Dissertations / Theses on the topic 'Mechanical reasoning'

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.
Includes bibliographical references (p. 63-64).
This thesis describes the Mechnet system, which was created to test an implementation of analogy-based reasoning about mechanical engineering, focusing on tools and machines that would be found in a shop. Mechnet uses common-sense data about how these things are used and what they are made of, and attempts to judge which objects are similar to each other. The goal was to make "sensible" analogies about things, in that they make sense to a human who has experience in this area. Results show some reasonable analogies for many tools and machines entered, but non-sensical analogies in several instances. The problems which cause these non-sensical analogies are discussed and analyzed. Recommendations are made for improvement; and further research into other kinds of common-sense reasoning.
by Aaron M. Sokoloski.
S.B.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 124-128).
Robots that can function in human-centric domains have the potential to help humans with the chores of everyday life. Moreover, dexterous robots with the ability to reason about the maneuvers they execute for manipulation tasks can function more autonomously and intelligently. This thesis outlines the development of a reasoning architecture that uses physics-, social-, and agent capability-based knowledge to generate manipulation strategies that a dexterous robot can implement in the physical world. The reasoning system learns object affordances through a combination of observations from human interactions, explicit rules and constraints imposed on the system, and hardcoded physics-based logic. Observations from humans performing manipulation tasks are also used to develop a unique manipulation repertoire suitable for the robot. The system then uses Bayesian Networks to probabilistically determine the best manipulation strategies for the robot to execute on new objects. The robot leverages this knowledge during experimental trials where manipulation strategies suggested by the reasoning architecture are shown to perform well in new manipulation environments.
by Kenton J. Williams.
S.M.

This work addressed the ongoing attempt for establishing a reliable yet simple system for the detection of tool wear and chatter in vertical milling machines. For this reason, a simple closed-loop system that utilizes wireless sensors, a dynamometer replacement and an artificial intelligence system for signal processing were designed. Various signal analysis techniques were applied to real force signal information containing chatter and wear to determine if they were suitable instruments for detection of such unwanted disturbances. An Index Based Reasoner (IBR) was proposed as a solution for overall signal processing. Furthermore, a novel Torque Analysis Device (TAD) that utilizes piezoelectric sensors was developed to replace the inconvenient and expensive dynamometer that is typically used to obtain force and torque information from vertical mills. When all aspects of this research were tested, the results were found to be successful and thus combined to form the closed-loop monitoring system.

This thesis describes a framework for the high level control of an autonomous unmanned spacecraft. Greater autonomy than currently exist is required for unmanned spacecraft to enable missions to distant planets and bodies. One reason for this is that the signal return time is too long to accommodate real-time control from the ground. A second reason is that spacecraft travelling to bodies where little is known of the environment (e.g. asteroids) must have the capability to respond to unplanned events. In addition, autonomy can help reduce mission operations costs, a very important factor in the current climate where more is expected from space missions at a lower cost. The thesis proposes a novel architecture for an autonomous unmanned spacecraft, based on Distributed Artificial Intelligence (DAI), and more specifically based on the multi-agent paradigm. The proposed model for spacecraft control is decentralised. In this architecture, the spacecraft is made up of agents; the traditional ground-based controller is one agent. The spacecraft is goal-driven; it receives high level goals from the ground. The planning and scheduling of activities to achieve these goals is carried out on-board the spacecraft. The spacecraft is also event-driven; it reacts to events that occur on-board the spacecraft as well as in the environment. A DAI architecture requires a co-ordination mechanism, and a communication structure. Also, distributed versions of algorithms must be provided. In this thesis, co-ordination with and without explicit communication and distributed scheduling were investigated, and a framework proposed for both these issues. An autonomous spacecraft must have inference capability for on-board decision making to enable it to respond to unplanned events. Probabilistic reasoning in the form of Bayesian networks was used to provide the spacecraft with the capability for on-board decision making. Situations may arise where the spacecraft must make decisions with uncertain or incomplete information. The issue of decision making with uncertain or incomplete knowledge (e.g. co-ordination without explicit communication) was investigated using domain specific scenarios. Spacecraft resources are typically very limited in capacity. On-board resource management should result in more efficient use of resources. A framework for an on-board resource manager was defined and implemented using reinforcement learning. A distributed version of the scheduling algorithm using reinforcement learning was developed. Thus, this thesis describes and investigates an architectural framework for a multi-agent approach to spacecraft control.

