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This presentation was given at the third Wind Energy Systems Engineering Workshop in Boulder, Colorado, and focused on wind plant controls research, combined optimization, a case study on the Princess Amalia Wind Park, results from the case study, and future work.
The 2014 annual tutorial for the Community Earth System Model (CESM) was held on August 11-August 15, 2014 at the National Center for Atmospheric Research in Boulder, CO. It included lectures and practical sessions on numerous aspects of the CESM model. The proceedings submitted here include a description of the tutorial.
In March and April of 2015, the ARM Doppler lidar that was formerly operated at the Tropical Western Pacific site in Darwin, Australia (S/N 0710-08) was deployed to the Boulder Atmospheric Observatory (BAO) for the eXperimental Planetary boundary-layer Instrument Assessment (XPIA) field campaign. The goal of the XPIA field campaign was to investigate methods of using multiple Doppler lidars to obtain high-resolution three-dimensional measurements of winds and turbulence in the atmospheric boundary layer, and to characterize the uncertainties in these measurements. The ARM Doppler lidar was one of many Doppler lidar systems that participated in this study. During XPIA the 300-m tower at the BAO site was instrumented with well-calibrated sonic anemometers at six levels. These sonic anemometers provided highly accurate reference measurements against which the lidars could be compared. Thus, the deployment of the ARM Doppler lidar during XPIA offered a rare opportunity for the ARM program to characterize the uncertainties in their lidar wind measurements. Results of the lidar-tower comparison indicate that the lidar wind speed measurements are essentially unbiased (~1cm s-1), with a random error of approximately 50 cm s-1. Two methods of uncertainty estimation were tested. The first method was found to produce uncertainties that were too low. The second method produced estimates that were more accurate and better indicators of data quality. As of December 2015, the first method is being used by the ARM Doppler lidar wind value-added product (VAP). One outcome of this work will be to update this VAP to use the second method for uncertainty estimation.
Within the wind energy community, it has become increasingly important to simulate realistic weather events at high fidelity in order to improve wind turbine design, wind farm efficiency, and power forecasting. One of the major difficulties in simulating atmospheric events with numerical models at high fidelity is in accurately transitioning from the mesoscale to the microscale. The mesoscale flow, when input into the large-eddy simulation (LES) domain, will be free of resolved turbulence; needing sufficient time and space (known as fetch) for resolved-scale turbulence to develop. In order to reduce this fetch, several methods exist in which the temperature field, wind field, or both, are stochastically perturbed in order to accelerate the generation of turbulence. However, for cases involving complex terrain, it remains unclear if these perturbation processes are necessary, and if the interaction of the flow over the terrain, alone, is sufficient to generate adequate turbulence. In this study, a wind ramp event observed at the National Wind Technology Center (NWTC) outside of Boulder, CO is simulated first with a mesoscale model and then, using the simulated mesoscale solution as initial and boundary conditions, within a microscale LES solver. The mesoscale solution generated by the Weather Research and Forecasting (WRF) model accurately captures the wind ramp event with only a slight temporal shift and a small temperature bias when compared to the meteorological towers in the NWTC site. This information is then taken as the initial and boundary conditions within the Simulator for Wind Farm Applications (SOWFA) microscale LES model with varying terrain inputs. These inputs include the high-resolution (roughly 30 m grid spacing) terrain data from the Shuttle Radar Topography Mission (SRTM) (Figure 1a), as well as, three intermediate terrain resolution data sets produced by applying a uniform convolution window to the SRTM data with varying window sizes (Figure 1b-d). These are compared to the WRF terrain data interpolated to the high-resolution microscale grid (Figure 1e) in order to determine the impact of low-resolution (about 1 km grid spacing) terrain data on turbulence generation. The wind field is compared at several heights and distances along the dominant wind flow axis between each of the terrain cases. It is found that the development of turbulence across the domain is accelerated as terrain information increases in fidelity. Further, because this ramp event at the location of interest is largely influenced by the interaction of the short-wave trough with the terrain, as the topographic information decreases in fidelity the accuracy of the ramp event is decreased. To make generalizations and describe the benefits and shortcomings of this approach, several of the existing perturbation techniques are employed and compared to that of turbulence generation through topographic features.
