<p>Command and Control (C2) refers to the process or function of commanding and controlling military or civilian units. For most military context C2 is exercised in an adversarial environment where two or more forces are fighting against each other. In these situations it is desirable to constrain the adversarial forces in order to prevent them from achieving their objectives. By maintaining an accurate view of the possible dependencies and couplings within the own forces and between the own and adversarial forces, constraints can be managed and coordinated.</p><p>The purpose of this thesis is to develop a model that is capable of capturing these dependencies and couplings. This model is developed using the Functional Resonance Analysis Method (FRAM; Hollnagel, 2004). FRAM builds on the assumption that all parts of the system can be described as functional units. These functional units can then be linked together to form large systems. The links themselves are defined by how a function may affect other functions or in turn be affected by them. This enables the model to incorporate complex interactions within the system as well as between two adversarial systems.</p><p>The microworld “Dynamiskt Krigsspel för Experiment” (DKE) was used to develop the model. A scenario with two teams battling in this adversarial microworld setting was analyzed in detail for this purpose. The developed model uses three different layers, or resolutions, of functions to capture all potential couplings between functions. The lowest level of functions, called the tactical level, is the physical actions of the units in the microworld. The next level, the operational level, concerns the more overarching goals for which the tactical functions are used. Last, the strategic level consists of the C2 functions, such as data collection, sensemaking and planning.</p><p>The developed model is then applied to the scenario in DKE and shown to be able to describe and explain all actions by the two adversary systems as well as the couplings and dependencies between them.</p>

Engineering design methods focus on developing products that are innovative, robust, and multi-functional. In this context, the term robust refers to a product's ability to accomplish successfully its predetermined functions. Owing to the abundance of optimized and robust biological systems, engineering designers are now looking to nature for inspiration. Researchers believe that biomimetic or bio-inspired engineering systems can leverage the principles, mechanisms, processes, strategies, and/or morphologies of nature's successful designs. Unfortunately, two important problems associated with biomimetic design are a designer's limited knowledge of biology and the difference in biological and engineering terminologies. This research developed a new design tool that addresses these problems and proposes to help engineering designers develop candidate bio-inspired products or solutions. A methodology that helps users infer or extract biomimetic design principles from a given natural system or biomimetic product pair is described in this thesis. The method incorporates and integrates five existing design tools and theories to comprehensively investigate a given natural system or biomimetic product. Subsequently, this method is used to extract biomimetic design principles from 23 biomimetic products and natural systems. It is proposed that these principles have the potential to inspire ideas for candidate biomimetic products that are novel, innovative, and robust. The principle extraction methodology and the identified principles are validated using two separate case studies and a detailed analysis using the validation square framework. In the first case study, two students and the author use the principle extraction methodology to extract characteristics from a natural system and a biomimetic product pair. Results from this case study showed that the methodology effectively and repeatedly identifies system characteristics that exemplify inherent biomimetic design principles. In the second case study, the developed biomimetic design principles are used to inspire a solution for an engineering design problem. The resulting solution and its evaluation show that the design's achieved usefulness is linked to applying the biomimetic design principles. Similar to the TRIZ principles, the biomimetic design principles can inspire ideas for solutions to a given problem. The key difference is that designers using TRIZ leverage the solution strategies of engineering patents, while designers using the biomimetic design principles leverage nature’s solution strategies. The biomimetic design principles are compared to TRIZ and the BioTRIZ matrix.

Les outils logiciels d’analyse des risques contribuent à la maîtrise de la qualité des produits, notamment en permettant l’identification de leurs modes de défaillances potentiels. Le travail de thèse présenté dans ce mémoire porte sur la définition d’un cadre de modélisation générique adapté aux produits du bâtiment et destiné à servir de base pour le développement d’un tel outil. Ce cadre de modélisation vise à permettre une représentation qualitative et unifiée des systèmes constructifs et de leurs modes de fonctionnement. Les différents objets qui le constituent ainsi que leurs articulations permettant de réaliser l’étude d’un produit sont décrits et illustrés. Un prototype d’outil fonctionnel est ensuite développé sur la base de ces travaux, puis mis en application au travers de plusieurs études. / Software tools for risk analysis contribute to the quality control of products, notably by allowing the identification of their potential failure modes. The thesis work presented in this dissertation concerns the definition of a generic modeling framework suitable for building products and intended to serve as basis for the development of such a tool. This modeling framework is intended to allow a qualitative and unified representation of building systems and their modes of operation. The various objects that constitute it and their articulations are described and illustrated. A functional prototype tool is then developed on the basis of our work, and implemented through several studies.