My work is broadly concerned with the question "How can designs bessynthesized computationally?" The project deals primarily with mechanical devices and focuses on pre-parametric design: design at the level of detail of a blackboard sketch rather than at the level of detail of an engineering drawing. I explore the project ideas in the domain of single-input single-output dynamic systems, like pressure gauges, accelerometers, and pneumatic cylinders. The problem solution consists of two steps: 1) generate a schematic description of the device in terms of idealized functional elements, and then 2) from the schematic description generate a physical description.

Thesis (Ph.D)--Computing, Georgia Institute of Technology, 2008.
Committee Chair: Goel, Ashok; Committee Member: Eastman, Charles; Committee Member: Ferguson, Ronald; Committee Member: Glasgow, Janice; Committee Member: Nersessian, Nancy; Committee Member: Ram, Ashwin.

This thesis is about symptom-based troubleshooting of heavy vehicles. The existing troubleshooting system at Scania is adapted to handle errors based on electronic fault codes. This means that some faults, such as mechanical faults when sensors are missing, are difficult to troubleshoot. In the thesis, a method is developed that will be a part of a symptom-based troubleshooting system which can handle all types of errors. The main objectives of the thesis are both to develop a method that can link customer symptoms with system reactions and also to develop formats for both customer symptoms and FMEA for the developed method. In the thesis, a literature study was first conducted in which troubleshooting methods and principles for the formalization of customer data were identified. The identified troubleshooting methods were Bayesian Network, Case-Based-Reasoning and Fault tree analysis. A case study was then conducted which was based on several documents for troubleshooting in gas engines and gas tanks. In the case study, data from the literature study and the empirically collected data were used to develop the final concept of the method. The case study included, among other things, semi-structured interviews to map out the existing troubleshooting process, and a workshop to choose the final concept. In order to meet the objectives of the thesis two research questions and one question linked to the case study were formulated: Research Questions: • RQ1: How is the troubleshooting process affected by the methods that can be used to link customer symptoms with system reactions in heavy vehicles? • RQ2: How can customer data and FMEA be formalized in order to be useful in the troubleshooting process of heavy vehicles? Case Study: • What kind of data is missing from Scania’s existing documentation to link customer symptoms with system reactions? The thesis resulted in a method based on two troubleshooting methods Bayesian network and Case-Based-Reasoning. The method links customer symptoms with system reactions by excluding human considerations and instead relying on previously documented cases and probabilities. A requirement for using this method is a cooperation between customer support, mechanics and development engineers. The formalization of customer symptoms in the developed method is based on what good data is for mechanics in troubleshooting contexts and what customers are capable of communicating; deviation – the customer’s description of the vehicle’s unexpected condition, position – where the customer considers the deviation to be present, context – what happened before, during and after the deviation was discovered. The conclusions that can be drawn is that it is not necessary to link customer symptoms with system reactions since the developed method allows the customer symptoms to be linked directly to the corrective actions needed. In addition, it was noted that the existing documentation at Scania on customer symptoms and system reactions is insufficient. However, this is not problematic as it was shown that FMEA is redundant for the method developed. In order for customer data to be useful, the formalization should include deviation, position and context. Further conclusions are that the role of the customer support becomes less critical when data driven troubleshooting methods are used, and that the accuracy of the developed method will improve over time as more data will be collected.
