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DOE OSTI2021

Metrics for Interzonal Dispersion Assessment of Airborne SARS-CoV-2 Within Office Buildings

High ventilation rate is increasingly considered as a mitigation strategy in the rapid spread of COVID-19 in existing buildings in addition to other options like UVGI and added filtration. However, this and other similar measures may also impact energy use and the efficiency of the buildings in which they are installed. Without concrete metrics, the impact of all these potential changes to the system cannot be properly assessed relative to the other impacts the measures might have, including additional energy use, added operation and maintenance costs, and reduced system life. Multizone airflow and contaminant transport simulations involving parameters such as infiltration rate, system configuration, and level of occupancy can provide critical information on relative risk distribution within a building. In this study, prototype airflow models are used to assess the degree to which ventilation-related measures can mitigate the spread of a virus like SARS-CoV-2 in a similar way that prototype energy models are used to study energy efficiency measures. A new detailed medium-sized office building prototype model is developed using the CONTAM software to represent contaminant transport in buildings like those modeled by the U.S. Department of Energy’s detailed medium office prototype model. The goal of this study is to generate a set of suitable metrics that will give a whole-building picture of airborne SARS-CoV-2 virus distributions across the different zones of the building under different parameters and scenarios.

DeGraw, Jason↗

DOE OSTI2021

Enhanced Beam Diagnostics with Existing BPPMs via GPU-powered Multi-Particle Simulation

This research aims to utilize the multi-particle code, High-Performance Simulator (HPSim), to realistically model the Side-Coupled-Cavity Linac (CCL) lattice of the LANSCE accelerator. This new model would allow us to predict the beam’s bunch length (the longitudinal spread), which is unavailable for individual accelerating modules or only accessible at the end of the linac. However, a correct bunch length is critical for the high-energy beam transport after the CCL. Its impact would be most significant in the Proton Storage Ring (PSR), where we should be able to reduce losses for the circulating beam. The PSR is scheduled to have a 25% current increase for the neutron spallation target upgrade at the Lujan Center. A highly bunched beam would be necessary to reduce the particle losses and lower the radiation levels produced from the ring. A realistic HPSim model with >1M macro-particles can help tackle the beam losses at the sub-percent level. This new work would also create a realistic surrogate model for future machine learning projects.

43 PARTICLE ACCELERATORS↗

NASA NTRS2003

Non-Migrating Diurnal Tides Generated with Planetary Waves in the Mesosphere

We report here the results from a modeling study with our Numerical Spectral Model (NSM) that extends from the ground into thermosphere. The NSM incorporates Hines Doppler Spread Parameterization for small-scale gravity waves (GWs) and describes the major dynamical features of the atmosphere, including the wave driven equatorial oscillations (QBO and SAO), and the seasonal variations of tides and planetary waves. Accounting solely for the solar migrating tidal excitation sources, the NSM generates through dynamical interactions also non-migrating tides in the mesosphere that have amplitudes comparable to those observed. The model produces the diurnal (and semidiurnal) oscillations of the zonal mean (m = 0), and eastward and westward propagating tides for zonal wave numbers m = 1 to 4. To identify the mechanism of excitation for these tides, a numerical experiment is performed. The NSM is run without the heat source for the zonal-mean circulation and temperature variation, and the amplitudes of the resulting nonmigrating tides are then negligibly small. This leads to the conclusion that the planetary waves, which normally are excited in the NSM by instabilities but are suppressed in this case, generate the nonmigrating tides through nonlinear interactions with the migrating tides.

Mayr, H. G.↗

DOE OSTI2012

Connecting Network Properties of Rapidly Disseminating Epizoonotics

Background: To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure. Methods: Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) ‘connectivity’, a model that integrated bio-physical concepts (the agent’s transmission cycle, road topology) into indicators designed to measure networks (‘nodes’ or infected sites with short- and long-range links), and 2) ‘contacts’, which focused on infected individuals but did not assess connectivity. Results: The connectivity model showed five network properties: 1) spatial aggregation of cases (disease clusters), 2) links among similar ‘nodes’ (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a ‘‘20:800 pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads. Conclusions: Geo-temporal constructs of Network Theory’s nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable to revise theory and optimize control measures. Prospective studies that consider pre-outbreak predictors, such as connecting networks, are recommended.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Evaluation of two inoculation routes of an adenovirus-mediated viral protein inhibitor in a Crimean-Congo hemorrhagic fever mouse model

Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne nairovirus with a wide geographic spread that can cause severe and lethal disease. No specific medical countermeasures are approved to combat this illness. The CCHFV L protein contains an ovarian tumor (OTU) domain with a cysteine protease thought to modulate cellular immune responses by removing ubiquitin and ISG15 post-translational modifications from host and viral proteins. Viral deubiquitinases like CCHFV OTU are attractive drug targets, as blocking their activity may enhance cellular immune responses to infection, and potentially inhibit viral replication itself. We previously demonstrated that the engineered ubiquitin variant CC4 is a potent inhibitor of CCHFV replication in vitro. A major challenge of the therapeutic use of small protein inhibitors such as CC4 is their requirement for intracellular delivery, e.g., by viral vectors. In this study, we examined the feasibility of in vivo CC4 delivery by a replication-deficient recombinant adenovirus (Ad-CC4) in a lethal CCHFV mouse model. Since the liver is a primary target of CCHFV infection, we aimed to optimize delivery to this organ by comparing intravenous (tail vein) and intraperitoneal injection of Ad-CC4. While tail vein injection is a traditional route for adenovirus delivery, in our hands intraperitoneal injection resulted in higher and more widespread levels of adenovirus genome in tissues, including, as intended, the liver. However, despite promising in vitro results, neither route of in vivo CC4 treatment resulted in protection from a lethal CCHFV infection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

SU-F-J-199: Predictive Models for Cone Beam CT-Based Online Verification of Pencil Beam Scanning Proton Therapy

Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal and distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Review of "ML for Surface Complexation Model Development"

The presentation given by Jadallah Zouabe on “ML for Surface Complexation Model Development”was extremely informative, but lacked some explanation of details that made the latter half hard to follow as someone outside of the field. He began his presentation with an anecdote to spilling milk or ink on the floor and seeing it spread, cleverly connecting that to the spread of contamination in the real world. He then explained the importance of being able to model contamination, as it allows specialists to see the potential effects on different areas and environments in the coming years. Heal so made it clear that the main issue trying to be addressed here is how expensive modelling is and that their goal is to make computationally cheaper models. The introduction was overall very well formulated and attention-grabbing, but it seemed to take up too much of the presentation time, as after this point the presentation lacked details and explanations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Advanced Instrumentation for Metal Additive Manufacturing

Laser powder bed fusion (LPBF) is the most widely used process for metal additive manufacturing (AM), particularly where complex geometries provide performance advantages unattainable with traditional manufacturing techniques. However, LPBF is highly sensitive to innate variability in both the powder spreading and fusion steps, often leading to defects such as pores that are difficult to detect yet significantly impair component mechanical properties and fatigue life. This thesis presents a range of novel instruments enabling both precise assessment of powder layer characteristics and in-situ thermal metrology of metal AM to advance the quality control of LPBF. First, leveraging a custom X-ray microscope and a radiation-transport model developed through this work, transmission X-ray imaging is used to study spreading of thin metal powder layers. Effective layer depth is directly mapped at a process-relevant size scale, surpassing optical techniques that can only estimate local deposition from layer surface topography. Layer packing density and quality are shown to be influenced by powder flowability and particle size relative to nominal powder layer thickness. Layer quality is additionally connected to the geometry of the spreading implement and its velocity. This technique and its presented findings enable pairing feedstocks with spreading strategies that create layers with consistent packing density and uniformity. Second, a twofold approach is employed to optically interrogate the laser fusion step of LPBF for observing signatures of defect formation. Aperture division multiplexing is conceptualized, providing for simultaneous laser delivery and high-fidelity infrared (IR) process monitoring through a common optic. In-situ microscopy at 50 μm spatial resolution and at mid-wave IR wavelengths is proven readily achievable with the first purpose-built optic of this type. Next, a bespoke imaging spectrometer, along with a temperature-emissivity separation technique, is used to retrieve accurate process temperatures over a 1000 K range. Data from these instruments are correlated to porosity as fine as 4.3 μm in two LPBF test artifacts, as verified using computed tomography (CT), establishing the viability of robust optically-based component qualification.