The use of function has been recognized as an important part of the design process over last two decades, especially at the conceptual design stage, 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 conceptual design process due to their focus on geometrical modeling but not functional modeling. This paper presents a functional modeling approach to guide conceptual die design through functional reasoning steps including functional decomposition, functional supportive synthesis and function-structure mapping. The formed functional model provides a good basis to generate various die structures at the conceptual design stage, because function is a higher level of abstraction than structure, and helps to capture the designer’s intent. The functional modeling process has been implemented in a computerized design environment to expedite the conceptual die design process. / Singapore-MIT Alliance (SMA)

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)

Complex engineering systems involve large numbers of functional elements. Each functional element can exhibit complex behavior itself. Ensuring the ability of such systems to meet the customer's needs and requirements requires modeling the behavior of these systems. Behavioral modeling allows a quantitative assessment of the ability of a system to meet specific requirements. However, modeling the behavior of complex systems is difficult due to the complexity of the elements involved and more importantly the complexity of these elements' interactions. In prior work, formal functional modeling techniques have been applied as a means of performing a qualitative decomposition of systems to ensure that needs and requirements are addressed by the functional elements of the system. Extending this functional decomposition to a quantitative representation of the behavior of a system represents a significant opportunity to improve the design process of complex systems. To this end, a functionality-based behavioral modeling framework is proposed along with a sensitivity analysis method to support the design process of complex systems. These design tools have been implemented in a computational framework and have been used to model the behavior of various engineering systems to demonstrate their maturity, application and effectiveness. The most significant result is a multi-fidelity model of a hybrid internal combustion-electric racecar powertrain that enabled a comprehensive quantitative study of longitudinal vehicle performance during various stages in the design process. This model was developed using the functionality-based framework and allowed a thorough exploration of the design space at various levels of fidelity. The functionality-based sensitivity analysis implemented along with the behavioral modeling approach provides measures similar to a variance-based approach with a computation burden of a local approach. The use of a functional decomposition in both the behavioral modeling and sensitivity analysis significantly contributes to the flexibility of the models and their application in current and future design efforts. This contribution was demonstrated in the application of the model to the 2009 Texas A&M Formula Hybrid powertrain design.

Design-by-Analogy is a powerful tool to augment the traditional methods of concept generation and offers avenues to develop innovative and novel design solutions. Few tools exist to assist designers in systematically seeking and identifying analogies from within design repositories such as the United States Patent and Trademark Office patent database. A new tool for extracting functional analogies from patents has been developed to perform this task utilizing a Vector Space Model algorithm to quantitatively evaluate the functional similarity between design problems and patent descriptions of products. Initially, a Boolean Search approach was evaluated and several limitations were identified such as a lack of quantitative metrics for determining search result relevancy ranking as well as inadequate query mapping methods. Next, a Vector Space Model search tool was developed which includes extensive expansion of the Functional Basis using human-based term classification and automated document indexing techniques. The resulting functional patent controlled vocabulary consists of approximately 2,100 unique functions extracted from 65,000 randomly selected patents. The patent search database was generated by indexing 275,000 patents selected from the over 4 million patents available in digital form. A graphical user interface was developed to facilitate query vector generation, and the accompanying search result viewing interface provides data clustering and relevancy ranking. Two case studies are conducted to evaluate the efficacy of the search engine. The first case study successfully replicated the functional similarity results of a classic Design-by-Analogy problem of the guitar pickup winder. The second case study is an original design problem consisting of an automated window washer, and the results illustrate the range of analogically distant solutions that can be extracted ranging from very near-field, literal solutions to the far-field cross domain solutions. Finally, the search tool’s efficacy with regard to increasing quantity and novelty of ideas produced during Concept Generation is experimentally evaluated. The two factors evaluated are first whether analogies improved performance and second how the functionality level of the analogy impacted performance. The experimental results showed an increase in novelty for high functionality analogies compared with the control and other experimental groups. No statistically significant difference was found with regard to quantity of ideas generated. / text

Command and Control (C2) refers to the process or function of commanding and controlling military or civilian units. For most military context C2 is exercised in an adversarial environment where two or more forces are fighting against each other. In these situations it is desirable to constrain the adversarial forces in order to prevent them from achieving their objectives. By maintaining an accurate view of the possible dependencies and couplings within the own forces and between the own and adversarial forces, constraints can be managed and coordinated. The purpose of this thesis is to develop a model that is capable of capturing these dependencies and couplings. This model is developed using the Functional Resonance Analysis Method (FRAM; Hollnagel, 2004). FRAM builds on the assumption that all parts of the system can be described as functional units. These functional units can then be linked together to form large systems. The links themselves are defined by how a function may affect other functions or in turn be affected by them. This enables the model to incorporate complex interactions within the system as well as between two adversarial systems. The microworld “Dynamiskt Krigsspel för Experiment” (DKE) was used to develop the model. A scenario with two teams battling in this adversarial microworld setting was analyzed in detail for this purpose. The developed model uses three different layers, or resolutions, of functions to capture all potential couplings between functions. The lowest level of functions, called the tactical level, is the physical actions of the units in the microworld. The next level, the operational level, concerns the more overarching goals for which the tactical functions are used. Last, the strategic level consists of the C2 functions, such as data collection, sensemaking and planning. The developed model is then applied to the scenario in DKE and shown to be able to describe and explain all actions by the two adversary systems as well as the couplings and dependencies between them.

