Generating a Performance Stochastic Model from UML Specifications

Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the software design process. This suitable methodology allows software designers to determine the performance of software during design. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model such as Stochastic Petri Net (SPN) or Stochastic process Algebra (SPA) models. Our work belongs to the same category. We propose to derive from a UML model a Stochastic Automata Network (SAN) in order to obtain performance predictions. Our approach is more flexible due to the SAN modularity and its high resemblance to UML' state-chart diagram

Developing Model-Based Design Evaluation for Pipelined A/D Converters

This paper deals with a prospective approach of modeling, design evaluation and error determination applied to pipelined A/D converter architecture. In contrast with conventional ADC modeling algorithms targeted to extract the maximum ADC non-linearity error, the innovative approach presented allows to decompose magnitudes of individual error sources from a measured or simulated response of an ADC device. Design Evaluation methodology was successfully applied to Nyquist rate cyclic converters in our works [13]. Now, we extend its principles to pipelined architecture. This qualitative decomposition can significantly contribute to the ADC calibration procedure performed on the production line in term of integral and differential nonlinearity. This is backgrounded by the fact that the knowledge of ADC performance contributors provided by the proposed method helps to adjust the values of on-chip converter components so as to equalize (and possibly minimize) the total non-linearity error. In this paper, the design evaluation procedure is demonstrated on a system design example of pipelined A/D converter. Significant simulation results of each stage of the design evaluation process are given, starting from the INL performance extraction proceeded in a powerful Virtual Testing Environment implemented in Maple™ software and finishing by an error source simulation, modeling of pipelined ADC structure and determination of error source contribution, suitable for a generic process flow

Enroute flight planning: The design of cooperative planning systems

Design concepts and principles to guide in the building of cooperative problem solving systems are being developed and evaluated. In particular, the design of cooperative systems for enroute flight planning is being studied. The investigation involves a three stage process, modeling human performance in existing environments, building cognitive artifacts, and studying the performance of people working in collaboration with these artifacts. The most significant design concepts and principles identified thus far are the principle focus

Pushing architectural quality further

In this paper, the intentions thriving the implementation of computational modeling of building physics as it is approached in the Architectural engineering courses at Ghent University are discussed. During the bachelor degree, courses focus mainly on integration of basic building physics feasibility in the architectural conceptualization. During the final bachelor year, students program their own simplified 2D models for internal condensation and thermal bridges in a spreadsheet, based on realistic detailing from buildings they studied in other courses. These models are intentionally kept both simplified and strongly mathematically based to nurture thorough comprehension of the physical background of problematic design options. Additionally, evaluation of energy performance with official EPB-software is incorporated in the courses because of its high relevance as a legal benchmark. All these models, including EPB, are (semi)static and thus offer only limited but nevertheless useful information on physical, legal, hygienic… viability of different options at reasonable complexity. Furthermore, they induce basic modeling skills as a basis for further development. During the master’s degree, the focus shifts from taxation of the feasibility of design decisions towards energetic performance as one of the starting points and validation criteria of the design process. For students who wish to specialize in the matter, elective courses and master’s thesis projects on optimization, innovative techniques, passive building standards etc. are offered in which advanced dynamic modeling is used. These models offer an important input for this specific design process as they enable precise, nuanced validation of the robustness and sensitivity for certain parameters of different strategies in a given, very complex, situation. By developing both innovative, more precise models for the master classes besides more powerful integration of modeling with design software (BIM) and robust predesign templates for the bachelor courses with master’s student cooperation, the research team supports these courses in achieving output of the highest possible quality

Heterogeneity in pure microbial systems: experimental measurements and modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale

Convective Heat Transfer coefficients in mechanical night ventilation: a sensitivity analysis

Since the Energy Performance for Buildings Directive (EPBD) was accepted and implemented over the course of the last years, buildings are audited energetically to receive the necessary construction licenses. This augmented the already high attention to research on innovative (passive) energy-saving system concepts even further. Previous research suggests that, although the effect of commissioning can be significant, specific fan power is the most important factor influencing the energetic viability of mechanically driven night ventilation as an active cooling replacement. This parameter should thus be the central point of focus during the design process. In this paper, we present an analysis of the effect of detailed convective heat transfer modeling on the predicted performance, in order to determine the level of detail needed to assess feasibility of this kind of system in early design phases. Results indicate that the effect amounts to 20-50% of the predicted performance and therefore cannot be neglected. It is within the range of effect of the dominant parameter, specific fan power. In light of these results, it is suggested that detailed convective heat transfer coefficient modeling is taken into account whenever forced convection due to large volume flow is introduced

Quality measures for ETL processes: from goals to implementation

Extraction transformation loading (ETL) processes play an increasingly important role for the support of modern business operations. These business processes are centred around artifacts with high variability and diverse lifecycles, which correspond to key business entities. The apparent complexity of these activities has been examined through the prism of business process management, mainly focusing on functional requirements and performance optimization. However, the quality dimension has not yet been thoroughly investigated, and there is a need for a more human-centric approach to bring them closer to business-users requirements. In this paper, we take a first step towards this direction by defining a sound model for ETL process quality characteristics and quantitative measures for each characteristic, based on existing literature. Our model shows dependencies among quality characteristics and can provide the basis for subsequent analysis using goal modeling techniques. We showcase the use of goal modeling for ETL process design through a use case, where we employ the use of a goal model that includes quantitative components (i.e., indicators) for evaluation and analysis of alternative design decisions.Peer ReviewedPostprint (author's final draft

A knowledge-based geometry repair system for robust parametric CAD models

In modern multi-objective design optimization (MDO) an effective geometry engine is becoming an essential tool and its performance has a significant impact on the entire MDO process. Building a parametric geometry requires difficult compromises between the conflicting goals of robustness and flexibility. This article presents a method of improving the robustness of parametric geometry models by capturing and modeling engineering knowledge with a support vector regression surrogate, and deploying it automatically for the search of a more robust design alternative while trying to maintain the original design intent. Design engineers are given the opportunity to choose from a range of optimized designs that balance the ‘health’ of the repaired geometry and the original design intent. The prototype system is tested on a 2D intake design repair example and shows the potential to reduce the reliance on human design experts in the conceptual design phase and improve the stability of the optimization cycle. It also helps speed up the design process by reducing the time and computational power that could be wasted on flawed geometries or frequent human intervention