Detta arbete behandlar symptombaserad felsökning av tunga fordon. Scanias befintliga felsökningssystem är anpassat för att hantera fel som grundas i elektroniska felkoder. Detta innebär att vissa typer av fel, såsom mekaniska fel när sensorer saknas, är svåra att felsöka. I detta arbete utvecklas en metod som ska ingå i ett symptombaserat felsökningssystem eftersom ett sådant system kan hantera alla typer av fel. Målen med arbetet är att utveckla en metod som kan sammankoppla kundsymptom med systemreaktioner, och utveckla format för kundsymptom och FMEA för den framtagna metoden. I arbetet utfördes först en litteraturstudie där felsökningsmetoder och principer för formaliseringen av kunddata identifierades. Felsökningsmetoderna som identifierades var Bayesiska nätvkerk, Case-Based-Reasoning och Felträdsanalys. Därefter utfördes en fallstudie som grundades på underlag om felsökning inom gasmotorer och gastankar. I fallstudien användes data från litteraturstudien och den empiriskt insamlade data för att utveckla det slutgiltiga konceptet. I fallstudien utfördes bland annat semistrukturerade intervjuer för att kartlägga den befintliga felsökningsprocessen, och en workshop för att kunna välja det slutgiltiga konceptet. För att kunna uppfylla arbetets mål formulerades två forskningsfrågor och en frågeställning kopplad till fallstudien: Forskningsfrågor: • F1: Hur påverkas felsökningsprocessen utifrån de metoder som kan användas för att sammankoppla kundsymptom med systemreaktioner inom tunga fordon? • F2: Hur kan kunddata och FMEA formaliseras för att vara användbara inom felsökningsprocessen av tunga fordon? Fallstudie: • Vilken data saknas i Scanias befintliga dokumentation för att kunna sammankoppla kundsymptom med systemreaktioner? Arbetet resulterade i en metod som baseras på de två felsökningsmetoderna Bayesiska nätverk och Case-Based-Reasoning. Metoden sammankopplar kundsymptom med systemreaktioner genom att exkludera mänskligt avvägande och istället förlita sig på tidigare dokumenterade fall och sannolikhet. En förutsättning för att metoden ska kunna användas är ett samarbete mellan kundmottagare, mekaniker och utvecklingsingenjörer. Formaliseringen av kundsymptom i den framtagna metoden bygger på vad bra data är för mekaniker i felsökningssammanhang och vad kunderna är kapabla att förmedla; avvikelse – kundens beskrivning av fordonets oväntade tillstånd, position – var anser kunden att avvikelsen förekommer, kontext – vad hände innan, under och efter att avvikelsen upptäcktes. Slutsatserna som kan dras utifrån arbetet är att det inte är nödvändigt att sammankoppla kundsymptom med systemreaktioner, utan kundsymptom kan sammankopplas direkt med åtgärder med den framtagna metoden. Dessutom noterades det att den befintliga dokumentationen hos Scania angående kundsymptom och systemreaktioner är bristfällig. Detta är inte problematiskt då det påvisades att FMEA inte är nödvändig för att metoden ska fungera. För att kunddata ska vara användbart bör formaliseringen ske med avvikelse, position och kontext. Ytterligare slutsatser är att kundmottagarrollen blir mindre kritisk när datadrivna felsökningsmetoder används, och att den framtagna metodens träffsäkerhet kommer att förbättras över tid allt eftersom mer data har samlats in.