Introduction: Exploring the brain for optimal locations for deep brain stimulation (DBS) therapy is a challenging task, which can be facilitated by analysis of DBS efficacy in a large number of patients with Parkinson’s disease (PD). The Unified Parkinson's Disease Rating Scale (UPDRS) scores indicate the DBS efficacy of the corresponding stimulation location in a particular patient. The spatial distribution of these clinical scores can be used to construct a functional model which closely models the expected efficacy of stimulation in the region. Designs and Methods: In this study, different interpolation techniques were investigated that can appropriately model the DBS efficacy for Parkinson’s disease patients. These techniques are linear triangulation based interpolation, ‘roving window’ interpolation and ‘Monopolar inverse weighted distance’ (MIDW) interpolation. The MIDW interpolation technique is developed on the basis of electric field geometry of the monopolar DBS stimulation electrodes, based on the DBS model of monopolar cathodic stimulation of brain tissues. Each of these models was evaluated for their predictability, interpolation accuracy, as well as other benefits and limitations. The bootstrapping based optimization method was proposed to minimize the observational and patient variability in the collected database. A simulation study was performed to validate that the statistically optimized interpolated models were capable to produce reliable efficacy contour plots and reduced false effect due to outliers. Some additional visualization and analysis tools including a graphic user interface (GUI) were also developed for better understanding of the scenario. Results: The interpolation performance of the MIDW interpolation, the linear triangulation method and Roving window method was evaluated as interpolation error as 0.0903, 0.1219 and0.3006 respectively. Degree of prediction for the above methods was found to be 0.0822, 0.2986 and 0.0367 respectively. The simulation study demonstrate that the mean improvement in outlier handling and increased reliability after bootstrapping based optimization (performed on Linear triangulation interpolation method) is 6.192% and 12.8775% respectively. The different interpolation techniques used to model monopolar and bipolar stimulation data is found to be useful to study the corresponding efficacy distribution. A user friendly GUI (PDRP_GUI) and other utility tools are developed. Conclusion: Our investigation demonstrated that the MIDW and linear triangulation methods provided better degree of prediction, whereas the MIDW interpolation with appropriate configuration provided better interpolation accuracy. The simulation study suggests that the bootstrapping-based optimization can be used as an efficient tool to reduce outlier effects and increase interpolated reliability of the functional model of DBS efficacy. Additionally, the differential interpolation techniques used for monopolar and bipolar stimulation modeling facilitate study of overall DBS efficacy using the entire dataset.

Energy harvesting is a promising and evolving field of research capable of supplying power to systems in a broad range of applications. In particular, the ability to gather energy directly from the environment without human intervention makes energy harvesting an excellent option for powering autonomous sensors in remote or hazardous locations. This dissertation examines the possibility of using energy harvesting in new and innovative ways to power wireless sensor nodes placed in the substructures of highway bridges for structural health monitoring. Estimates for power requirements are established, using a wireless sensor node from National Instruments as an example system. Available power in a bridge environment is calculated for different energy sources, including solar radiation, wind, and vibration from traffic. Feasibility of using energy harvesting in such an application is addressed for both power availability and cost as compared with grid power or primary batteries. An in-depth functional analysis of existing energy-harvesting systems is also presented, with insights into where innovation would be most beneficial in future systems. Finally, the development of a suite of complementary energy-harvesting devices is described. Because conditions on bridges may vary, multiple solutions involving different energy domains are desired, with the end user able to select the harvester most appropriate for the specific installation. Concept generation techniques such as mind-mapping and 6-3-5 (C-Sketch) are used to produce a wide variety of concepts, from which several promising concept variants are selected. The continued development for one concept, which harvests vibration using piezoelectric materials, is described. Analytical modeling is presented for static and dynamic loading, as well as predicted power generation. Two proof-of-concept prototypes are built and tested in laboratory conditions. Through the development of this prototype, it is shown that the example wireless sensor node can successfully be powered through energy harvesting, and insights are shared concerning the situations where this and other energy harvesters would be most appropriate. / text