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At least 343 records · Page 19

Transforming Regional Transmission Planning: FERC Order 1920 Explained [Slides]

This presentation presents the key topics from FERC Order 1920: Building for the Future Through Electric Regional Transmission Planning and Cost Allocation. It breaks down and summarizes the main reforms from the regulation including comments from diverse perspectives on how the new rules may be implemented. This presentation can serve as a resource for diverse stakeholders including policymakers, utilities, industry, and researchers who seek to understand how the new ruling may impact regional transmission planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multi-scale, Multi-disciplinary, and Multi-agent Explainable AI with Koopman-Undergirded Learning, Prediction, and Analysis (M3EA KULPA) (Project Closeout Report)

The goal of this project was to develop and use domain-aware machine learning formulations, based on the Koopman Operator (KO), for modelling multi-scale, multi-disciplinary (e.g., multi-physics), and/or multi-agent systems. The project developed these formulations for the following cases: • Systems with dynamics at two separate time scales, • Systems with a bi-level hierarchical control structure, • Systems with bi-level hierarchical control and dynamics at two separate time scales (the lower level controls operating at the faster time scale), and • Systems with n separate but interacting agents/disciplines (with/without control, respectively); the controls for each agent could include bi-level hierarchical control and dynamics at two separate time scales as described above. The project then defined a set of dynamical systems consisting of different nonlinear oscillators that could be used to test these different formulations and then subsequently learned the KO models for those systems. With the KO models, we were able to do the following: • Quantify system stability, including both long-term and transient behavior, • Quantify the effects of feedbacks between the different time scales and agents/disciplines in terms of those feedbacks’ effects on system stability, • Replace a standard Proportional-Integral (PI) control in the hierarchical control structure with a KO-based Linear-Quadratic Regular (LQR), a form of optimal control, • Calculate optimal supervisory control policies a) with and without time scale separated dynamics at the lower level control levels and b) with both PI and KO-based LQR lower level control policies, and • Calculate dynamic Nash equilibria for multi-agent systems where each agent makes its own control decisions.

97 MATHEMATICS AND COMPUTING↗

Individual Nest Site Preferences Do Not Explain Upslope Population Shifts of a Secondary Cavity-Nesting Species

Geographic ranges of plants and animals are shifting due to environmental change. While some species are shifting towards the poles and upslope in elevation, the processes leading to these patterns are not well known. We analyzed 22 years of western bluebird (Sialia mexicana) data from a large nest box network in northern New Mexico at elevations between 1860 m and 2750 m. This population has shifted to higher elevations over time, but whether this is due to changes in nesting behavior and preference for higher elevation within the population or driven by immigration is unclear. We banded adults and nestlings from nest boxes and examined nesting location and elevation for individual birds captured two or more times. Most recaptured birds nested at the same nest boxes in subsequent years, and the number of birds that moved upslope did not significantly differ from the number that moved downslope. Fledglings moved greater distances and elevations than adults, but these movements were not upslope specific. Female fledglings showed greater changes in elevation and distance compared to male fledglings, but again, movements were not consistently upslope. The upslope shift in this population may be due to birds immigrating into the population and not from changes in individual nesting behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Development of Explainable Data-Driven Turbulence Models with Application to Liquid Fuel Nuclear Reactors