Penny, Ryan↗

DOE OSTI2020

Evaporation Sub-model Development for Volume of Fluid (eVOF) Method Applicable to Spray-Wall Interaction Including Film Characteristics with Validation at High Pressure and Temperature Conditions (Final Report)

Internal combustion engines have seen a great evolution over the last several decades through application of high pressure direct injection, multiple injections, and other technologies to reduced fuel consumption, NOx, and PM. Although combustion systems with advanced injection strategies have been studied extensively, there exists a significant fundamental knowledge gap on the fuel-spray interactions with the piston surface and chamber walls. Advanced computational codes validated with experimental techniques have to be developed for accurate representation of the drop impingement, fuel film formation, and vaporization. Current engine CFD spray models utilize a Lagrangian framework for modeling which lacks critical considerations of the physics pertaining to these interactions and thus requiring extensive parameterization, tuning and validation. The team from Michigan Technological University, University of Massachusetts Dartmouth, and Argonne National Laboratory is composed of experts in sprays, combustion, engines and CFD with a wide spectrum of knowledge including specific expertise in the area under consideration. In the proposed work, a VOF modeling approach has been adopted for the spray-wall interaction, film formation and spreading, and vaporization. With the inclusion of a vaporization submodel, a more predictive and accurate simulation of the spray-film was performed without extensive need of parameterization and tuning. Extensive experimentation of the spray-wall interaction under the range of conditions matching the thermodynamic and surface temperatures that occur in diesel and gasoline engines were conducted to validate the SWI submodels and for development of the evaporation sub-model, which has been implemented in the Converge software.

42 ENGINEERING↗

DOE OSTI2025

Widening of Wind Stress Anomalies Amplifies ENSO in a Warming Climate

Abstract Climate change simulations generally indicate the strengthening of El Niño–Southern Oscillation (ENSO) sea surface temperature (SST) variability through the twenty-first century, yet a robust physical mechanism explaining this change across different models is still lacking, and the projections for ENSO amplitude exhibit a large spread. Most commonly, changes in the background state of the tropical Pacific are invoked to explain these changes of ENSO. Here, we show that changes in the structure of wind stress anomalies associated with ENSO are potentially as important as these background state changes. Specifically, changes in the magnitude, meridional width, and zonal structure of wind stress anomalies can explain approximately 53% of the intermodel variance in the projected change of ENSO magnitude through the twenty-first century as well as 43% in ENSO periodicity changes. Among these changes in the wind structure, the meridional widening of wind anomalies plays the most important role. To demonstrate that these changes are indeed critical, we develop a hybrid model of ENSO based on the Community Earth System Model, version 2, which incorporates a dynamical ocean coupled to a simplified statistical atmosphere within the tropical Pacific. In the absence of external forcing and corresponding mean-state changes, the imposed changes in wind stress anomalies in this hybrid model result in an increase of ENSO amplitudes of nearly 10% along the equator. Our results are also theoretically supported by a recharge-oscillator model that incorporates the meridional wind structure. Thus, changes in the structure of wind stress anomalies, together with changes in the mean state, likely play a critical role in the projected strengthening of ENSO.

Stuivenvolt-Allen, Jacob [Yale University, New Hav↗

DOE OSTI2022

The role of geographical spreaders in infectious pattern formation and front propagation speeds

The pattern formation and spatial spread of infectious populations are investigated using a kernel-based Susceptible–Infectious–Recovered (SIR) model applicable across a wide range of basic reproduction numbers R O . The goal is to examine the role of geographical spreaders on transient spatial pattern formation of infectious populations and the associated maximum invasive front speeds c max . In the simulations conducted here, geographical spreaders are defined as a portion of the infected population Φ experiencing high mobility between identical communities. The spatial organization of the infected population and c max are determined when the infections are randomly initiated in space within multiple communities. For small but finite , scaling analysis and numerical simulations in 1-dimension suggest that when the spreading kernel is Gaussian-shaped, where is the inverse of the infectious duration. This finding for agrees with a diffusion-based representation of mobility in 1-D. Numerical simulations in 2-D across wide-ranging suggest that , the variance of the spatial kernel describing mobility of long-distance geographical spreaders across communities, determines the spatial organization of infections across communities. When (long-distance mobility, where is the minimum spatial extent defining adjacent communities), the infectious population will experience a transient but spatially coherent pattern with a wavelength that can be derived from the spreading kernel properties. Moreover, the 2-D simulations for the bounded kernel suggest that attainment of is also dictated by but the magnitude is not sensitive to unlike diffusion-based models.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Control and Cost-benefit Analysis of Fast Spreading Diseases: The case of Ebola

