In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand the in silico toolbox.

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Experimental and Numerical Study of a Microcogeneration Stirling Unit under On–Off Cycling Operation

Energies ◽

10.3390/en14040801 ◽

2021 ◽

Vol 14 (4) ◽

pp. 801

Author(s):

Gianluca Valenti ◽

Aldo Bischi ◽

Stefano Campanari ◽

Paolo Silva ◽

Antonino Ravidà ◽

...

Keyword(s):

Numerical Study ◽

Thermal Storage ◽

Primary Energy ◽

Operational Cost ◽

Cogeneration Plant ◽

Economic Optimization ◽

Viable Option ◽

Heating Value ◽

Energy Flows

Stirling units are a viable option for micro-cogeneration applications, but they operate often with multiple daily startups and shutdowns due to the variability of load profiles. This work focused on the experimental and numerical study of a small-size commercial Stirling unit when subjected to cycling operations. First, experimental data about energy flows and emissions were collected during on–off operations. Second, these data were utilized to tune an in-house code for the economic optimization of cogeneration plant scheduling. Lastly, the tuned code was applied to a case study of a residential flat in Northern Italy during a typical winter day to investigate the optimal scheduling of the Stirling unit equipped with a thermal storage tank of diverse sizes. Experimentally, the Stirling unit showed an integrated electric efficiency of 8.9% (8.0%) and thermal efficiency of 91.0% (82.2%), referred to as the fuel lower and, between parenthesis, higher heating value during the on–off cycling test, while emissions showed peaks in NOx and CO up to 100 ppm but shorter than a minute. Numerically, predictions indicated that considering the on–off effects, the optimized operating strategy led to a great reduction of daily startups, with a number lower than 10 per day due to an optimal thermal storage size of 4 kWh. Ultimately, the primary energy saving was 12% and the daily operational cost was 2.9 €/day.

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