The purpose of this study was to confirm the original factor structure of the Wide Range Assessment of Memory and Learning (WRAML) utilizing a non-clinical adolescent population. Additional analysis examined the relationship between SAT-M scores and spatial relations ability. Exploratory analyses were conducted to determine ethnic and gender differences on the WRAML and subtests from the DAT. Sixty-four academically talented adolescents completed the WRAML and the mechanical reasoning and spatial relations subtests from the Differential Aptitude Test (DAT). The confirmatory factor analysis found the data obtained to not be a good fit for the factor structure of the WRAML (Sheslow & Adams, 1990). Additional confirmatory analyses were conducted which examined data fit of a three factor model found by reanalyzing the standardization data (Burton et al., 1996; Wasserman & Cambias, 1991) as well as two null models. The data failed to fit any of these three models. No support was found for the second hypothesis that predicted a positive relationship between SAT-M scores and spatial relations ability. Ethnic and gender differences on the WRAML and two DAT subtests were examined and discussed. Limitations of this study were reviewed which may have accounted for the overall lack of results.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
Includes bibliographical references (p. 105-107).
by Leon Chih Wen Wong.
M.S.

The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown considerably since their introduction during the 1970s. The majority of the early knowledge-based systems incorporated shallow knowledge, which sought to define simple cause and effect relationships between a symptom and a fault, that could be encoded as a set of rules. Though such systems enjoyed much success, it was recognised that they suffered from a number of inherent limitations such as inflexibility, inadequate explanation, and difficulties of knowledge elicitation. Many of these limitations can be overcome by developing knowledge-based systems which contain deeper knowledge about the device being diagnosed. Such systems, now generally referred to as model-based systems, have shown much promise, but there has been little evidence to suggest that they have successfully made the transition from the research centre to the workplace. This thesis argues that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex devices, and that both deep and shallow knowledge have their part to play in this process. More specifically this thesis demonstrates how a wide-ranging knowledge-based system for quality assurance, based upon shallow knowledge, can be developed, and implemented. The resultant system, named DIPLOMA, not only diagnoses faults, but additionally provides advice and guidance on the assembly, disassembly, testing, inspection and repair of a highly complex hydro-mechanical device. Additionally it is shown that a highly innovative modelbased system, named MIDAS, can be used to contribute to the provision of diagnostic, explanatory and training facilities for the same hydro-mechanical device. The methods of designing, coding, implementing and evaluating both systems are explored in detail. The successful implementation and evaluation of the DIPLOMA and MIDAS systems has shown that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex hydro-mechanical devices, and that they make a beneficial contribution to the business performance of the host organisation. Furthermore, it has been demonstrated that the most effective and comprehensive knowledge-based approach to fault diagnosis is one which incorporates both deep and shallow knowledge, so that the distinctive advantages of each can be realised in a single application. Finally, the research has provided evidence that the model-based approach to diagnosis is highly flexible, and may, therefore, be an appropriate technique for a wide range of industrial applications.
Science and Engineering Research Council, and Alvey Directorate

The study addresses the automated translation of architectural drawings from 2D Computer Aided Drafting (CAD) data into a Building Information Model (BIM), with emphasis on the nature, possible role, and limitations of a drafting language Knowledge Representation (KR) on the problem and process. The central idea is that CAD to BIM translation is a complex diagrammatic interpretation problem requiring a domain (drafting language) KR to render it tractable and that such a KR can take the form of an information model. Formal notions of drawing-as-language have been advanced and studied quite extensively for close to 25 years. The analogy implicitly encourages comparison between problem structures in both domains, revealing important similarities and offering guidance from the more mature field of Natural Language Understanding (NLU). The primary insight we derive from NLU involves the central role that a formal language description plays in guiding the process of interpretation (inferential reasoning), and the notable absence of a comparable specification for architectural drafting. We adopt a modified version of Engelhard's approach which expresses drawing structure in terms of a symbol set, a set of relationships, and a set of compositional frameworks in which they are composed. We further define an approach for establishing the features of this KR, drawing upon related work on conceptual frameworks for diagrammatic reasoning systems. We augment this with observation of human subjects performing a number of drafting interpretation exercises and derive some understanding of its inferential nature therefrom. We consider this indicative of the potential range of inferential processes a computational drafting model should ideally support. The KR is implemented as an information model using the EXPRESS language because it is in the public domain and is the implementation language of the target Industry Foundation Classes (IFC) model. We draw extensively from the IFC library to demonstrate that it can be applied in this manner, and apply the MVD methodology in defining the scope and interface of the DOM and IFC. This simplifies the IFC translation process significantly and minimizes the need for mapping. We conclude on the basis of selective implementations that a model reflecting the principles and features we define can indeed provide needed and otherwise unavailable support in drafting interpretation and other problems involving reasoning with this class of diagrammatic representations.

