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Symmetry-projected cluster mean-field theory applied to spin systems
We introduce S z spin-projection based on cluster mean-field theory and apply it to the ground state of strongly correlated spin systems. In cluster mean-fields, the ground state wavefunction is written as a factorized tensor product of optimized cluster states. In previous work, we have focused on unrestricted cluster mean-field, where each cluster is S z symmetry adapted. We here remove this restriction by introducing a generalized cluster mean-field (GcMF) theory, where each cluster is allowed to access all S z sectors, breaking S z symmetry. In addition, a projection scheme is used to restore global S z , which gives rise to the S z spin-projected generalized cluster mean-field (S z GcMF). Both of these extensions contribute to accounting for inter-cluster correlations. We benchmark these methods on the 1D, quasi-2D, and 2D J 1 – J 2 and XXZ Heisenberg models. Furthermore, our results indicate that the new methods (GcMF and S z GcMF) provide a qualitative and semi-quantitative description of the Heisenberg lattices in the regimes considered, suggesting them as useful references for further inter-cluster correlations, which are discussed in this work.
Enhancing Convection Parameterization for Next Generation E3SM (Final Technical Report)
This technical report summarizes the achievements during the project period. The general goal of the project is to enhance the representation of atmospheric deep convection in the DOE global climate model E3SM. By implementing a stochastic convection scheme into E3SM, we improved the simulation of precipitation intensity and frequency. As a result, it has a profound impact on the simulation of other fields in the model, including aerosol scavenging by precipitation and aerosol radiative effects. We also implemented a convective cloud microphysics scheme into E3SMv2 to represent more accurately the interaction between convection and grid-scale clouds. An extensive analysis of model simulations as part of the Next Generation Development (NGD) convection scheme assessment project found that including the convective microphysics scheme improved the simulation of Madden-Julian oscillations (MJO) in the model. To make convective parameterization schemes more scale-aware as the GCM resolution increases, we analyzed the output from cloud-resolving model (CRM) simulations of both organized and unorganized convection by coarse-graining the CRM data to different GCM resolutions. Using a novel approach to modify the convective closure, we demonstrated that the convection scheme used in E3SM (ZM scheme) can be made scale-aware.
Improved Contacts for Tandem Cells with Enhanced Effciency Grown by D-HVPE
Dynamic hydride vapor phase epitaxy (D-HVPE) has provided a potential route towards lower cost material growth of III-V photovoltaic devices. A highly doped Ga0.5In0.5P emitter layer is grown in attempt to force passivation at the front of the cell to account for the absence of a suitable window layer in our reactor. Control over dopant diffusion in these materials is thus critical to achieving high-efficiency device performance. Here, we institute a two-step contact layer design that boosts tandem cell efficiencies by minimizing Se diffusion into the underlying emitter layer while still providing sufficiently low contact resistance. Short-circuit current in these devices improves to 8.9 mA/cm2 in an uncoated GaInP/GaAs cell, an improvement of 1.2 mA/cm2 over our previous best cell. Conversion efficiency with the new contact doping scheme is projected to be ~27% with the inclusion of a standard ARC layer.
Feedback Power Cost Optimization in Power Distribution Networks with Prosumers
Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.
Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies
Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs) or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we present a road map of how dynamic vegetation demographic models (VDMs) can be used to investigate hypotheses surrounding ecosystem responses to one type of UCE: unprecedented droughts. As a result of nonlinear ecosystem responses to UCEs that are qualitatively different from responses to milder extremes, we consider both biomass loss and recovery rates over time by reporting a time-integrated carbon loss as a result of UCE, relative to the absence of drought. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites using well-tested models (ED2 and LPJ-GUESS). The severity and patterns of biomass losses differed substantially between models. For example, biomass loss could be sensitive to either drought duration or drought intensity depending on the model approach. This is due to the models having different, but also plausible, representations of processes and interactions, highlighting the complicated variability of UCE impacts that still need to be narrowed down in models. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight the consequences of differences in process formulations and uncertainties in models, most notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. We provide a summary of the current state and role of many model processes that give way to different underlying hypotheses of plant responses to UCEs, reflecting knowledge gaps which in future studies could be tested with targeted field experiments and an iterative modeling–experimental conceptual framework.