The OSIRIS-REx mission will provide invaluable ground-truth validation for the computer models in a case study that set out to determine the timeframe within which we must launch either a kinetic impactor or a nuclear explosive carrier and develop a conceptual design for that spacecraft. From the on-asteroid data gathered when the spacecraft touches down and, eventually, from hands-on research here on Earth, we will get a reality check for what we think we know about Bennu’s material composition (boulders, chunks, and dust), shape, mass, density, and so on. Gravimetric data could reveal whether the asteroid is hollow. Back on Earth, researchers will run various tests on the material. We may have enough information to develop a theoretical equation of state. We could then compare it to its closest match in SESAME, the Los Alamos database of equations of state. Armed with that data, we will rerun the models to see how much each scenario changes. Comparing data from the touchdown and sample return to the earlier, remotely observed data from Bennu will help us calibrate remote observations of other objects in the future. Then we can more precisely model the effects of our deflection and disruption strategies and refine the spacecraft design.
Wind plant performance depends on local environmental conditions—and understanding those conditions is crucial to research on wind plant dynamics. Factors such as sloping terrain, surface type and cover, atmospheric heating and cooling, and weather events all play a role in determining the winds that turbines convert into power. However, most models used for wind plant design and operation do not sufficiently account for environmental effects. This can limit our understanding of wind plant dynamics and, thus, our ability to design, site, and operate wind plants for maximum power production and reliability. To meet this challenge, Arthur and other LLNL researchers partnered with scientists at the National Center for Atmospheric Research; the University of California, Berkeley; the University of Colorado, Boulder; and Texas Tech University to develop and demonstrate a novel, mesoscale-tomicroscale wind plant modeling framework.
The open source aeroservoelastic wind turbine solver, OpenFAST, now includes an aeroacoustics model, which is described here and validated against experimental measurements recorded on a GE 1.5-MW wind turbine installed at the Flatirons Campus of the National Renewable Energy Laboratory in Boulder, Colorado. The validation demonstrates satisfactory agreement between numerical predictions and experimental recordings, with discrepancies up to 7 dB in the overall sound pressure levels at low wind speeds and a better agreement around the rated wind speed of the turbine.
Field data collected from the NREL/GE 1.5MW wind turbine (WT) and met tower (MetT) at the NREL Wind Technology Center near Boulder, CO June-October 2018 were analyzed to quantify the impacts of turbulence eddies on the load responses measured from sensors on the main shaft, blade and tower. The passage of individual mountain-generated eddies from the met tower to the WT were critically determined by correlating the optimal time shifts in signal between MetT and nacelle anemometers with mean advection time. Loading responses from mountain eddy passage were compared with atmospheric eddies from the north/south, unimpeded by the mountains, and found to be similar. Whereas time variations in torque were highly correlated with time changes in horizontal eddy velocity, the out-of-plane bending moments on the main shaft (directly forcing the main bearing) were uncorrelated with horizontal eddy velocity. This result is consistent with a previous LES study indicating that the main bearing is forced by asymmetrical interactions between the WT rotor and turbulence eddies, while power fluctuations respond primarily to advective eddy velocity. Surprisingly, the nacelle anemometer produced statistics very similar to the MetT.