The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown considerably since their introduction during the 1970s. The majority of the early knowledge-based systems incorporated shallow knowledge, which sought to define simple cause and effect relationships between a symptom and a fault, that could be encoded as a set of rules. Though such systems enjoyed much success, it was recognised that they suffered from a number of inherent limitations such as inflexibility, inadequate explanation, and difficulties of knowledge elicitation. Many of these limitations can be overcome by developing knowledge-based systems which contain deeper knowledge about the device being diagnosed. Such systems, now generally referred to as model-based systems, have shown much promise, but there has been little evidence to suggest that they have successfully made the transition from the research centre to the workplace. This thesis argues that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex devices, and that both deep and shallow knowledge have their part to play in this process. More specifically this thesis demonstrates how a wide-ranging knowledge-based system for quality assurance, based upon shallow knowledge, can be developed, and implemented. The resultant system, named DIPLOMA, not only diagnoses faults, but additionally provides advice and guidance on the assembly, disassembly, testing, inspection and repair of a highly complex hydro-mechanical device. Additionally it is shown that a highly innovative modelbased system, named MIDAS, can be used to contribute to the provision of diagnostic, explanatory and training facilities for the same hydro-mechanical device. The methods of designing, coding, implementing and evaluating both systems are explored in detail. The successful implementation and evaluation of the DIPLOMA and MIDAS systems has shown that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex hydro-mechanical devices, and that they make a beneficial contribution to the business performance of the host organisation. Furthermore, it has been demonstrated that the most effective and comprehensive knowledge-based approach to fault diagnosis is one which incorporates both deep and shallow knowledge, so that the distinctive advantages of each can be realised in a single application. Finally, the research has provided evidence that the model-based approach to diagnosis is highly flexible, and may, therefore, be an appropriate technique for a wide range of industrial applications.

Videogame designers hope to sculpt gameplay, but actually work in the concrete medium of computation. What they create is code, artwork, dialogue---everything that goes inside a videogame cartridge. In other materially constrained design domains, design-support tools help bridge this gap by automating portions of a design in some cases, and helping a designer understand the implications of their design decisions in others. I investigate AI-based videogame-design support, and do so from the perspective of putting knowledge-representation and reasoning (KRR) at the front. The KRR-centric approach starts by asking whether we can formalize an aspect of the game-design space in a way suitable for automated or semi-automated analysis, and if so, what can be done with the results. It begins with the question, "what could a computer possibly do here?", attempts to show that the computer actually can do so, and then looks at the implications of the computer doing so for design support. To organize the space of game-design knowledge, I factor the broad notion of game mechanics mechanics into four categories: abstract mechanics, concrete audiovisual representations, thematic mappings, and input mappings. Concretely, I investigate KRR-centric formalizations in three domains, which probe into different portions of the four quadrants of game-design knowledge: 1. using story graphs and story-quality functions for writing interactive stories, 2. automatic game design focused on the "aboutness" of games, which auto-reskins videogames by formalizing generalized spaces of thematic references, and 3. enhancing mechanics-oriented videogame prototypes by encoding the game mechanics in temporal logic, so that they can be both played and queried.

