Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2008. / Janet K. Allen, Committee Member ; David McDowell, Committee Member ; Jye-Chyi Lu, Committee Member ; Jitesh Panchal, Committee Member ; Farrokh Mistree, Committee Chair.

The development and induction in-service of Unmanned Air Vehicles (UAV) systems in a variety of civil, paramilitary and military roles have proven valuable on high-risk missions. These UAVs based on fixed wing configuration concept have demonstrated their operational effectiveness in recent operations. New UAVs based on rotary wing configuration concept have received major attention worldwide, with major resources committed for its research and development. In this thesis, the design process of a rotary-wing aircraft was re-visualised from an unmanned perspective to address the requirements of rotary-wing UAVs - Vertical Take-off UAVs (VTUAV). It investigates the conventional helicopter design methodology for application in UAV design. It further develops a modified design process for VTUAV addressing the requirements of unmanned missions by providing remote command-and-control capabilities. The modified design methodology is automated to address the complex design evaluations and optimisation process. An illustration of the automated design process developed for VTUAVs is provided through a series of inputs of the requirements and specifications, resulting in an output of a proposed VTUAV design configuration for

The increased use of advanced composites in aerospace manufacturing has led to the development of new production processes and technology. The implementation of advanced composites manufacturing technology is poorly served by traditional cost accounting methods, which distort costs by using inappropriate volume-based allocations of overhead. Activity-based costing has emerged as a methodology which provides more accurate allocation of costs to products or activities by their usage of company resources. Better designs may also be produced if designers could evaluate the cost implications of their choices early in the design process. This research describes a methodology whereby companies can improve product cost estimation at the conceptual design phase, using intelligent searching and arrangement of existing accounting data to enable designers to access the activity cost information more readily. The concept has considerable scope for application in industry because it will allow companies to make better use of information that is already being recorded in their information systems, by providing it in a form which will enable designers to make better informed decisions during the design process. The design decision support framework is illustrated by applying it to a typical problem in aerospace composites manufacturing. Feasibility of the approach is demonstrated using a prototype software model of the Design Decision Support System, implemented using commercially available software. / Ph. D.

Thesis (doctoral)--Rijksuniversiteit Groningen, 1992. / Includes bibliographical references (p. 223-230).

Performance-based landfill design approach is a relatively new design approach adopted recently in solid waste management and applied in USA, European Union countries and some developing-economy countries like South Africa. This approach rejects the strict design criteria and accommodates a design that selects the most appropriate design components of a landfill (final cover, bottom liner, and leachate collection system) and their design details to result in the best overall performance with respect to performance criteria (groundwater contamination and stability) considering the system variables (climatic conditions of the site, site hydrogeology, and size of the landfill). These design components, performance criteria and design variables involved in decision process make performance-based landfill design a complex environmental problem. Decision support systems (DSS) are among the most promising approaches to confront this complexity. The fact that different tools can be integrated under different architectures confers DSSs ability to confront complex problems, and capability to support decision-making processes. In this thesis study, a DSS to aid in the selection of design components considering the design variables and performance criteria for performance-based landfill design was developed. System simulation models and calculation modules were integrated under a unique DSS architecture. A decision support framework composed of preliminary design and detailed design phases were developed. The decision of appropriate design components leading to desired performance was made based on stability issues and vulnerability of groundwater, using knowledge gathered from DSS. Capabilities and use of the developed DSS were demonstrated by one real and one hypothetical landfill case studies.

By 2050, the world’s population is expected to reach 9.7 billion, with over half living in urban settlements (United Nations, 2015). Planning and designing new urban developments and improving existing infrastructure will create or reshape urban landscapes and will carry significant implications for energy consumption, infrastructure costs, and the urban microclimate on a larger scale. Researchers and industry professionals must recognize how changes in land use affect the urban microclimate and, therefore, building energy consumption. Built environment and microclimate studies commonly involve modeling or experimenting with mass and energy exchanges between natural and the built environment. Current methods to quantify these exchanges include the isolated use of microclimate and building energy simulation tools. However, current urban planning and building design processes lack a holistic and seamless approach to quantifying all thermodynamic interactions between natural and built environments; nor is there a method for communicating and visualizing the simulated building energy data. This dissertation has developed a coupling method to quantify the effects of the urban microclimate on building energy consumption. The coupling method was tested on a medium-sized office building and applied to a design case, a redevelopment project in Pittsburgh, PA. Three distinct approaches were used. First, to develop the coupling method, a study was conducted to quantify the importance of accurate microclimate model initialization for achieving simulation results that represent measured data. This initialization study was conducted for 24 cases in the Pittsburgh climate. The initialization study developed a rule-based method for estimating the number of ENVI-met simulations needed to predict the microclimate for an annual period. Second, a coupling method was developed to quantify these microclimate effects on building energy consumption. The Center for Sustainable Landscapes (CSL) building was used as a test-case for this coupling method to measure improvement in predicting building heating and cooling energy consumption. Results show that the coupling method, more than the TMY3 weather data used for energy simulations, can improve building energy consumption predictions for the winter and summer months. Third, to demonstrate industry implications, the coupling method was applied to a design case, the Lower Hill District Redevelopment, Pittsburgh, PA. Comparing the decoupled energy model and TMY3 weather data revealed a high degree of variation in the heating and cooling energy consumption. Overall results reinforced the hypothesis that building surface level coupling is not essential if the energy model accounts for the microclimate effects. A Design Decision Support (DDS) method was also developed as a tool for project stakeholders to communicate high-fidelity simulated energy data.