Mitigating the spread of infectious disease is of great importance for policy makers. Taking the recent outbreak of Ebola as an example, it was difficult for policy makers to identify the best course of action based on the cost-effectiveness of what was available. In effort to address the needs of policy makers to mitigate the spread of infectious disease before an outbreak becomes uncontrollable, we have devised a cost-benefit disease control model to simulate the effect of various control methods on disease incidence and the cost associated with each of the scenarios. Here, we present a case study of Ebola used to quantify the cost effectiveness of vaccination and isolation methods to minimize the spread of the disease. We evaluate the impact of changing strategy levels on the incidence of the disease and address the benefits of choosing one strategy over the other with regards to cost of vaccine and isolation. Disease. We use a general SEIRJ model for disease transmission. Here, S-Susceptible, E- Exposed (latent), IA– Infected (asymptomatic),IM– Infected (mild symptoms), IS– Infected (severe symptoms),JM– Isolated (mild symptoms at home), JS– Isolated (severe symptoms in hospital), and R- Recovered individuals. In this model, we consider the dynamics of the system and the effect of the relative transmissibility of isolated individuals (L) compared to other infected individuals. Cost. Ebola vaccination and treatment are very expensive and not widely available. Some preliminary data shows that it will take$73 million (M) to produce 27 M vaccines plus the cost for vaccine delivery and health care professionals (not included here). On the other hand, the treatment for Ebola in the U.S. would cost $25,000dollars a day per person to ensure proper isolation and adequate care(treatment, health care professionals, facilities and special equipment).Although not included in this research, the proper isolation of Ebola patients would also lead to a loss in hospital revenue of $148,000per day due to reduced patient capacity3. Here, we use $27,000 per individual hospitalized per day and $2.70 per person vaccinated. Model. To evaluate the cost-effectiveness of control methods on disease transmission, we assessed the affect of different levels of vaccination coverage on the resulting number of infected individuals. Then, we calculated the overall estimated cost of vaccination and resulting hospitalization for each scenario to identify the lowest cost-benefit ratio. Using a base population of 10 M individuals, we ran scenarios for different levels of vaccination (μ= 0.01, 0.05, 0.1) while varying the relative transmissibility of isolated individuals (L = 0.5, 0.6, 0.65).For each combination, we calculated the incidence, vaccination and hospitalization cost per individual per day (Fig 1). We note that an increase in the relative transmissibility of isolated individuals leads to a higher number of infected people and, therefore, a reduced number of candidates for vaccination and an overall increase in cost. Since the cost of vaccination is 1 ten-thousandth of the cost of hospitalization, our results clearly show the cost-benefit of vaccinating over hospital treatment. In every scenario studied, we observed a measurable reduction in disease incidence when vaccinating a higher fraction of the population compared to isolating individuals post infection. Given these preliminary results, we plan to extend the framework of our model to a dynamic control system where we consider the cost of vaccination and isolation embedded in the system of differential equations. This approach will allow us see the best available control implementation while minimizing the cost of treatment and vaccination.

EBOLA↗

DOE OSTI2020

Superdiffusive transport of energy in one-dimensional metals

Metals in one spatial dimension are described at the lowest energy scales by the Luttinger liquid theory. It is well understood that this free theory, and even interacting integrable models, can support ballistic transport of conserved quantities including energy. In contrast, realistic one-dimensional metals, even without disorder, contain integrability-breaking interactions that are expected to lead to thermalization and conventional diffusive linear response. We argue that the expansion of energy when such a nonintegrable Luttinger liquid is locally heated above its ground state shows superdiffusive behavior (i.e., spreading of energy that is intermediate between diffusion and ballistic propagation), by combining an analytical anomalous diffusion model with numerical matrix-product–state calculations on a specific perturbed spinless fermion chain. Different metals will have different scaling exponents and shapes in their energy spreading, but the superdiffusive behavior is stable and should be visible in time-resolved experiments.