Orientador: Prof. Dr. João Ricardo Sato
Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Neurociência e Cognição, 2016.
Com o avanço das tecnologias em neuroimagem, em principal da Ressonância Magnética Funcional, baseada no sinal Blood Oxygenation Level Dependent (BOLD), possibilitou-se a realização de estudos que investigam o funcionamento de redes cerebrais. Dentre as diversas redes a Default Mode Network (DMN) e a Task Positive Network (TPN) tem se destacado na literatura. Isso se deve ao fato de que estas redes estão associadas a diferentes funções cognitivas, como por exemplo, no processo da interação social ou durante o raciocínio mecânico. Este estudo teve como objetivo principal, investigar a conectividade funcional obtida do sinal BOLD entre seis regiões pertencentes às estas duas redes, da quais três regiões estão associadas ao processo de interação social e as outras três estão associadas ao raciocínio mecânico. Esta análise foi realizada em 652 indivíduos entre a segunda infância e a pré-adolescência. Além disso, foi investigado também o possível efeito da idade, do sexo (gênero) e do comportamento social na conectividade funcional entre estas regiões. Os resultados mostram a existência de correlação negativa entre todos os pares de conexões de regiões investigados. A partir desta confirmação, verificou-se a possível influência das variáveis idade e sexo na conectividade funcional, e constatou-se o efeito da variável idade em dois pares de conexões: Córtex Pré-frontal Medial com Sulco Pré-frontal Superior, e Córtex Pré-frontal Lateral com Córtex Pré-frontal Medial. A variável sexo não alcançou valores significativos. Por fim, verificou-se a relação do comportamento social na conectividade funcional dos pares de conexões que apresentaram valores significativos na análise da variável idade. Foi encontrada a evidência de que problemas no comportamento social em crianças entre a segunda infância e a pré-adolescência estão associados a anormalidades na conectividade funcional entre um par de conexão: Córtex Pré-frontal Lateral com Córtex Pré-frontal Medial. Este achado sugere que os indivíduos com problemas de comportamento social apresentam uma correlação negativa menor, mais fraca, nesta conexão.
The advance of technology in neuroimaging, in specific Functional Magnetic Resonance Imaging based on the signal Blood Oxygenation Level Dependent (BOLD), allowed to carry out studies investigating the functioning of brain networks. Among the various networks, the Default Mode Network and the Task Positive Network has been highlighted in the literature. This interest is because these networks are related to different cognitive functions, such as social interaction or mechanical reasoning. This study investigates the functional connectivity of the BOLD signal obtained from six regions belonging to these two networks, of which three regions are associated with the process of social interaction, and the other three are related to the mechanical reasoning. This analysis was performed in 652 individuals between middle childhood and preadolescence. We also investigated the potential effect of age, gender and social behavior in the functional connectivity between these regions. The results show a negative correlation between all pairs of connected regions investigated. From these findings, we examined the possible effects of the variables age and gender in the functional connectivity, and we found the effect of the variable age in two pairs of connections: Medial Prefrontal Cortex with Superior Frontal Sulcus and Lateral Prefrontal Cortex with Medial Prefrontal Cortex. The variable gender did not reach significant values. Finally, we investigate the possible effects of the social behavior in the functional connectivity in this pairs of connections that got significant values in the analysis of variable age. We found evidence that problems in the social behavior of children between middle childhood and preadolescence are associated with abnormalities in functional connectivity between a pair of connection: Lateral Prefrontal Cortex with Medial Prefrontal Cortex. These findings suggest that individuals with social behavior problems have a smaller negative correlation in this pair of connection.

Master’s theses “Application Physics Practical Tasks and Reasoning Schemes in Teaching Mechanic Concepts“ consists of an introduction, 3 sections, conclusions, references to literature and 3 annexes. 8 tables and 18 pictures are presented in the work. The work comprises 72 pages (83 with annexes). Application physics practical task and reasoning schemes, teaching mechanic concept is examined in the theses. The problem of pedagogical and psychological concepts’ formation is examined in section I. In section II all the methodological material (the reasoning of the tasks system, structure and content is presented). The results of the pedagogical experiment are presented in section III. The pedagogical experiment showed, that practical tasks and their conceptional schemes help pupils to improve knowledge in physics as well as an effective way to raise the motivation.

We describe a program called SketchIT capable of producing multiple families of designs from a single sketch. The program is given a rough sketch (drawn using line segments for part faces and icons for springs and kinematic joints) and a description of the desired behavior. The sketch is "rough" in the sense that taken literally, it may not work. From this single, perhaps flawed sketch and the behavior description, the program produces an entire family of working designs. The program also produces design variants, each of which is itself a family of designs. SketchIT represents each family of designs with a "behavior ensuring parametric model" (BEP-Model), a parametric model augmented with a set of constraints that ensure the geometry provides the desired behavior. The construction of the BEP-Model from the sketch and behavior description is the primary task and source of difficulty in this undertaking. SketchIT begins by abstracting the sketch to produce a qualitative configuration space (qc-space) which it then uses as its primary representation of behavior. SketchIT modifies this initial qc-space until qualitative simulation verifies that it produces the desired behavior. SketchIT's task is then to find geometries that implement this qc-space. It does this using a library of qc-space fragments. Each fragment is a piece of parametric geometry with a set of constraints that ensure the geometry implements a specific kind of boundary (qcs-curve) in qc-space. SketchIT assembles the fragments to produce the BEP-Model. SketchIT produces design variants by mapping the qc-space to multiple implementations, and by transforming rotating parts to translating parts and vice versa.