Field data collected from the NREL/GE 1.5MW wind turbine and met tower at the NREL Wind Technology Center near Boulder, Colorado from June-October 2018 were analyzed to quantify the impacts of turbulence eddies on the load responses measured from sensors on the main shaft, blade and tower. The passage of individual mountain-generated eddies from the met tower to the wind turbine were critically determined by correlating the optimal time shifts in signal between met tower and nacelle anemometers with mean advection time. Loading responses from mountain eddy passage were compared with atmospheric eddies from the north/south, unimpeded by the mountains, and found to be similar. Whereas time variations in torque were highly correlated with time changes in horizontal eddy velocity, the out-of-plane bending moments on the main shaft (directly forcing the main bearing) were uncorrelated with horizontal eddy velocity. This result is consistent with a previous LES study indicating that the main bearing is forced by asymmetrical interactions between the rotor and turbulence eddies, while power fluctuations respond primarily to advective eddy velocity. Surprisingly, the nacelle anemometer produced statistics very similar to the met tower.
Concentrating Solar Power (CSP) provides firm and dispatchable electricity due to its thermal storage and hybridization capabilities, which supports the decarbonization of our energy supply. Of the various CSP technologies, parabolic trough collectors are the most mature, with over 500 MW operating worldwide. The optical performance of parabolic trough systems is sensitive to tracking error, which is defined as the angular offset of a collector away from the sun position in the transversal plane. Tracking error commonly occurs due to non-continuous adjustment of the trough angle to point toward the sun, but other factors such as gravity, heating, and wind loading can also contribute to tracking error. Researchers have explored the impact of tracking error on optical performance both numerically and experimentally, but existing studies do not include measurements from operational utility-scale power plants. Tilt angle measurements of parabolic troughs at operational utility-scale power plants illustrate spatial variations in optical performance and include various sources of tracking error such as gravity, heating, and wind loading. To fully characterize wind driven loads on parabolic troughs, we are conducting a long-term field measurement campaign at the Nevada Solar One CSP plant located in Boulder City, NV, which has a nominal capacity of 72 MW and 0.5 hours of full-load storage. We record load measurements on four outer trough rows, collecting support structure bending moments, drive torque moments, dynamic accelerations of the spaceframe, mirror displacement, and tilt angles. Using the tilt measurements acquired at 20 Hz frequency, we calculate the deviation between the nominal sun position and the tracker angle. Using a Monte-Carlo ray-tracing simulation software, we assess the impact of the tracker angle deviation on optical performance throughout the diurnal cycle at various spatial locations within the CSP plant. In our view, this first-of-a-kind study will provide important guidance for future trough designs that reduce the impact of various sources of tracking error on performance.
Centre Pier is a 3.9 ha property owned by the Commissioners of the Port Hope Harbour in the Municipality of Port Hope, Ontario, Canada. It is centrally located on the Port Hope waterfront and is bounded on the west by the Port Hope Harbour, on the east by the Ganaraska River, on the south by Lake Ontario, and on the north by a railway corridor. The property is currently leased by the Commissioners of the Port Hope Harbour to the Cameco Corporation which owns the four onsite building that are used as warehouse space for their uranium conversion facility located on the western side of the Harbour. Remediation of this site forms part of the Port Hope Project being undertaken by Atomic Energy of Canada Limited (AECL) and Public Works and Government Services Canada (PWGSC) as part of the Port Hope Area Initiative (PHAI). Soil impacts include radiological, metals and petroleum hydrocarbons resulting from long term historical industrial use. Radiological impacts in soil extend across most of the site primarily within the upper metre of fill. Metals-contaminated soil is present across the entire site in the underlying fill material. The metals-contaminated fill extends to a maximum depth of 2.0 m below grade at the north end of the site which is underlain by peat. However, the metals-contaminated soil could extend to the top of the bedrock on the remainder of the site. Based on the elevation of the