WBS 2.1.5.401 - Model Validation and Site Characterization for Early Deployment MHK Sites and Establishment of Wave Classification Scheme
The "Resource Characterization" project delivers the data and tools needed to engineer robust marine renewable energy devices and projects. The project measures resource details at commercially promising sites, runs high resolution models of promising sites and regions, and develops classification schemes that streamline device engineering, project development, and increase investor confidence.
Challenges, Industry Practice, and Research Opportunities for Protection of IBR-Rich Systems
The objective of this technical report is to outline the challenges of protection design for power systems rich in inverter-based resources (IBRs), synthesize current industrial practices, review new approaches from recent literature, and explore future opportunities in protection. IBRs are experiencing widespread adoption across both transmission and distribution systems. When present in significant quantities, IBRs challenge the performance of many traditional protection functions. To address these issues, the industry has developed sophisticated protection schemes that involve advanced relaying techniques in highly engineered pilot projects. However, these schemes are expensive and time-consuming to develop, build, and test. Researchers have proposed a number of new approaches for protection in IBR-rich distribution systems. Despite their potential, these new approaches do not address some major shortcomings of industry approaches stemming from complexity, practical requirements, and reliability.
Error field predictability and consequences for ITER
Abstract ITER coil tolerances are re-evaluated using the modern understanding of coupling to least-stable plasma modes and an updated center-line-traced model of ITER’s coil windings. This reassessment finds the tolerances to be conservative through a statistical, linear study of n = 1 error fields (EFs) due to tilted, shifted misplacements and nominal windings of central solenoid and poloidal field coils within tolerance. We also show that a model-based correction scheme remains effective even when metrology quality is sub-optimal, and compare this to projected empirical correction schemes. We begin with an analysis of the necessity of error field correction (EFC) for daily operation in ITER using scalign laws for the EF penetration threshold. We then consider the predictability of EF dominant mode overlap across early planned ITER scenarios and, as measuring EFs in high power scenarios can pose risks to the device, the potential for extrapolation to the ITER Baseline Scenario (IBS). We find that carefully designing a scenario matching currents proportionally to those of the IBS is far more important than plasma shape or profiles in accurately measuring an optimal correction current set.
Pumped-Storage Hydropower using Abandoned Underground Mines (PSH-AUM) as an Innovative Energy Storage Technology for Fossil-Integrated Systems
Pumped-storage hydropower (PSH) provides around 95% of all utility-scale energy storage in the U.S. and globally. Additional deployment of PSH is hampered by excessively long permitting and commissioning requirements and is constrained to locations for which natural topography provides suitable elevation relief between the upper and lower reservoirs (the ΔH challenge). The purpose of this research was to evaluate Pumped-Storage Hydropower using Abandoned Underground Mines (PSH-AUM) as a means to solve the ΔH challenge and initiate the commercialization pathway for a promising new energy storage technology. Four primary tasks were conducted: Screening and ranking of candidate sites for project development; multiphase reservoir modeling to evaluate mine performance; techno-economic analysis and preliminary designs for PSH-AUM systems integrated with fossil-fuel power units; and stakeholder engagement to identify pathways to commercialization of this new technology. Key results were achieved in each of the four primary tasks. Candidate site screening determined that nearly 10,000 underground mines were spatially locatable, of which more than 100 sites appear suitable for integration with existing fossil power plants that are expected to remain in longer-term operation. Mine reservoir models were developed using PNNL’s STOMP simulator and parameterized using candidate site data to evaluate interactions with the surrounding groundwater system and confirm the potential for some mines to accommodate inflows and outflows on the order of 100 m3/s over 8-hour durations (1.6 GWh system) without excessive aqueous pressures. Techno-economic analysis resulted in a project cost optimization scheme to identify key sensitivities and the development of preliminary designs that can minimize overall costs of deployment. Finally, stakeholder engagement with industry, state government, and local economic development leaders confirmed the viability of PSH-AUM as a promising new technology. Our Phase I project results suggest that PSH-AUM technology has a domestic market potential on the order of $100+ Billion with ample space for technology development to commercialization within the next decade.