碩士
國立臺灣大學
機械工程學研究所
87
This thesis applies the constraint-directed reasoning method to an expert system for mechanical design. First, the design knowledge and data is represented by the object-oriented knowledge representation method. A dependency constraint network is also established to represent the design requirements of the system or relationships between different components of the system. Then, a constraint-driven reasoning process is developed to find design solutions that satisfy all design constraints. Finally, an expert system with object-oriented knowledge representation and constraint-driven reasoning process is developed for finding feasible solutions of a mechanical system. A post processor for automatically constructing the solid model of design solutions is also included in the expert system. Detail design processes of some examples are given to show that the developed expert system can be used easily and effectively to generate feasible design solutions of mechanical systems.

A mechanical design "compiler" has been developed which, given an appropriate schematic, specifications, and utility function for a mechanical design, returns catalog numbers for an optimal implementation. The compiler has been successfully tested on a variety of mechanical and hydraulic power transmission designs and a few temperature sensing designs. Times required have been at worst proportional to the logarithm of the number of possible combinations of catalog numbers.

The relative significance of upstream design activity to downstream design activity is widely recognized, due to its critical role in determining the final product’s functionality. Although there are now some general methodologies dealing with functions or reasoning about functions, virtually no commercial CAD system can support functional design. In functional modeling, a design problem is represented in a hierarchy of functions and the behaviors that realize the functions. This paper presents a functional design methodology based on a behavior-driven function-environment-structure (B-FES) modeling framework to guide functional design through functional reasoning steps including causal behavioral reasoning (CBR) and functional decomposition. The proposed functional design starts from a set of design specifications including functional requirements and design constraints, and results in diverse behavioral schema corresponding to a set of design alternatives. A design example for functional design of a terminal cut-off unit in an automatic assembly system is used to provide a demonstration of the proposed functional design methodology.
Singapore-MIT Alliance (SMA)

Triangle meshes have become an increasingly popular shape representation. Given the ease of standardization it allows and the proliferation of devices (scanners, range images ) that capture and output shape information as meshes, this representation is now used in applications such as virtual reality, medical imaging, rapid prototyping, digital art and entertainment, simulation and analysis, product design and development. In product development manipulation of mesh models is required in applications such as visualization, analysis, simulation and rapid prototyping. The nature of manipulation of the mesh includes annotation, interactive viewing, slicing, re-meshing, mesh optimization, mesh segmentation, simplification and editing. Of these editing has received the least attention. Mesh model often requires editing either locally or globally based on the application. With the increased use of meshes it is desirable to have formal reasoning tools that enable manipulation of mesh models in product development. The mesh model may contain artifacts like self-intersection, overlapping triangles, inconsistent normal’s of triangles and gaps or holes with or without islands. It is necessary to repair the mesh before further processing the mesh model. An automatic algorithm is proposed to repair and fill arbitrary holes while maintaining curvature continuity across the boundaries of the hole. The algorithm uses slices across the hole to first identify curves that bridge the hole. These curves are then used to find the surface patch that would fill the hole. The proposed algorithm works for arbitrary holes in any mesh model irrespective of the type of underlying surface and is able to preserve features in the mesh model that are missing in the input information. Since editing during product development is mostly feature based, an automatic algorithm to recognize shape features by directly clustering the triangles constituting a feature in a mesh model is proposed. Shape features addressed in the thesis are volumetric features that are associated with either addition or removal of a finite volume. The algorithm involves two steps – isolating features in 2D slices followed by a 3D traversal to cluster all the triangles in the feature. Editing a mesh model mainly implies editing local volumetric features in that model. An automatic algorithm is proposed for parametric editing of volumetric features in the mesh model. The proposed algorithm eliminates the need of original CAD model while manipulating any volumetric feature in the mesh model based on feature parameters. An automatic algorithm to manipulate global shape parameters of the object using the mesh model is developed. Global shape parameters include thickness, drafts and axes of symmetry. As the mesh models do not explicitly carry this information global editing of mesh models (other than for visualization) has not been attempted thus far. This thesis proposes the use of mid-surface to identify and manipulate global shape parameters for a class of objects that are classified as thin walled objects. Mid-curves are first identified on slices of the part and then the mid-surface is obtained from these mid-curves. Results of implementation are presented and discussed along with the scope for future work.