bedrock in the adjacent river and Harbour Basin, the metals-contaminated soil may extend to a depth of 5.6 m or 6.5 m below existing grade. Petroleum-contaminated soil is present on the southeast side of the site, where a storage tank farm was previously located. Challenges include: - The complex history of the site both relating to site use and Pier construction. Pier development began in the 1800's and was undertaken by many different entities. Modifications and repairs were made over the years resulting in several different types of Pier walls and fill that must be considered during remediation. A wide variety of industrial activity on the Pier including extensive foundry operations as well as the industrial nature of the fill used to construct the Pier has resulted in extensive contamination distribution. The Pier structure will require reinforcement to permit both the remediation of the Pier and the adjacent Harbour and remediation techniques will need to be well suited to minimize disruption of wall structures as well as being able to deal with fill ranging from ash to boulders. - Multiple stakeholders are responsible for building demolition, remediation of radiological impacts, remediation of industrial impacts and the use of the site as a staging area for Harbour sediment remediation. The successful remediation of the Centre Pier will require careful negotiation and planning for the various remediation activities noted above. - The depth of contamination on the Pier would result in the complete removal of the Pier if all contamination were to be excavated. Therefore, a Risk Assessment will be conducted to determine the appropriate means for in situ risk management for materials to be left in place below a proposed depth of 1.5 m below current grade. With the concurrence of the property owners and Provincial regulators, the Risk Assessment will be undertaken in accordance with the Provincial requirements that will ensure adequate protection of the environment and future users of the site. - The end use of the Pier has yet to be confirmed by the Municipality. (authors)
For presentation at, and publication in the proceedings of, the National Radio Science Meeting, Boulder, CO, January 9-13, 2024.In this paper, we report on loss mechanisms contributing to the link budget for interrogation of Surface Acoustic Wave (SAW) devices in metallic tubular structures. Impedance matching losses associated with a SAW device are minimized by design optimization and antenna coupling losses and resulting propagation losses are measured in metallic tubular structures enabling prediction of interrogation distances with various antenna configurations.
ASHRAE Guideline 36-2021 (G36) provides high-performance control sequences for all-air and hydronic HVAC systems, and it has proven effective at reducing energy use for single building all-air equipment. The most recent version of G36 included control sequences for water-cooled chiller plants, which can be used in district cooling systems (DCSs). Despite not being a traditional application of G36 controls, DCSs could benefit from energy savings that G36 control sequences have demonstrated in single building systems. We therefore investigate the possibility to extend G36 chiller plant control from a single building to district cooling using a real-world district cooling system in Boulder, Colorado as a case study. Four timeframes representing low to peak loads are simulated and analyzed to compare energy use of the district cooling system for three control sequences. Results show that although G36 chiller plant sequences can be applied to DCSs, further analysis and potentially control optimization is needed to ensure energy savings compared to default controls.
We report on the fault-tolerant operation of logical qubits on a neutral atom quantum computer, with logical performance surpassing physical performance for multiple circuits including Bell state preparation (12x error reduction), random circuits (15x), and a prototype Anderson Impurity Model ground state solver for materials science applications (up to 6x, non-fault-tolerantly). The logical qubits are implemented via the [[4, 2, 2]] code (C 4 ). Our work constitutes the first complete realization of the benchmarking protocol proposed by Gottesman 2016 demonstrating results consistent with fault tolerance. In light of recent advances on applying concatenated C 4 /C 6 detection codes to achieve error correction with high code rates and thresholds, our work can be regarded as a building block towards a practical scheme for fault tolerant quantum computation. Our demonstration of a materials science application with logical qubits particularly demonstrates the immediate value of these techniques on current experiments.