Energy and cost performance optimization for commercial building system design is growing in popularity, but it is often criticized for its time consuming process. Moreover, the current process lacks integration, which not only affects time performance, but also investors’ confidence in the predicted performance of the generated design. Such barriers keep building owners and design teams from embracing life cycle cost consideration. This thesis proposes a computationally efficient design optimization platform to improve the time performance and to streamline the workflow in an integrated multi-objective building system design optimization process. First, building system cost estimation is typically completed through a building information model based quantity take-off process, which does not provide sufficient design decision support features in the design process. To remedy this issue, an automatic cost estimation framework that integrates EnergyPlus with an external database to perform building systems’ capital and operation costs is proposed. Optimization, typically used for building system design selection, requires a large amount of computational time. The optimization process evaluates building envelope, electrical and HVAC systems in an integrated system not only to explore the cost-saving potential from a single high performance system, but also the interrelated effects among different systems. An innovative optimization strategy that integrates machine learning techniques with a conventional evolutionary algorithm is proposed. This strategy can reduce run time and improve the quality of the solutions. Lastly, developing baseline energy models typically takes days or weeks depending on the scale of the design. An automated system for generating baseline energy model according to ANSI/ASHRAE/IESNA Standard 90.1 performance rating method is thus proposed to provide a quick appraisal of optimal designs in comparison with the baseline energy requirements. The main contribution of this thesis is the development of a new design optimization platform to expedite the conventional decision making process. The platform integrates three systems: (1) cost estimation, (2) optimization and (3) benchmark comparison for minimizing the first cost and energy operation costs. This allows designers to confidently select an optimal design with high performance building systems by making a comparison with the minimum energy baseline set by standards in the building industry. Two commercial buildings are selected as case studies to demonstrate the effectiveness of this platform. One building is the Center for Sustainable Landscapes in Pittsburgh, PA. This case study is used as a new construction project. With 54 million possible design solutions, the platform is able to identify optimal designs in four hours. Some of the design solutions not only save the operation costs by up to 23% compared to the ASHRAE baseline design, but also reduce the capital cost ranging from 5% to 23%. Also, compared with the ASHRAE baseline design, one design solution demonstrates that the high investment of a product, building integrative photovoltaic (BiPV) system, can be justified through the integrative design optimization approach by the lower operation costs (20%) as well as the lower capital cost (12%). The second building is the One Montgomery Plaza, a large office building in Norristown, PA. This case study focuses on using the platform for a retrofit project. The calibrated energy model requires one hour to complete the simulation. There are 4000 possible design solutions proposed and the platform is able to find the optimal design solution in around 50 hours. Similarly, the results indicate that up to 25% capital cost can be saved with $1.7 million less operation costs in 25 years, compare to the ASHRAE baseline design.

The numerous buildings that currently require thermal rehabilitation in Romania means that substantial resources and a large number of competent people are required to carry out surveys and energy audits. However, commercial energy balance software is mostly unaffordable for those organisations involved in this process. This paper describes an energy balance programme – ENEFControl – developed to be a rapid, low cost, local tool able to assist in the choice of energy efficient solutions for buildings. To test the software, thermal and energy analyses were carried out on a 1970s built apartment block in Transylvania. Based on these analyses, three constructive scenarios were proposed for thermal rehabilitation. Compared to the performance of the analysed building, the thermal and energy performance of the retrofitted building in all three scenarios significantly improved. Since European Union accession in 2007, rapidly rising energy costs have affected the Romanian population. ENEFControl offers Romanian engineers and architects an opportunity to speed up the rehabilitation programme of buildings without the need for more expensive expertise and tools.

Product tolerancing decisions made in product design have a significant effect on manufacturing environmental and cost performances by strongly influencing both the selection and operation of processing machinery. These decisions however are typically made without quantitative knowledge of their effects in manufacturing. With estimates of environmental and cost performances of manufacturing processes required to achieve specific part designs earlier in the product design cycle, designers may make more informed, and potentially better, design decisions with respect to manufacturing environmental and cost performance goals. In this thesis a method for quantifiably relating product tolerancing decisions to environmental and cost performances in manufacturing in order to provide decision support for cost and environmentally conscious design for manufacturing is developed. The method is instantiated as an Excel-based tool and exercised by two illustrative examples of increasing complexity, as well as a study of the manufacture of automotive transmission pinion gears with differing tolerance requirements. Uncertainty analysis is performed through the use of @RISK software; the uncertainty of parameters associated with manufacturing operations and machinery is captured through the use of probability density functions and Monte Carlo simulation is performed. Simulation results provide insight into the uncertainty of performance estimates and the risks associated with ensuing decision making. This method may be useful to product designers, as well as process planners, to support decision making efforts related to cost and environmental consciousness in the manufacturing phase of the product life cycle.