Reduced order models for Lagrangian hydrodynamics
It is reported, as a mathematical model of high-speed flow and shock wave propagation in a complex multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts with sharp gradients. These challenges hinder the existing projection-based model reduction schemes from being practical. We develop several variations of projection-based reduced order model techniques for Lagrangian hydrodynamics by introducing three different reduced bases for position, velocity, and energy fields. A time-windowing approach is also developed to address the challenge imposed by the advection-dominated solutions. Lagrangian hydrodynamics is formulated as a nonlinear problem, which requires a proper hyper-reduction technique. Therefore, we apply the over-sampling DEIM and SNS approaches to reduce the complexity due to the nonlinear terms. Finally, we also present both a posteriori and a priori error bounds associated with our reduced order model. We compare the performance of the spatial and time-windowing reduced order modeling approaches in terms of accuracy and speed-up with respect to the corresponding full order model for several numerical examples, namely Sedov blast, Gresho vortices, Taylor-Green vortices, and triple-point problems.
A Comprehensive Framework for Valuation of Ecosystem Services in the Context of Hydropower
While models to value ecosystem services exist, they suffer from a lack of “portability” in the sense that a single modelling framework developed for one site cannot be imported and applied to another. Additionally, benefit estimations are often fragmented, incomplete, incomparable, and in heterogenous metrics, thus preventing aggregation to arrive at one comprehensive value. In the context of hydropower, the methods, as well as the metrics used to value the associated ecosystem services, vary between stakeholders (e.g., competing water users, agencies, etc.), detracting from the ability to assess the total value of a hydropower project, water management schemes, or comparing value between competing water users. Further, current methods to value water neglect non-market ecosystem services’ values by failing to account for externalities, resulting in misallocation of costs (e.g., obligatory stakeholder payments for water use) and misinterpretation of hydropower benefits. The benefit-cost ratios in hydropower development are often incomplete because non-market benefits are excluded (e.g., benefits, such as fish habitat resiliency and agricultural water reliability, derived from hydropower development). An approach to enable consistent, standardized hydropower benefit-cost analyses does not currently exist. This paper conceptualizes a methodology to standardize ecosystem services valuation in the context of hydropower projects through the integration of the U.S. Environmental Protection Agency’s existing Final Ecosystem Goods and Services Classification System framework and economic valuation techniques, and demonstrates the applicability of this methodology through a limited proof-of-concept application (the New Waddell Plant, a pumped hydroelectric energy storage facility in Phoenix, AZ). The beauty of our proposed framework lies in its ability to be imported and applied to any other pumped storage facility after accounting for site-specific features.
Across the Scales of the Nucleus: Understanding Short Range Correlations from Medium Modification to Probe Independence
The atomic nucleus presents an intricate system due to the non-linear forces described by Quantum Chromodynamics (QCD) that govern its structure. The range of scales involved is remarkable; the most massive nuclei weigh approximately five orders of magnitude more than the quarks that compose them. The nucleus can be analyzed at various levels, from quarks to hadrons to the nucleus as a whole. Short-Range Correlations (SRCs) within the nucleus play a significant role that spans these diverse scales. At the most fundamental level, SRCs influence the interaction between nucleons. The nucleon-nucleon (NN) interaction, arising from QCD, is crucial in determining nuclear properties. SRCs serve as valuable probes for measuring this NN interaction, as the nucleons within SRCs become effectively decoupled from the rest of the nucleus. Multiple experimental techniques, including electron scattering, have been employed to investigate the NN interaction through SRCs. However, our first project demonstrates that inclusive measurements alone are inadequate to constrain this interaction fully. Moving to the scale of the nucleus, SRCs contribute to the high-momentum tail of the nuclear spectral function. While the low-momentum region is characterized by nucleons exhibiting bulk properties, nucleons begin to pair into SRCs at higher momenta. Our research aims to bridge the understanding between the mean-field portion of the nucleus and its high-momentum SRC components. Additionally, SRCs affect the quark structure of protons, as evidenced by the EMC effect, which indicates that quarks behave differently when protons are embedded within a nucleus—an effect referred to as medium modification. This thesis explores the correlation between SRCs and medium modification across various experimental setups. Finally, we seek to establish an interpretation of the nuclear ground state. Accomplishing this requires demonstrating that our SRC observables are independent of the probe’s scale and scheme. The concluding project of this thesis illustrates how we utilize triple coincidence quasi-elastic scattering across a range of (Q2) values to develop a model-dependent framework for understanding SRC distributions within the nucleus’s ground-state wavefunction.
