Numerical modelling of radiative heat transfer in a polydispersion of ceramic particles under direct high-flux solar irradiation

The effects of polydispersity on radiative and interfacial convective heat transfer are investigated in particle–gas two-phase media for solar particle receiver applications. Non-grey radiative transfer is analysed using the collision-based Monte Carlo ray-tracing method. The Mie theory is employed to calculate radiative properties of particles. The finite volume method and the explicit Euler time integration scheme are used to solve the transient energy equations for the particle and gas phases. Three alternative approaches to modelling particle properties and thermal conditions are employed: (i) a novel discrete size model, in which particle groups within discrete size intervals are assigned individual properties and temperatures locally; (ii) a lumped size model, in which integral properties and a single temperature are assigned to the particle phase locally; and (iii) a monodisperse size model, in which properties are evaluated for the Sauter mean diameter of the polydispersion and a single temperature is assigned to the particle phase locally. Strongly size-dependent radiation absorption and interfacial convective heat transfer are predicted with the discrete size model for alumina particles. Particles smaller than 27.4μm located near the aperture absorb the solar irradiation and transfer heat to the gas phase most effectively. The angular spread of the incident solar radiation is found to have a negligible effect on the overall absorption, although the most uniform thermal conditions occur for the solar irradiation with the smallest confinement angle. The overall absorptance of alumina particles is higher by 3.4% and 2.7% than that of iron (III) oxide and mullite particles, respectively. The lumped and monodisperse size models allow for reduction of the computational time at the expense of lower accuracy and limited information about particle properties and thermal conditions. © 2021 The Author(s

Waypoint Planning for Autonomous Aerial Inspection of Large-Scale Solar Farms

Solar energy is seen as a sustainable and nondepletable source of energy supply. Worldwide, large-scale solar power infrastructure is being installed every day. Such structures can suffer from many faults and defects that degrade their energy output during their operational life. Detecting such faults and defects requires regular inspection over physically large and distributed solar infrastructure. On-site manual human inspection tends to be impractical, risky and costly. As such, replacing humans with autonomous robotic aerial inspection systems has great potential. In this work, we propose an unmanned aerial vehicle (UAV) waypoint generation system that is specifically designed for aerial inspection of solar infrastructure. Our system takes into consideration the physical structure and the dynamic nature of sun-tracking solar modules and generates waypoints with the right camera viewing pose and drone orientation. Statistical methods are used to generate a randomly selected set of modules as a representation of the entire solar farm. The set is guaranteed to satisfy a user-defined confidence level and margin of error requirements. A path is generated to visit selected modules in an optimal way by deploying the traveling-salesman shortest path algorithm, allowing the vehicle to maximize battery use. Illustrative flights and preliminary inspection results are presented and discussed.This research was supported by the Australian Renewable Energy Agency (ARENA), through Grant G00853 “A robotic vision system for rapid inspection and evaluation of solar plant infrastructure”

Optical and Thermal Performance of Bladed Receivers

Bladed receivers use conventional receiver tube-banks rearranged into bladed/finned structures, and offer better light trapping, reduced radiative and convective losses, and reduced tube mass, based on the presented optical and thermal analysis. Optimising for optical performance, deep blades emerge. Considering thermal losses leads to shallower blades. Horizontal blades perform better, in both windy and no-wind conditions, than vertical blades, at the scales considered so far. Air curtains offer options to further reduce convective losses; high flux on blade-tips is still a concern.This work was is supported by the Australian Renewable Energy Agency, grant 2014/RND010. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Population- and individual-specific regulatory variation in Sardinia

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.M.P. is supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement 633964 (ImmunoAgeing). Z.Z. is supported by the National Science Foundation (NSF) GRFP (DGE- 114747) and by the Stanford Center for Computational, Evolutionary, and Human Genomics (CEHG). Z.Z., J.R.D., and G.T.H. also acknowledge support from the Stanford Genome Training Program (SGTP; NIH/NHGRI T32HG000044). J.R.D. is supported by the Stanford Graduate Fellowship. K.R.K. is supported by Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEQ) Fellowship 32 CFR 168a. S.J.S. is supported by the NIHR Cambridge Biomedical Research Centre. The SardiNIA project is supported in part by the intramural program of the National Institute on Aging through contract HHSN271201100005C to the Consiglio Nazionale delle Ricerche of Italy. The RNA sequencing was supported by the PB05 InterOmics MIUR Flagship grant; by the FaReBio2011 “Farmaci e Reti Biotecnologiche di Qualità” grant; and by Sardinian Autonomous Region (L.R. no. 7/2009) grant cRP3-154 to F. Cucca, who is also supported by the Italian Foundation for Multiple Sclerosis (FISM 2015/R/09) and by the Fondazione di Sardegna (ex Fondazione Banco di Sardegna, Prot. U1301.2015/AI.1157.BE Prat. 2015-1651). S.B.M. is supported by the US National Institutes of Health through R01HG008150, R01MH101814, U01HG007436, and U01HG009080. All of the authors would like to thank the CRS4 and the SCGPM for the computational infrastructure supporting this project

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Dish systems for CSP

Parabolic dish technology, for concentrating solar power (CSP) applications, has been continuously modified and improved since the pioneering work in the 1970s. Best practice dishes now have features such as lightweight structure, balanced design, high-quality, low-cost mirror panels, and can be deployed rapidly with little in-field labour. This review focuses on the evolution of dish design, by examining features such as mode of tracking, structure and mirror design, for a wide selection of CSP dish examples. The review includes a brief summary of power generation options – both on-dish and central plant – as well as a discussion about options for storage and hybridisationThis work was supported by the Australian Solar Thermal Research Initiative (ASTRI), a project supported by the Australian Government, through the Australian Renewable Energy Agency (ARENA). Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed martin Corporation, for the U.S. Department of Energy’s national Nuclear Security Administration under contract DE-AC04-94AL85000

Exergy analysis of the focal-plane flux distribution of solar-thermal concentrators

As concentrating solar power systems push towards higher temperatures and lower costs, it is critical that losses of overall system performance can be attributed correctly to the appropriate source. Up to now, this has been poorly done for the case of optical errors, since applicable methods do not exist to quantify how much different imperfections contribute to reducing the upper-bound efficiency of the overall system. Here, the exergy impact of varied optical design parameters—slope error, rim angle, mirror reflectance and sun-shape—is calculated for the first time. Slope error is shown to have the strongest impact. Also, dishes with rim angles significantly wider than the conventional 45° are shown to yield the best overall energy conversion. The resulting analysis method, broadly applicable in concentrating solar power, enables a new approach to quantitative optical system design.This work was conducted as part of the Australian Solar Thermal Research Initiative (ASTRI) program, supported by the Australian Government through the Australian Renewable Energy Agency (ARENA). The Australian Government, through ARENA, is supporting Australian research and development in solar photovoltaic and solar thermal technologies to help solar power become cost competitive with other energy sources