<p>The difficulties of system design are persistentlyincreasing due to the integration of more functionality on asystem, time-to-market pressure, productivity gap, andperformance requirements. To address the system designproblems, design methodologies build system models at higherabstraction level. However, the design task to map an abstractfunctional model on a system architecture is nontrivial becausethe architecture contains a wide variety of system componentsand interconnection topology, and a given functionality can berealized in various ways depending on cost-performancetradeoffs. Therefore, a system design methodology must provideadequate design steps to map the abstract functionality on adetailed architecture.</p><p>MASIC—Maths to ASIC—is a system design methodologytargeting DSP applications. In MASIC, we begin with afunctional model of the system. Next, the architecturaldecisions are captured to map the functionality on the systemarchitecture. We present a systematic approach to classify thearchitectural decisions in two categories: system leveldecisions (SLDs) and implementation level decisions (ILDs). Asa result of this categorization, we only need to consider asubset of the decisions at once. To capture these decisions inan abstract way, we present three transaction level models(TLMs) in the context of DSP systems. These TLMs capture thedesign decisions using abstract transactions where timing ismodeled only to describe the major synchronization events. As aresult the functionality can be mapped to the systemarchitecture without meticulous details. Also, the artifacts ofthe design decisions in terms of delay can be simulatedquickly. Thus the MASIC approach saves both modeling andsimulation time. It also facilitates the reuse of predesignedhardware and software components.</p><p>To capture and inject the architectural decisionsefficiently, we present the grammar based language of MASIC.This language effectively helps us to implement the stepspertaining to the methodology. A Petri net based simulationtechnique is developed, which avoids the need to compile theMASIC description to VHDL for the sake of simulation. We alsopresent a divide and conquer based approach to verify the MASICmodel of a system.</p><p><b>Keywords:</b>System design methodology, Signal processingsystems, Design decision, Communication, Computation, Modeldevelopment, Transaction level model, System design language,Grammar, MASIC.</p>

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.

München: Auf dem Messegelände findet eine Audi Management Konferenz (MMK) in statt. Das Audi Journal berichtet zum ersten Mal von der MMK. Der Aufbruch: Rupert Stadler – der Vorstandsvorsitzende der AUDI AG – zeichnet in seiner Rede ein Bild über den Weg in die Zukunft. Die Themenschwerpunkte: digital, global, ultra, premium – was steckt dahinter? (AUDI AG 2014)

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.

Dieser Beitrag stellt ein neues, hybrides Modell für die Entwicklung mechanischer und mechatronischer Systeme vor. Ziel ist es, die derzeitig bestehende Lücke zwischen abstrakten Funktionsmodellen und sehr konkreten, geometrieorientierten 3D-CAD-Modellen zu überbrücken. Das hier vorgestellte SkiPo-Modell beschreibt die Interaktionen zwischen den Komponenten eines Systems basierend auf den zugehörigen Material-, Energie- und Signalflüssen. Ergänzt wird diese abstrakte Darstellung mit Skizzen, die wichtige Konstruktionsentscheidungen in einer strukturierten, semistandardisierten Weise dokumentieren. Das Ziel dieser hybriden Modellierung ist es, die unvermeidbaren Iterationen zwischen abstrakten und sehr detaillierten Betrachtungen von mechanischen und mechatronischen Systemen in der frühen Phase der Produktentstehung zu unterstützen. In Erprobungen mit Studentengruppen zeigte sich, dass dieser Modellierungsansatz das Verständnis und die Kommunikation im Team fördern kann.

München: Auf dem Messegelände findet eine Audi Management Konferenz (MMK) in statt. Das Audi Journal berichtet zum ersten Mal von der MMK. Der Aufbruch: Rupert Stadler – der Vorstandsvorsitzende der AUDI AG – zeichnet in seiner Rede ein Bild über den Weg in die Zukunft. Die Themenschwerpunkte: digital, global, ultra, premium – was steckt dahinter? (AUDI AG 2014)

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.

A gap exists in the methods used in industry and available in academia that prevents customers and engineers from having a voice when considering engineering risk appetite in the dynamic shaping of early-phase conceptual design trade study outcomes. Current methods used in Collaborative Design Centers either collect risk information after a conceptual design has been created, treat risk as an afterthought during the trade study process, or do not consider risk at all during the creation of conceptual designs. This dissertation proposes a risk-informed decision making framework that offers a new way to account for risk and make decisions based upon risk information within conceptual complex system design trade studies. A meaningful integration of the consideration of risk in trade studies is achieved in this framework thus elevating risk to the same level as other important system-level design parameters. Trade-offs based upon risk appetites of individuals are explicitly allowed under the framework, enabled by an engineering-specific psychometric risk survey that provides aspirational information to use in utility functions. This dissertation provides a novel framework and supporting methodologies for risk-informed design decisions and trades to be made that are based upon engineering risk appetites in conceptual design trade studies. / Graduation date: 2012

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.

Bibliography: leaves 172-182. / viii, 183 leaves, [96] p. : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Proposes that there are fundamental and inadequately recognised differences between architectural practice and the basis of much design advice about environmental issues in house design. Concludes by discussing the implications of these differences for understanding how environmental issues are currently addressed in house design in Australia. / Thesis (Ph.D.)--University of Adelaide, Dept. of Architecture, 2000