Nuclear Reaction Data Evaluations for Nuclear Applications Physics and modeling [Slides]
This presentation provides an evaluation workflow scheme for the project. It also discusses nuclear data libraries, including an overview of worldwide nuclear data libraries and current funding agencies. The presentation also discusses the theoretical framework commonly used in the evaluated work, including the R-matrix theory (≈ up to a few keVs for heavy nuclei) as well as pre-equilibrium (PE) and Hauser-Feshbach (HF) theory (⪆1 MeV for medium/heavy nuclei). Inclusion of experimental effects are also discussed. Examples of evaluated work, including theory, experiments, and applications are discussed, specifically n+ 28,29,30 Si evaluation (direct capture component), n+ 53 Cr evaluation (strong multiple scattering effects), n+ 239 Pu(n,γf) reaction (fluctuations in neutron multiplicities), and α+ 17,18 O evaluations (emerging neutron spectra).
Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well
Knowledge of petrophysical and geomechanical properties of gas hydrate-bearing sediments are essential for predicting reservoir response due to gas production from gas hydrate reservoirs. That information will be critical parameters for designing production well completion such as specification of depressurization pump, water storage tank, and mesh size of sand screen. In December 2018, Stratigraphic Test Well Hydrate-01 was drilled in the western part of the Prudhoe Bay Unit, Alaska North Slope as part of the technical planning effort for a future long-term production test by collaborative team of DOE/NETL, USGS, and MH21-S (Boswell et al., 2020, Collett et al., 2020, Okinaka et al., 2020). Data set of logging-while-drilling (LWD) were acquired (Haines et al., 2020, Suzuki et al., 2019) and core sampling depth was determined on-site.Side-wall pressure coring was conducted to recover gas hydrate-bearing sediments from two reservoir sections named Unit-B and Unit-D. A total of 34 cores were successfully recovered by 5 runs of a wire-line deployed pressure corer (CoreVault® System - Halliburton). Core analysis scheme of this project are shown in Figure 1. All cores were quenched in liquid nitrogen while at high pressure in the laboratory of Stratum Reservoir, LLC. at Anchorage (Figure 1, a)). And the cores were removed from the pressure corer autoclave with temperature support of dry ice and stored under liquid nitrogen at atmospheric pressure. 19 damaged cores were processed to index property measurements directly such as grain size, grain density. 4 of another 17 cores were depressurized and trimmed for making a plug to analyze petrophysical properties of host sediments. Unsteady-state permeability test was conducted to obtain relative water permeability to gas and core scale NMR T2 distribution measurement was performed for evaluating pore size distribution at Houston (Figure 1, b)). Remained high quality 13 cores were preserved with gas hydrate for advanced laboratory analysis. National Institute of Advanced Industrial Science and Technology, as a part of the Japanese National Hydrate Research Program (MH21-S, funded by Ministry of Economy, Trade and Industry), received the samples at Sapporo, Japan for advanced core analysis. High-resolution X-ray CT was used to analyze the quality of the samples, which showed undisturbed lithological layers. Cores were lathed into cylindrical shape and distributed for multi property measurements (Figure 1, c)).<p>As a result, sediment from Unit-D is categorized as silty sand at ~37% porosity with ~80% gas hydrate saturation. An average hydration number n = 6.16 was measured by Raman spectroscopy. An average intrinsic permeability of ~400 mD and in situ effective permeability (with hydrate) on the order of ~10 mD. The Unit B recovered cores consisted of well sorted sand at ~40% porosity with ~95% gas hydrate saturation. An average intrinsic permeability of ~1 Darcy and in situ effective permeability on the order of ~30 mD was measured for the Unit B cores. There was a small permeability reduction due to porosity loss with increasing effective stress that simulated consolidation behavior along with depressurization in the highly permeable sandy sediment. The apparent minimum change in porosity and permeability may be caused by the low compressibility of quartz sand grains in the recovered cores. XRD and thermal conductivity analysis also suggested high quartz content. Triaxial compression tests established internal friction angles based on the Mohr-Coulomb's failure criterion, which are 40° for hydrate-bearing sediment and 29.8° for hydrate free sediment.</p>
