The NVBL Viral Fate and Transport Team includes researchers from eleven DOE national laboratories and is utilizing unique experimental facilities combined with physics-based and data-driven modeling and simulation to study the transmission, transport, and fate of SARSCoV-2. The team was focused on understanding and ultimately predicting SARS-CoV-2 viability in varied environments with the goal of rapidly informing strategies that guide the nation’s resumption of normal activities. The primary goals of this project include prioritizing administrative and engineering controls that reduce the risk of SARS-CoV-2 transmission within an enclosed environment; identifying the chemical and physical properties that influence binding of SARS-CoV-2 to common surfaces; and understanding the contribution of environmental reservoirs and conditions on transmission and resurgence of SARS-CoV-2.
High-temperature particle receivers are being pursued to enable next-generation concentrating solar thermal power (CSP) systems that can achieve higher temperatures (> 700 °C) to enable more efficient power cycles, lower overall system costs, and emerging CSP-based process-heat applications. The objective of this work was to develop characterization methods to quantify the particle and heat losses from the open aperture of the particle receiver. Novel camera- based imaging methods were developed and applied to both laboratory-scale and larger 1 MWt on-sun tests at the National Solar Thermal Test Facility in Albuquerque, New Mexico. Validation of the imaging methods was performed using gravimetric and calorimetric methods. In addition, conventional particle-sampling methods using volumetric particle-air samplers were applied to the on-sun tests to compare particle emission rates with regulatory standards for worker safety and pollution. Novel particle sampling methods using 3-D printed tipping buckets and tethered balloons were also developed and applied to the on-sun particle-receiver tests. Finally, models were developed to simulate the impact of particle size and wind on particle emissions and concentrations as a function of location. Results showed that particle emissions and concentrations were well below regulatory standards for worker safety and pollution. In addition, estimated particle temperatures and advective heat losses from the camera-based imaging methods correlated well with measured values during the on-sun tests.
An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g., airflow/ventilation), and face coverings. The CFD results were combined with infectivity models to determine probability of infection, which is a function of the spatial-temporal aerosol concentrations, viral load, infectivity rate, viral viability, lung-deposition probability, and inhalation rate. Uncertainty distributions were determined for these parameters from the literature. Probabilistic analyses were performed to determine cumulative distributions of infection probabilities and to determine the most important parameters impacting transmission. This modeling approach has relevance to both pathogen and pollutant dispersion from expelled aerosol plumes.
High-temperature falling particle receivers are being investigated for next-generation concentrating solar power applications. Small sand-like particles are released into an open-cavity receiver and are irradiated by concentrated sunlight from a field of heliostats. The particles are heated to temperatures over 700 °C and can be stored to produce heat for electricity generation or industrial applications when needed. As the particles fall through the receiver, particles and particulate fragments in the form of aerosolized dust can be emitted from the aperture, which can lower thermal efficiency, increase costs of particle replacement, and pose a particulate matter (PM) inhalation risk. This paper describes sampling methods that were deployed during on-sun tests to record nearfield (several meters) and far-field (tens to hundreds of meters) concentrations of aerosol particles within emitted plumes. The objective was to quantify the particulate emission rates and loss from the falling particle receiver in relation to OSHA and EPA National Ambient Air Quality Standards (NAAQS). Near-field instrumentation placed on the platform in proximity to the receiver aperture included several real-time aerosol size distribution and concentration measurement techniques, including a TSI Aerodynamic Particle Sizers (APS), TSI DustTraks, Handix Portable Optical Particle Spectrometers (POPS), Alphasense Optical Particle Counters (OPC), TSI Condensation Particle Counters (CPC), Cascade Particle Impactors, 3D-printed prototype tipping buckets, and meteorological instrumentation. Far-field particle sampling techniques utilized multiple tethered balloons located upwind and downwind of the particle receiver to measure the advected plume concentrations using a suite of airborne aerosol and meteorological instruments including POPS, CPCs, OPCs and cascade impactors. The combined aerosol size distribution for all these instruments spanned particle sizes from 0.02 μm - 500 μm. Results showed a strong influence of wind direction on particle emissions and concentration, with preliminary results showing representative concentrations below both the OSHA and NAAQS standards.
This paper describes a terrestrial thermocline storage system comprised of inexpensive rock, gravel, and/or sand-like materials to store high-temperature heat for days to months. The present system seeks to overcome past challenges of thermocline storage (cost and performance) by utilizing a confined radialbased thermocline storage system that can better control the flow and temperature distribution in a bed of porous materials with one or more layers or zones of different particle sizes, materials, and injection/extraction wells. Air is used as the heat-transfer fluid, and the storage bed can be heated or "trickle charged"by flowing hot air through multiple wells during periods of low electricity demand using electrical heating or heat from a solar thermal plant. This terrestrial-based storage system can provide low-cost, large-capacity energy storage for both high- (∼400- 800°C) and low- (∼100-400°C) temperature applications. Bench-scale experiments were conducted, and computational fluid dynamics (CFD) simulations were performed to verify models and improve understanding of relevant features and processes that impact the performance of the radial thermocline storage system. Sensitivity studies were performed using the CFD model to investigate the impact o f the air flow rate, porosity, particle thermal conductivity, and air-to-particle heattransfer coefficient on temperature profiles. A preliminary technoeconomic analysis was also performed to estimate the levelized cost of storage for different storage durations and discharging scenarios.
Computational fluid dynamics (CFD) modelling was performed to simulate spatial and temporal airborne pathogen concentrations during an observed COVID-19 outbreak in a restaurant in Guangzhou, China. The reported seating configuration, overlap durations, room ventilation, layout, and dimensions were modelled in the CFD simulations to determine relative exposures and probabilities of infection. Results showed that the trends in the simulated probabilities of infection were consistent with the observed rates of infection at each of the tables surrounding the index patient. Alternative configurations that investigated different boundary conditions and ventilation conditions were also simulated. Increasing the fresh-air percentage to 10%, 50%, and 100% of the supply air reduced the accumulated pathogen mass in the room by an average of ∼30%, ∼70%, and ∼80%, respectively, over 73 min. The probability of infection was reduced by ∼10%, 40%, and 50%, respectively. Highlights: Computational fluid dynamics (CFD) models used to simulate pathogen concentrations Infection model developed using spatial and temporal CFD results Simulating spatial variability was important to match observed infection rates Recirculation increased exposures and probability of infection Increased fresh-air ventilation decreased exposures and probability of infection.