In the U.S., emissions of greenhouse gases and air pollutants are often developed independently. Here, we describe the GReenhouse gas And Air Pollutants Emissions System (GRA 2 PES), which provides gridded emissions of fossil-fuel carbon dioxide (ffCO 2 ) and 93 air quality (AQ) species for 17 combustion and non-combustion sectors at 4 km × 4 km spatial resolution across the contiguous US. We find that the AQ emissions most spatially correlated with ffCO 2 are nitrogen oxides (NO x , ρ = 0.67), followed by sulfur dioxide (SO 2 , ρ = 0.51), carbon monoxide (CO, ρ = 0.44), and fine particulate matter (PM 2.5 , ρ = 0.38). We evaluate GRA 2 PES ffCO 2 emissions with an ensemble of publicly available regional and global inventories at national (Normalized Mean Bias (NMB) = +1.4%), state (NMB = +1.5%, R 2 = 0.98), and urban (NMB = +11.5%, R 2 = 0.97) scales. Nationally, the differences of publicly available inventories from the ensemble average range from −10.0% to +5.7%, and consistency diverges at state and urban scales. We simulate GRA 2 PES ffCO 2 in a particle dispersion model and compare to measurements of radiocarbon ( 14 C)-derived ffCO 2 collected in Los Angeles (August 2021), with results suggesting that GRA 2 PES ffCO 2 may be low by 19% for this city, but well within model-observation differences for other publicly available inventories (−43% to +94%). GRA 2 PES AQ/ffCO 2 ratios converted to concentration space generally agree with field observations (NMB = +4%, log R 2 = 0.90). Lastly, we present a method by which to utilize GRA 2 PES to derive AQ emission fluxes from ffCO 2 emissions.
The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol forms the basis for a public traceable and certifiable quantum randomness beacon that we have launched. Over the first 40 days of operation, we completed the protocol 7,434 out of 7,454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error multiplied by actual success probability bounded by 2−64. Further, the generation of certifiable and traceable randomness represents a public service that operates with an entanglement-derived advantage over comparable classical approaches.
This study demonstrates a specific application of the hierarchical system development (HSD) approach to investigate, analyze, and attribute model issues within the Unified Forecast System (UFS), with a focus on process isolation. By evaluating a non‐precipitating, shallow cumulus case at the Atmospheric Radiation Measurement Southern Great Plains site in the UFS global forecast against the observation, the investigation identifies a warmer and deeper daytime convective planetary boundary layer (PBL) and misrepresented nocturnal PBL transition. Hypothesis testing, which employs the Common Community Physics Package (CCPP) single‐column model (SCM) and uses the same physics as the UFS global model, confirms that these issues are attributed to the model physics and initialization. Specifically, misrepresented PBL processes are linked to problematic surface condition and a lack of cloud formation, which may stem from deficiencies in PBL and cloud microphysics parameterizations and their interactions. The UFS initial condition contributes to an earlier, excessively collapsed daytime convective boundary layer and a lack of decoupling between the stable boundary layer and residual layer late in the afternoon. This work introduces an avenue for the community to engage with the application of HSD, along with the CCPP and CCPP SCM, to understand the interplay of model physics, disentangle the roles of model components, as well as facilitate model and forecast improvement.
The surface energy budget (SEB) is a central regulator of Arctic climate and sea ice evolution, yet its processes remain poorly constrained due to sparse observations and complex, coupled surface-atmosphere interactions. This study leverages year-long measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) to provide the most comprehensive assessment to date of the central Arctic SEB and its modulation by atmospheric variability. Ship- and ice-based observations from October 2019 to September 2020 were used to directly measure or tightly constrain each term of the SEB, leading to exceptional energetic closure with the seasonal snow and ice mass balance. The analysis reveals strong seasonal transitions in atmosphere-surface energy transfer that are modulated by the atmospheric state and constrained by the ability of the surface temperature to respond. Classification of the atmosphere into its two dominant radiative states—the semi-transparent (ST) and opaque (OP)—highlights the central role of synoptic-scale variability in clouds. The ST atmospheric state dominated the long winter ice growth season, with limited cloudiness supporting persistent surface radiative cooling and ice growth. The OP state, associated with liquid-containing or thick ice clouds, became dominant in spring, with the combination of increased solar heating and cloud surface longwave warming driving ice and snow melt. Eddy covariance versus bulk approaches for deriving surface turbulent heat fluxes provide vastly different perspectives on the role of turbulence in modulating the SEB. These results establish a high-quality benchmark dataset for Arctic SEB studies and demonstrate how the balance of atmospheric radiative states exerts a first-order control on the annual evolution of the sea ice. The findings have broad implications for advancing observing technologies, understanding Arctic amplification, improving climate models, and predicting future sea ice change.