Liquid fuel nuclear reactors offer innovative possibilities in terms of nuclear reactor designs and passive safety systems. Molten Salts Reactors (MSRs) with a fast spectrum are a particular type of these reactors using liquid fuel. MSFRs often involve large open cavities in their core in which the liquid fuel circulates at a high speed to transport the heat generated by the nuclear reactions into the heat exchangers. This high-speed flow yields a turbulent field with large Reynolds numbers in the reactor core. Since the nuclear power, the neutron precursor’s transport and the thermal exchanges are strongly coupled in the MSFR’s core cavity, having accurate turbulent models for the liquid fuel flow is necessary to avoid introducing significant errors in the numerical simulations of these reactors. Nonetheless, high-accuracy simulations of the turbulent flow field in the reactor cavity of these reactors are usually prohibitively expensive in terms of computational resources, especially when performing multiphysics numerical calculations. Therefore, in this work, we propose a novel method using a modified genetic algorithm to optimize the calculation of the Reynolds Shear Stress Tensor (RST) used for turbulence modeling. The proposed optimization methodology is particularly suitable for advanced liquid fuel reactors such as the MSFRs since it allows the development of high-accuracy but still low-computational-cost turbulence models for the liquid fuel. We demonstrate the applicability of this approach by developing high accuracy Reynolds-Averaged Navier–Stokes (RANS) models (averaged flow error less than 5%) for a low and a large aspect ratio in a Backward-Facing Step (BFS) section particularly challenging for RANS models. The newly developed turbulence models better capture the flow field after the boundary layer tipping, over the extent of the recirculation bubble, and near the boundary layer reattachment region in both BFS configurations. The main reason for these improvements is that the developed models better capture the flow field turbulent anisotropy in the bulk region of the BFS. Then, we illustrate the interest in using this turbulence modeling approach for the case of an MSFR by quantifying the impact of the turbulence modeling on the reactor key parameters.

42 ENGINEERING↗

The Spiral Galaxies Flat Rotational Velocity Curve Explained by the Constant Group Velocity of a Nonlinear Density Wave

The rotation velocity curves of stars in galaxies, the motions of pairs of galaxies, and the behavior of galaxies in clusters and super-clusters all indicate that there is a lack of mass on different scales in the universe. In this paper, we derive the expression for rotational velocity using the nonlinear density wave theory considering only stellar components and we show that such theory can support the observed flat rotational velocity curve due to the main property of the soliton wave, which is a constant group velocity of the wave. The surface mass density (SMD) function, used to derive gravitational potential gradient and rotational velocity, is not assumed but rather derived as a solution of the nonlinear Srödinger equation, on the contrary to the widely used, in the literature, exponential disk approximation. Three parameters relevant to the curve shape are the intensities of equilibrium SMD, the amplitude of the wave, and total angular velocity or differential rotation, equivalently. Since the shape of the rotational velocity is highly sensitive to the mentioned parameters, this theory eventually provides a method for a very accurate estimation of galaxy mass and angular velocity as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stellar Activity Manifesting at a One-year Alias Explains Barnard b as a False Positive

Barnard’s star is among the most studied stars given its proximity to the Sun. It is often considered the radial velocity (RV) standard for fully convective stars due to its RV stability and equatorial decl. Recently, an Msin i=3.3M{sub ⊕} super-Earth planet candidate with a 233 day orbital period was announced by Ribas et al. New observations from the near-infrared Habitable-zone Planet Finder (HPF) Doppler spectrometer do not show this planetary signal. We ran a suite of experiments on both the original data and a combined original + HPF data set. These experiments include model comparisons, periodogram analyses, and sampling sensitivity, all of which show the signal at the proposed period of 233 days is transitory in nature. The power in the signal is largely contained within 211 RVs that were taken within a 1000 day span of observing. Our preferred model of the system is one that features stellar activity without a planet. We propose that the candidate planetary signal is an alias of the 145 day rotation period. This result highlights the challenge of analyzing long-term, quasi-periodic activity signals over multiyear and multi-instrument observing campaigns.

