Modular design

Summary

Modular design, or modularity in design, is a design principle that subdivides a system into smaller parts called modules (such as modular process skids), which can be independently created, modified, replaced, or exchanged with other modules or between different systems. Overview A modular design can be characterized by functional partitioning into discrete scalable and reusable modules, rigorous use of well-defined modular interfaces, and making use of industry standards for interfaces. In this context modularity is at the component level, and has a single dimension, component slottability. A modular system with this limited modularity is generally known as a platform system that uses modular components. Examples are car platforms or the USB port in computer engineering platforms. In design theory this is distinct from a modular system which has higher dimensional modularity and degrees of freedom. A modular system design has no distinct lifetime and exhibits flexibili

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https://en.wikipedia.org/wiki/Modular_design

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Dynamic non-contacting seals have been identified as the most appropriate sealing technology for reduced-scale and high-speed turbomachinery applications since they provide a clearance gap preventing rotor-to-seal contact during operation. Yet, any clearance, however small, between rotor and seal permits the passage to fluid flow across regions of unequal pressure as a leakage which penalize the overall system efficiency. A thorough theoretical and experimental investigation of these types of gas seal at a reduced scale, however, is missing today. Furthermore, in thermodynamic cycles, fluids often operate within the vicinity of the saturation line where the well-known ideal gas law is not valid. For reduced scale turbomachinery seals operating close to the fluid saturation line, validated models to capture the real gas effects are not available yet. The aim of this thesis is to address these shortcomings. Initially, a qualitative research approach has been used for the selection of the ideal seals for reduced-scale applications. Using the qualitative data available from the literature of large-scale seals, a weighted decision matrix has been implemented. For assessing the robustness of the selection process, the sensitivity analysis has been carried out by using different weight distributions. The top two ranked seals, namely, Hole Pattern Seal (HPS) and Pocket Damper Seal (PDS), have been identified as the most promising seals for reduced-scale turbomachinery applications due to their low leakage rates and their low influence on the rotordynamic system. In order to predict the seal performance, the commonly used bulk-flow approach has been used for the numerical modeling approach. Furthermore, for the comparison purpose, three different state-of-the-art models have been implemented. As a benchmark, the predicted results from the different models are compared with the experimental data of well-established literature. A good agreement between the different seal models and the experimental data has been observed. A dedicated hermetic test-rig for the experimental investigations on the reduced-scale seal has been designed and built. A modular test section design has been adopted to test different types and sizes of seals. Six different reduced-scale seals, both on cylindrical and conical cross-section, have been investigated experimentally at different inlet boundary conditions with R134a and air. The experimental data for different seals were compared between the predicted results from the developed models as a validation process. Compared to the-state-of the-art models, the authorâs model demonstrates a superior prediction quality in terms of leakage, cavity pressure, and temperature distribution in all test cases. The Hole Pattern Seal (HPS) has been identified as the most effective seal for reduced-scale applications. The experimental data suggests a strong impact of the real gas effects on leakage. Compared to a high degree of superheat the leakage increases by up to 10% for an operation close to the saturation line. The authorâs model shows better prediction quality at different degrees of superheat compared to state-of-the-art models and demonstrates its ability to capture the real gas effect.

EPFL2020

MoDN-Flip: Optimizing Modular Clinical Decision Support Networks with Decision Flippability Score

Kuan Tung

BACKGROUND. Clinical Decision Support Systems (CDSS) are point-of-care questionnaires that guide consultations to evidence-based predictions with the aim of standardizing care and optimizing resource allocation. The data collected in these tools contain potentially useful insights to further train its predictive algorithms, however, the questionnaire structure biases data with systematic missingness, making it unusable in traditional models. Further, privacy and interoperability issues make it challenging to synergize with data collected in related CDSS tools. The Modular Decision Support Network (MoDN) was previously proposed by our group to address these issues. It can predict diagnoses at each step in a consultation using sequentially encoded questions. However, it lacks the ability to provide information on unencoded questions, such as predicting their importance, which could potentially optimize questionnaire structure. AIM. In this work, we aim to optimize MoDN by deriving a flippability score (FS) which computes the importance of a question in the form of how likely its answer would flip (change) the predicted diagnoses. METHODS & FINDINGS. The FS is computed with the help of MoDN’s feature decoders that predict unknown feature values in the data. The optimal questionnaire order is then derived by feeding MoDN the question with the highest FS. This approach—-MoDN-flip—- is validated on two independent real world CDSS-derived data sets of pediatric outpatients. We show that FS-optimized question order can achieve the baseline predictive performance 14.71% faster (or with 3.53 fewer questions) compared to MoDN with the original question order. FS-optimized questionnaires are also able to improve the cumulative F1 score by 5.24%. Furthermore, we test the utility of FS-optimization when porting MoDN to an imperfectly interoperable data set (i.e. with slightly different questionnaire structures and partially-overlapping feature sets). The results show that the score is valid in a new dataset and can provide better predictive performance at an earlier stages, albeit a slight cost to final performance. CONCLUSION. With the aim of providing data-driven questionnaire optimization for CDSS tools, we propose the flippability score, which indicates the importance of each potential question in a consultation. The experimental results show that FS can express predictive importance of questions and has the potential to significantly optimize questionnaire structure. It is now necessary to evaluate this ordering against human consultation logic.

2022

Design and development of the smart machine vision sensor

The Smart Machine Vision Sensor (SMVS) is a self-contained low-cost machine vision system that combines an image sensor, a processing unit and communication interfaces in a single unit. This paper describes the design of the SMVS, the concept of the operating system and the application software. The main characteristics of the SMVS are (1) the absence of an analog video signal and (2) the modular design concept. The signal processing is performed with the processing unit and the output consists either of image analysis results or a compressed digital image data stream. The modular design allows for easy customization for applications that require different sensor technologies, resolutions and spectral sensitivities. The modular design is made possible by the development of a generic sensor-CPU interface. This interface can be used with either CCD or CMOS sensors with a resolution of 512512 pixels. It eliminates the need to redesign the processor board with changing sensor requirements. The SMVS is smaller and cheaper than traditional image processing systems based on desktop personal computers. It uses full-frame, non-interlaced sensors with square pixels to provide an optimal image quality, avoiding the drawbacks of an analog, interlaced video signal with ^Lxed frame rate.

1998

MoDN-Flip: Optimizing Modular Clinical Decision Support Networks with Decision Flippability Score

Kuan Tung

2022

EPFL2020