Engineering topics
Watson, Michael D.
Publications and source records attributed to Watson, Michael D..
Engineering Elegant Systems: Postulates, Principles, and Hypothesis of Systems Engineering
No abstract available
Principles of Sociology in Systems Engineering
Systems engineering involves both the integration of the system and the integration of the disciplines which develop and operate the system. Integrating the disciplines is a sociological effort to bring together different groups, often with different terminology, to achieve a common goal, the system. The focus for the systems engineer is information flow through the organization, between the disciplines, to ensure the system is developed and operated with all relevant information informing system decisions. Robert K. Merton studied the sociological principles of the sciences and the sociological principles he developed apply to systems engineering. Concepts such as specification of ignorance, common terminology, opportunity structures, role-sets, and the reclama (reconsideration) process are all important sociological approaches that should be employed by the systems engineer. In bringing the disciplines together, the systems engineer must also be wary of social ambivalence, social anomie, social dysfunction, insider-outsider behavior, unintended consequences, and the self-fulfilling prophecy. These sociological principles provide the systems engineer with key approaches to manage the information flow through the organization as the disciplines are integrated and share their information. This also helps identify key sociological barriers to information flow through the organization. This paper will discuss this theoretical basis for the application of sociological principles to systems engineering.
Practical Application of Sociology in Systems Engineering
Systems engineering involves both the integration of the system and the integration of the disciplines which develop and operate the system. Integrating the disciplines is a sociological effort to bring together different groups, who often have different terminology, to achieve a common goal, the system. The focus for the systems engineer is information flow through the organization, between the disciplines, to ensure the system is developed and operated will all relevant information informing system decisions. The practical application of the sociology in systems engineering brings in various organizational development concepts including the principles of planned renegotiation and the application of principles to address information barriers created by organizational culture. Concepts such as specification of ignorance, consistent terminology, opportunity structures, role-sets, and the reclama (reconsideration) process are all important sociological approaches that help address the organizational social structure (culture). In bringing the disciplines together, the systems engineer must also be wary of social ambivalence, social anomie, social dysfunction, and insider-outsider behavior. Unintended consequences can result when these social issues are present. These issues can occur when localized subcultures shift from the overarching organizational culture, or when the organizational culture prevents achievement of system goals. These sociological principles provide the systems engineer with key approaches to manage the information flow through the organization as the disciplines are integrated and share their information and provides key sociological barriers to information flow through the organization. This paper will discuss the practical application of sociological principles to systems engineering.
Launch Vehicle and Spacecraft Sensor Fabrication and Qualification Standards
No abstract available
Collaborative Engineering in a Large Geographically Distributed Organization: Digital System Integration (DSI) Across a Full Lifecycle
No abstract available
Exergy Based Analysis for the Environmental Control and Life Support Systems of the International Space Station
When optimizing the performance of complex systems, a logical area for concern is improving the efficiency of useful energy. The energy available for a system to perform work is defined as a system's energy content. Interactions between a system's subsystems and the surrounding environment can be accounted for by understanding various subsystem energy efficiencies. Energy balance of reactants and products, and enthalpies and entropies, can be used to represent a chemical process. Heat transfer energy represents heat loads, and flow energy represents system flows and filters. These elements allow for a system level energy balance. The energy balance equations are developed for the subsystems of the Environmental Control and Life Support (ECLS) system aboard the International Space Station (ISS). The use of these equations with system information would allow for the calculation of the energy efficiency of the system, enabling comparisons of the ISS ECLS system to other systems as well as allows for an integrated systems analysis for system optimization.
NASA Systems Engineering Research Consortium: Defining the Path to Elegance in Systems
No abstract available
NASA Systems Engineering Research Consortium: Defining the Path to Elegance in Systems
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system exergy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modelling, System Robustness, and Value Modelling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
NASA Systems Engineering Research Consortium: Defining the Path to Elegance in Systems
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system energy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modeling, System Robustness, and Value Modeling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
Engineering Elegant Systems: Principles of Systems Engineering
No abstract available
Reduction of Subjective and Objective System Complexity
Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached in finding the optimal or 'best balance' of the system functions and interrelationships. This is achievable following von Bertalanffy's approach of describing systems as a set of equations representing both the system functions and the system interrelationships. Reduction is found based on an objective function defining the system output given variations in the system inputs and the system operating environment. By minimizing the objective function with respect to these inputs and environments, a reduced system can be found. Thus, a reduction of the system complexity is feasible.
Exergy Analysis of Rocket Systems
Exergy is defined as the useful work available from a system in a specified environment. Exergy analysis allows for comparison between different system designs, and allows for comparison of subsystem efficiencies within system designs. The proposed paper explores the relationship between the fundamental rocket equation and an exergy balance equation. A previously derived exergy equation related to rocket systems is investigated, and a higher fidelity analysis will be derived. The exergy assessments will enable informed, value-based decision making when comparing alternative rocket system designs, and will allow the most efficient configuration among candidate configurations to be determined.