Coupling of building and vegetation resolving urban microclimate model with a building energy simulation program

posterThe objective of this work is to develop and validate a coupled fast-running Building Energy Modeling/Microclimate model for use in developing site-specific design strategies which minimize energy and water use All the micro-climate variables affecting the building energy consumption, such as solar radiation, long wave radiation, air temperature, wind speed and direction, are taken into account. Differently from previous literature, we propose a fully-dynamic coupling approach, fully surface-specific, coupling EnergyPlus and QES

Doctor of Philosophy

dissertationUrban microclimate has an important impact on the alterations of the local climate in urban and suburban areas. These changes significantly affect pollutant transport, air quality, water and energy consumption, and the general health and comfort of urban residents. Despite extensive research on the computational modeling of urban flows, the integrated impacts of microclimate driving forces (i.e., momentum fluxes, radiative, and turbulent heat fluxes) and major urban infrastructure elements (i.e., buildings' geometrical parameters) have rarely been investigated for complex urban configurations at street-level, neighborhood, and city scales. In this study we used various computational fluid dynamics (CFD) approaches to improve the understanding of momentum and scalar (e.g., particle, energy, and moisture) transport at different time-space scales in street canyons and city districts. We investigated the role of urban layout configurations on flow regimes and transitions, flow patterns, and dominant topological features in street canyons with uneven and single-height buildings. We rigorously analyzed the performance of the CFD methods on predicting and tracking the dynamics of major flow topological features in different flow regimes. At a broader scale, we studied the spatiotemporal characteristics of mean and turbulent momentum and scalar transport and their correlations with the morphological parameters in city districts. Finally, we introduced a high-performance fast-response environmental simulation software for dynamic modeling of mass, momentum and energy exchange processes at city districts during diurnal cycles. We studied the validity of the software for a complex urban area during a full day of field experiment at the University of Utah campus. Our findings showed that urban layout configurations strongly influenced the existence, transition, and spatial variations of the flow features including vortex pairs, secondary vortices, rooftop recirculation zones, saddle points, in-canyon separation points, and wake fields. At broader scales, the urban morphology and surface characteristics altered the spatially-averaged turbulent flow features, particle concentration, and energy transport in city districts and complex urban areas. Overall the results of this study provided beneficial information and computational tools for decision-making studies in urban design, city planning, and building energy analysis

A Parallelization Strategy for the Time Efficient Analysis of Thousands of LC/MS Runs in High-Performance Computing Environment

Combining robust proteomics instrumentation with high-throughput enabling liquid chromatography (LC) systems (e.g., timsTOF Pro and the Evosep One system, respectively) enabled mapping the proteomes of 1000s of samples. Fragpipe is one of the few computational protein identification and quantification frameworks that allows for the time-efficient analysis of such large data sets. However, it requires large amounts of computational power and data storage space that leave even state-of-the-art workstations underpowered when it comes to the analysis of proteomics data sets with 1000s of LC mass spectrometry runs. To address this issue, we developed and optimized a Fragpipe-based analysis strategy for a high-performance computing environment and analyzed 3348 plasma samples (6.4 TB) that were longitudinally collected from hospitalized COVID-19 patients under the auspice of the Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study. Our parallelization strategy reduced the total runtime by ∼90% from 116 (theoretical) days to just 9 days in the high-performance computing environment. All code is open-source and can be deployed in any Simple Linux Utility for Resource Management (SLURM) high-performance computing environment, enabling the analysis of large-scale high-throughput proteomics studies

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC

Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention

IgM N-glycosylation correlates with COVID-19 severity and rate of complement deposition

The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during human acute viral infection. The analysis of IgM N-glycosylation from healthy controls and hospitalized coronavirus disease 2019 (COVID-19) patients reveals increased high-mannose and sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific immunoglobulin N-glycan profiles. Moreover, the degree of total IgM mannosylation and sialylation correlate significantly with markers of disease severity. We link the changes of IgM N-glycosylation with the expression of Golgi glycosyltransferases. Lastly, we observe antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients and modulated by exoglycosidase digestion. Taken together, this work links the IgM N-glycosylation with COVID-19 severity and highlights the need to understand IgM glycosylation and downstream immune function during human disease