22 research outputs found
Using data from monitoring combined sewer overflows to assess, improve, and maintain combined sewer systems
Using low-cost sensors, data can be collected on the occurrence and duration of overflows in each combined sewer overflow (CSO) structure in a combined sewer system (CSS). The collection and analysis of real data can be used to assess, improve, and maintain CSSs in order to reduce the number and impact of overflows. The objective of this study was to develop a methodology to evaluate the performance of CSSs using low-cost monitoring. This methodology includes (1) assessing the capacity of a CSS using overflow duration and rain volume data, (2) characterizing the performance of CSO structures with statistics, (3) evaluating the compliance of a CSS with government guidelines, and (4) generating decision tree models to provide support to managers for making decisions about system maintenance. The methodology is demonstrated with a case study of a CSS in La Garriga, Spain. The rain volume breaking point from which CSO structures started to overflow ranged from 0.6. mm to 2.8. mm. The structures with the best and worst performance in terms of overflow (overflow probability, order, duration and CSO ranking) were characterized. Most of the obtained decision trees to predict overflows from rain data had accuracies ranging from 70% to 83%. The results obtained from the proposed methodology can greatly support managers and engineers dealing with real-world problems, improvements, and maintenance of CSSsSupport for this project was provided by the ENDERUS Project (CTM-2009-13018) and the predoctoral grant FPI BES-2010-039247, founded by the Spanish Ministry of Science and Innovation. Lluís Corominas received the postdoctoral Juan de la Cierva grant (JCI-2009-05604) from the Government of Spain and the Career Integration Grant (PCIG9-GA-2011-293535) from the EU. The authors also acknowledge the support from the Economy and Knowledge Department of the Catalan Government through the Consolidated Research Group (2014 SGR 291)–Catalan Institute for Water Researc
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A Framework for the Design of Biomimetic Cellular Materials for Additive Manufacturing
Cellular materials such as honeycombs and lattices are an important area of research in
Additive Manufacturing due to their ability to improve functionality and performance. While there
are several design choices when selecting a unit cell, it is not always apparent what the optimum
cellular design for a particular application is. This becomes particularly challenging when seeking
an optimal design for more than one function, or when the design needs to transition spatially
between different functions. Nature abounds with examples of cellular materials that are able to
achieve multifunctionality, but designers lack the ability to translate the underlying principles in
these examples to their design tools. In this work, we propose a framework to bridge the gap
between nature and designer. We present a classification of natural cellular materials based on
their structure and function, and relate them in a manner amenable for use in guiding design for
Additive Manufacturing.Mechanical Engineerin