碩士
國立交通大學
理學院碩士在職專班網路學習學程
96
Abstract After having surveyed correlated literature, it is found that students with different aptitudes in mechanical reasoning will perform accordingly in their Physics classes under traditional pedagogical instruction. However, as an in-service teacher, I am convinced that to vary teaching strategies with the intervention of different instructive equipment will cater to the needs of learners with different styles, thus bridge the gap between the performances in physics made by high-achievers and lower-achievers in Mechanical Reasoning Aptitude Test (MRAT). In the unit of “Work and Energy” in the 11th-grade physics curriculum, plenty of dynamic contests cannot be illustrated under conventional pedagogical instruction, which is likely to widen the gap between the performances made by high-achievers and lower-achievers in MRAT in Physics classes. Since the assistance of multimedia can present the dynamic contents illustratively and vividly, low-achievers in MRAT could thus be motivated and illuminated, thus reducing the gap of learning performances. The purpose of the study was to investigate the effects of multimedia-assisted and traditional instructions on learning performances made respectively by high-achievers and low-achievers in Mechanical Reasoning Aptitude Test (MRAT). The study implemented experimental design method. The subjects were 88 senior high school students of one school in Miaoli County. Based on statistical analysis of the findings are as follows: 1. Prior to the standardized test, groups under multimedia-assisted instruction and tradition instruction averagely scored 50.1 and 43.8 respectively, with little significant difference. There is no significant differences of effects of multimedia-assisted and traditional instructions on learning performances. The group with lower mechanical reasoning ability performed better under the multimedia-assisted instruction than under traditional instruction. In contrast, the group with higher mechanical reasoning ability made similar performance under two instructive methods. Since in experiment I, subjects were not grouped based on their mechanical abilities, there was no significant difference yielded. 2. Multimedia-assisted instruction can enhance the learning effects of group with lower mechanical reasoning ability. According to this study, under traditional instruction, group with higher mechanical reasoning ability performed significantly better than their counterpart with lower mechanical reasoning ability. On the other hand, under multimedia-assisted instruction, two groups made similar performances on the post-test. Synthetically deduced from the results of experiment II and III, multimedia-assisted instruction can enhance the learning effects of group with lower mechanical reasoning ability. 3. There was no significant difference yeilded in learning effects after high-achievers in Mechanical Reasoning Aptitude Test (MRAT) had been under multimedia- assisted and traditional instructions respectively. Since the group with higher with better mechanical reasoning ability, they can grasp the abract concepts in the Unit of Work and Energy under conventional instruction. 4. There was a significant difference in learning effects after low-achievers in mechanical reasoning aptitude test had been taught under multimedia- assisted and traditional instructions respectively. The results of the study provide physics teachers with insights into teaching students with different mechanical reasoning abilities, particularly when they offer instructions on the unit of “Work and Engergy.” Keyword: CAI, mechanical reasoning abilities

abstract: The main objective of this project was to create a framework for holistic ideation and investigate the technical issues involved in its implementation. In previous research, logical ideation methods were explored, ideation states were identified, and tentative set of ideation blocks with strategies were incorporated in an interactive software testbed. As a subsequent study, in this research, intuitive methods and their strategies were investigated and characterized, a framework to organize the components of ideation (both logical and intuitive) was devised, and different ideation methods were implemented based on the framework. One of the major contributions of this research is the method by which information passes between different ideation methods. Another important part of the research is that a framework to organize ideas found by different methods. The intuitive ideation strategies added to the holistic test bed are reframing, restructuring, random connection, force connection, and analogical reasoning. A computer tool facilitating holistic ideation was developed. This framework can also be used as a research tool to collect large amounts of data from designers about their choice of ideation strategies, and assessment of their effectiveness.
Dissertation/Thesis
M.S. Mechanical Engineering 2012

In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems.