relevant physical processes, transform the set of individual processes into equations and carry out mathematical simplification. We take the view that understanding the task of model generation is fundamental to our future research on approximate modeling in design.
Model Generation from Physical Principles: A Progress Report
, 1992
"... This paper describes a framework and a system for generating mathematical models (i.e. sets of equations) for analyzing physical systems. The models are derived from physical principles, and include not only models based on algebraic and ordinary differential equations (i.e. "lumped" model ..."
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This paper describes a framework and a system for generating mathematical models (i.e. sets of equations) for analyzing physical systems. The models are derived from physical principles, and include not only models based on algebraic and ordinary differential equations (i.e. "lumped" models) , but also those based on partial differential equations (i.e. "distributed " models). We are motivated by the need for analysis models to be used in designing artifacts, and focus on the domain of thermal manufacturing. Our framework involves three sequential subtasks: identify regions of interest on the artifact, determine and identify the relevant physical processes, transform the set of individual processes into equations and carry out mathematical simplification. We take the view that understanding the task of model generation is fundamental to our future research on approximate modeling in design. Introduction This paper describes a framework and a system for generating mathematical models f...
MSG: A Computer System for Automated Modeling of Heat Transfer
 Artificial Intelligence for Engineering Design, Analysis and manufacturing
, 1993
"... The task of modeling, i.e. of creating a set of equations that can be used to predict the behavior of a physical object, is a key step in engineering analysis. This paper describes a computer system, MSG, for generating mathematical models to analyze physical systems involving heat transfer behavior ..."
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The task of modeling, i.e. of creating a set of equations that can be used to predict the behavior of a physical object, is a key step in engineering analysis. This paper describes a computer system, MSG, for generating mathematical models to analyze physical systems involving heat transfer behavior. MSG is motivated by the need for modeling in an automated design process. The models are sets of equations which may include algebraic equations, ordinary differential equations and partial differential equations. MSG uses the strong domain theory to guide model construction in three sequential tasks: identify regions of interests on an object, determine relevant heat transfer and energy storage processes, and transform these processes into equations. The decisions in these tasks are guided by estimates of variation in temperature and material property, and the relative strengths of heat transfer processes. 1 Introduction The task of modeling, i.e. of creating a set of equations that ca...
Approximation Operators in Distributed Modeling
 In 7th International Workshop on Qualitative Reasoning
, 1993
"... Computer programs which do any task which requires reasoning about physical systems need to use models of those systems with varying accuracy /complexity tradeoffs. This paper describes an approach to model generation in the domain of heat transfer which is capable of producing models that vary grea ..."
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Computer programs which do any task which requires reasoning about physical systems need to use models of those systems with varying accuracy /complexity tradeoffs. This paper describes an approach to model generation in the domain of heat transfer which is capable of producing models that vary greatly along this dimension. This approach is based on the law of conservation of energy, which provides a set of choices for the models in terms of "control volumes" and heat flows. These choices are made by using rules of thumb, which can be seen as instances of two reduction operators, deltaiso and dominance. Various rough models are used to estimate the physical parameters on which these rules depend. That is, the rough models are evaluated in the process of building more accurate ones. The application of these operators is only valid for a specific set of physically meaningful quantities; thus we are really reasoning about physics, not equations. This method has been implemented in a runn...
Model~BasedKinematic Simulation
, 1992
"... We present a practical simulation program for rigid part mechanisms, such as feeders, locks, and brakes. The program performs a kinematic simulation of the behavior produced by part contacts and input motions along with a dynamical simulation of the behavior produced by gravity, springs, and frictio ..."
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We present a practical simulation program for rigid part mechanisms, such as feeders, locks, and brakes. The program performs a kinematic simulation of the behavior produced by part contacts and input motions along with a dynamical simulation of the behavior produced by gravity, springs, and friction. It describes the behavior in a compact, symbolic format and with a realistic, threedimensional animation. The program is more efficient and informative than traditional simulators. It examines roughly 1/6 as many degrees of freedom because the kinematics module eliminates the blocked ones. It spends little time on coffision detection because the kinematics module precomputes the configurations where parts collide, It covers more mechanisms than do previous modelbased simulators, generates fuller behavioral descriptions, and exploits kinematics more fully. It uses a simple model of dynamics that captures the steadystate effect of forces without the conceptual and computational cost of dynamical simulation. We demonstrate that our simulation algorithm captures the workings of most mechanisms by surveying 2500 mechanisms from an engineering encyclopedia.
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"... We present a kinematic analysis algorithm for mechanisms built of rigid parts, such as door locks, gearboxes, and transmissions. The algorithm produces a concise and complete description of the kinematics of a mechanism. It optimizes the computation by decomposing complex mechanisms into subassembli ..."
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We present a kinematic analysis algorithm for mechanisms built of rigid parts, such as door locks, gearboxes, and transmissions. The algorithm produces a concise and complete description of the kinematics of a mechanism. It optimizes the computation by decomposing complex mechanisms into subassemblies, deriving the kinematics of the subassemblies, and incrementally composing the results. We define a class of mechanisms for which kinematic analysis is feasible by restricting the shapes, motions, and interactions of parts. The feasible class contains linkages, mechanisms whose parts move along fixed spatial axes, and combinations of the two types. We show that the feasible class covers most mechanisms by surveying 2500 mechanisms from an engineering encyclopedia. We implement the kinematic analysis algorithm for fixedaxes mechanisms. The inputs are the shapes and initial configurations of the parts. The output is a region diagram, a partition of the mechanism configuration space into regions that characterize its operating modes. The program computes the region diagram by identifying motion axes and interacting pairs of parts, partitioning the pairwise configuration spaces, and composing them. Coupling the program with existing linkage analysis packages covers most feasible mechanisms. We identify classes of infeasible mechanisms and describe possible analysis strategies for them. 1
Compositional Modeling For Spatial Problems
, 1994
"... OF THE DISSERTATION Compositional Modeling for Spatial Problems by Kyungsook Han Dissertation Director: Professor Andrew Gelsey Solving a problem about a complex physical system generally involves the creation and execution of a model needed to reason about the problem. Effective problem solving abo ..."
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OF THE DISSERTATION Compositional Modeling for Spatial Problems by Kyungsook Han Dissertation Director: Professor Andrew Gelsey Solving a problem about a complex physical system generally involves the creation and execution of a model needed to reason about the problem. Effective problem solving about a physical system requires the use of an adequate model, the creation of which in turn depends on the types of knowledge available for the physical system and their representation. Such a model is normally created by the person studying the system, but a handcrafted model is often errorprone. Modifying a handcrafted model to solve a similar problem about other physical systems is also difficult, and may take more time than building a new model for the systems. My research has two main goals: (1) automating the construction and execution of models of physical systems for spatial problems, where objects are related to each other either geometrically or topologically to satisfy a set of c...