Understanding uncertainties in projections of western North Pacific tropical cyclogenesis
Reliable projections of tropical cyclone (TC) activities in the western North Pacific (WNP) are crucial for climate policy-making in densely-populated coastal Asia. Existing projections, however, exhibit considerable uncertainties with unclear sources. Here, based on future projections by the latest Coupled Model Intercomparison Project Phase 6 climate models, we identify a new and prevailing source of uncertainty arising from different TC identification schemes. Notable differences in projections of detected TCs and empirical genesis potential indices are found to be caused by inconsistent changes in dynamic and thermodynamic environmental factors affecting TC formations. While model uncertainty holds the secondary importance, we show large potential in reducing it through improved model simulations of present-day TC characteristics. Internal variability noticeably impacts near-term projections of the WNP tropical cyclogenesis, while the relative contribution of scenario uncertainty remains small. Our findings provide valuable insights into model development and TC projections, thereby aiding in adaptation decisions.
Smart quantum statistical imaging beyond the Abbe-Rayleigh criterion
The wave nature of light imposes limits on the resolution of optical imaging systems. For over a century, the Abbe-Rayleigh criterion has been utilized to assess the spatial resolution limits of imaging instruments. Recently, there has been interest in using spatial projective measurements to enhance the resolution of imaging systems. Unfortunately, these schemes require a priori information regarding the coherence properties of “unknown” light beams and impose stringent alignment conditions. Here, we introduce a smart quantum camera for superresolving imaging that exploits the self-learning features of artificial intelligence to identify the statistical fluctuations of unknown mixtures of light sources at each pixel. This is achieved through a universal quantum model that enables the design of artificial neural networks for the identification of photon fluctuations. Our protocol overcomes limitations of existing superresolution schemes based on spatial mode projections, and consequently provides alternative methods for microscopy, remote sensing, and astronomy.
Projection-to-Born-improved subtractions at NNLO
While the current frontier in fixed-order precision for collider observables is N 3 LO, important steps are necessary to consolidate NNLO cross-section predictions with improved stability and efficiency. Slicing methods have been successfully applied to obtain NNLO and N 3 LO predictions, but have shown poor performance in the presence of fiducial cuts due to large kinematical power corrections. In this paper we implement Projection-to-Born-improved q T (P2B q T ) and jettiness (P2Bτ 0 ) subtractions for a large class of color singlet processes in MCFM. This method allows for the efficient evaluation of fiducial power corrections in any non-local subtraction scheme using a Projection-to-Born subtraction. We demonstrate the significant numerical improvements of this method based on fiducial Drell-Yan and Higgs cross-sections. Moreover, with fiducial power corrections removed via this method, the leading-logarithmic power corrections that have only been calculated without fiducial cuts can be included, further improving the calculations. For di-photon production with photon isolation, we devise a novel method in combination with P2B-improved subtractions, which we name P2B γ τ 0 , and P2B γ q T for the two subtraction schemes, respectively. This method allows the inclusion of both fiducial power corrections due to kinematic cuts on the photons and a set of isolation power corrections in the fragmentation channel where a quark may enter the isolation cone. We find significant improvements in the convergence of NNLO di-photon cross-sections with photon isolation cuts, demonstrating that it is possible to achieve a stable and efficient calculation of di-photon cross-sections using slicing methods.