Bulchandani, Vir B.↗

DOE OSTI2018

An Experimental and Computational Study of a Single Diesel Droplet Impinging on a Dry Surface

This work presents experiments and computational simulations of a single diesel droplet impinging on a dry surface to provide a better understanding of the dynamics of the impingement process. The experimental work was carried out at several substrate surface temperatures where a single diesel droplet was dropped from a precision syringe pump to provide a specific droplet diameter and impact velocity. The effect of the surface temperature on the temporal evolution of the droplet spreading factor, dynamic contact angle, and contact line velocity was studied. The experimental study on the temporal evolution of the droplet-wall interaction was used to develop a dynamic contact angle model for computational simulations. Using an in-house multiphase flow solver, simulations of the single diesel droplet impingement were performed. The simulation results of the spreading factor were compared to the experimental results and the effects of liquid temperature and contact angle model parameters were investigated. The development of a dynamic contact angle model for diesel droplets enhances the ability to study diesel droplet impingement, an important factor in diesel fuel injection. With an accurate dynamic contact angle model, future studies can be performed at scales and velocities representative of the conditions present in internal combustion engines.

Markt, D.↗

DOE OSTI2025

Quantification of regional net CO 2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements

Inverse model intercomparison projects (MIPs) provide a chance to assess the uncertainties in inversion estimates arising from various sources. However, accurately quantifying ensemble CO 2 flux errors remains challenging and often relies on the ensemble spread. This study proposes a method for quantifying the errors in regional net surface–atmosphere CO 2 flux estimates from models taken from the Orbiting Carbon Observatory-2 (OCO-2) v10 MIP by using independent airborne CO 2 measurements for the period 2015–2017. We first calculate the root mean square error (RMSE) between the ensemble mean of posterior CO 2 concentrations and airborne observations and then isolate the CO 2 concentration errors caused solely by the ensemble mean of posterior net fluxes by subtracting the observation, representation, and transport errors from seven regions. Our analysis reveals that the flux errors projected onto CO 2 space account for 55 %–85 % of the regional average RMSE over the 3 years, ranging from 0.88 to 1.91 ppm. In five regions, the error estimates based on observations exceed those computed from the ensemble spread of posterior fluxes by a factor of 1.33–1.93, implying an underestimation of the actual flux errors, while their magnitudes are comparable in two regions. The adjoint sensitivity analysis identifies that the underestimation of flux errors is prominent where the magnitudes of fossil fuel emissions exceed those of terrestrial-biosphere fluxes by a factor of 3–31 over the 3 years. This suggests the presence of systematic biases in the inversion estimates associated with errors in the prescribed fossil fuel emissions common to all models. Our study emphasizes the value of airborne measurements for quantifying regional errors in ensemble net CO 2 flux estimates.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Mesosphere Dynamics with Gravity Wave Forcing: Planetary Waves - 2

We present results from a non-linear, 3D, time dependent numerical spectral model (NSM) which extends from the ground up into the thermosphere and incorporates Hines' Doppler Spread Parameterization for small-scale gravity waves (GW). Our focal point is the mesosphere where wave interactions are playing a dominant role. We discuss planetary waves in the present paper and diurnal and semi-diurnal tides in the companion paper. Without external time dependent energy or momentum sources, planetary waves (PWs) are generated in the model for zonal wavenumbers 1 to 4, which have amplitudes in the mesosphere above 50 km as large as 30 m/s and periods between 2 and 50 days. The waves are generated primarily during solstice conditions, which indicates that the baroclinic instability (associated with the GW driven reversal in the latitudinal temperature gradient) is playing an important role. Results from a numerical experiment show that GWs are also involved directly in generating the PWs. For the zonal wavenumber m = 1, the predominant wave periods in summer are around 4 days and in winter between 6 and 10 days. For m = 2, the periods are in summer and close to 2.5 and 3.5 days respectively For m = 3, 4 the predominant wave periods are in both seasons close to two days. The latter waves have the characteristics of Rossby gravity waves with meridional winds at equatorial latitudes. A common feature of the PWs (m = 1 to 4) generated in summer and winter is that their vertical wavelengths throughout the mesosphere are large which indicates that the waves are not propagating freely but are generated throughout the region. Another common feature is that the PWs propagate preferentially westward in summer and eastward in winter, being launched from the westward and eastward zonal winds that prevail respectively in summer and winter altitudes below 80 km. During spring and fall, for m = 1 and 2 eastward propagating long period PWs are generated that are launched from the smaller eastward zonal winds that prevail in these seasons. PWs generated in the model produce large amplitude modulations of the diurnal tides at altitudes above 80 km and contribute to their seasonal variations.

Mayr, H. G.↗

DOE OSTI2014

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m –2 and 100 W m –2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. In conclusion, validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

17 WIND ENERGY↗