47 OTHER INSTRUMENTATION↗

A thermal-driven graupel generation process to explain dry-season convective vigor over the Amazon

Large-eddy simulations (LESs) are conducted for each day of the intensive observation periods (IOPs) of the Green Ocean Amazon (GoAmazon) field campaign to characterize the updrafts and microphysics within deep convective cores while contrasting those properties between Amazon wet and dry seasons. Mean Doppler velocity (V dop ) values simulated using LESs are compared with 2-year measurements from a radar wind profiler (RWP) as viewed by statistical composites separated according to wet- and dry-season conditions. In the observed RWP and simulated LES V dop composites, we find more intense low-level updraft velocity, vigorous graupel generation, and intense surface rain during the dry periods compared with the wet periods. To investigate coupled updraft–microphysical processes further, single-day golden cases are selected from the wet and dry periods to conduct detailed cumulus thermal tracking analysis. Tracking analysis reveals that simulated dry-season environments generate more droplet-loaded low-level thermals than wet-season environments. This tendency correlates with seasonal contrasts in buoyancy and vertical moisture advection profiles in large-scale forcing. Employing a normalized time series of mean thermal microphysics, the simulated cumulus thermals appear to be the primary generator of cloud droplets. When subsequent thermals penetrate the ice crystal layer, droplets within the thermals interact with entrained ice crystals, which enhances riming in the thermals. This appears to be a production pathway of graupel/hail particles within simulated deep convective cores. In addition, less-diluted dry-case thermals tend to be elevated higher, and graupel grows further during sedimentation after spilling out from thermals. Therefore, greater concentrations of low-level moist thermals likely result in more graupel/hail production and associated dry-season convective vigor.

54 ENVIRONMENTAL SCIENCES↗

Hysteretic temperature sensitivity of wetland CH 4 fluxes explained by substrate availability and microbial activity

Methane (CH 4 ) emissions from wetlands are likely increasing and important in global climate change assessments. However, contemporary terrestrial biogeochemical model predictions of CH 4 emissions are very uncertain, at least in part due to prescribed temperature sensitivity of CH 4 production and emission. While statistically consistent apparent CH 4 emission temperature dependencies have been inferred from meta-analyses across microbial to ecosystem scales, year-round ecosystem-scale observations have contradicted that finding. Here, we show that apparent CH 4 emission temperature dependencies inferred from year-round chamber measurements exhibit substantial intra-seasonal variability, suggesting that using static temperature relations to predict CH 4 emissions is mechanistically flawed. Our model results indicate that such intra-seasonal variability is driven by substrate-mediated microbial and abiotic interactions: seasonal cycles in substrate availability favors CH 4 production later in the season, leading to hysteretic temperature sensitivity of CH 4 production and emission. Our findings demonstrate the uncertainty of inferring CH 4 emission or production rates from temperature alone and highlight the need to represent microbial and abiotic interactions in wetland biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗

Coordination of rooting, xylem, and stomatal strategies explains the response of conifer forest stands to multi-year drought in the southern Sierra Nevada of California

Abstract. Extreme droughts are a major determinant of ecosystem disturbance that impacts plant communities and feeds back into climate change through changes in plant functioning. However, the complex relationships between aboveground and belowground plant hydraulic traits and their role in governing plant responses to drought are not fully understood. In this study, we use a model, the Functionally Assembled Terrestrial Ecosystem Simulator in a configuration that includes plant hydraulics (FATES-Hydro), to investigate ecosystem responses to the 2012–2015 California drought in comparison with observations at a site in the southern Sierra Nevada that experienced widespread tree mortality during this drought. We conduct a sensitivity analysis to explore how different plant water sourcing and hydraulic strategies lead to differential responses during normal and drought conditions. The analysis shows the following. Deep roots that sustain productivity through the dry season are needed for the model to capture observed seasonal cycles of evapotranspiration (ET) and gross primary productivity (GPP) in normal years, and deep-rooted strategies are nonetheless subject to large reductions in ET and GPP when the deep soil reservoir is depleted during extreme droughts, in agreement with observations. Risky stomatal strategies lead to greater productivity during normal years as compared to safer stomatal control, but they also lead to a high risk of xylem embolism during the 2012–2015 drought. For a given stand density, stomatal and xylem traits have a stronger impact on plant water status than on ecosystem-level fluxes. Our study highlights the significance of resolving plant water sourcing strategies to represent drought impacts on plants and consequent feedbacks in models.

54 ENVIRONMENTAL SCIENCES↗