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At least 415 records · Page 23

The Magnetized Indirect Drive Project on the National Ignition Facility

A new project is underway at the National Ignition Facility with the goal of applying a seed magnetic field to the fusion fuel in an indirect drive hohlraum implosion and quantifying the effect on the hot-spot temperature, shape and neutron yield. Magnetizing fusion fuel is calculated to reduce heat loss from the implosion core by constraining the motion of electrons and fusion-generated alpha particles; this can improve the chances of achieving high-gain fusion in a laboratory plasma. Here, we describe the goals of this project and the significant scientific and technological challenges which must be overcome for this project to succeed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗

When do different scenarios of projected electricity demand start to meaningfully diverge?

Resource adequacy studies look at balancing electricity supply and demand on 10- to 15-year time horizons while asset investment planning typically evaluates returns on 20- to 40-year time horizons. Projections of electricity demand are factored into the decision-making in both cases. Climate, energy policy, and socioeconomic changes are key uncertainties known to influence electricity demands, but their relative importance for demands over the next 10-40 years is unclear. The power sector would benefit from a better understanding of the need to characterize these uncertainties for resource adequacy and investment planning. In this study, we quantify when projected United States (U.S.) electricity demands start to meaningfully diverge in response to a range of climate, energy policy, and socioeconomic drivers. Here we use a wide yet plausible range of 21st century scenarios for the U.S. The projections span two population/economic growth scenarios (Shared Socioeconomic Pathways 3 and 5) and two climate/energy policy scenarios, one including climate mitigation policies and one without (Representative Concentration Pathways 4.5 and 8.5). Each climate/energy policy scenario has two warming levels to reflect a range of climate model uncertainty. We show that the socioeconomic scenario matters almost immediately – within the next 10 years, the climate/policy scenario matters within 25-30 years, and the climate model uncertainty matters only after 50+ years. This work can inform the power sector working to integrate climate change uncertainties into their decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluation of integrated daylighting and electric lighting design projects: Lessons learned from international case studies

This article presents and discusses the lessons learned from the monitoring of 25 integrated daylighting and electric lighting international case study projects. The case studies consist of real occupied buildings that have been monitored as part of the International Energy Agency (IEA) SHC Task 61/EBC Annex 77 Programme. The general goal of the case studies was to balance lighting energy use with occupants’ visual and non-visual requirements. This was achieved using innovative solutions for daylighting and electric lighting with advanced controls, but also implementing simple and out-of-the-box strategies. The findings suggest that energy demands for lighting can significantly be reduced by combining sensible daylight provision, efficient lighting sources, and advances in controls. Yet, the effective achievement of project goals requires adequate monitoring, fine-tuning, and verification. The findings also suggest that the adoption of “integrative” lighting – that is, lighting systems that address both visual and non-visual responses – is getting increasingly popular. Catering to non-visual requirements will likely drive further innovation in lighting technology. Currently, there is limited investment available for developing daylighting systems for integrative lighting, and the current related electric strategies often come at the risk of energy rebound effects. Overall, providing daylighting and understanding user requirements are fundamental steps towards achieving quality projects, with potential benefits beyond saving energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Risk matrix for legacy wells within the Area of Review (AoR) of Carbon Capture & Storage (CCS) projects

The success of CCS depends on the capacity, injectivity, and confinement by the storage medium. Thousands of wells drilled over the past century with the intention to find the trapped oil and gas may penetrate the containment seals. These wells may provide leakage pathways for the CO 2 to escape and contaminate the underground sources of drinking water (USDW) or reach the surface in the worst-case scenario. Identifying the risky wells penetrating the containment seals and predicting their current as well as future well integrity is the most challenging task when limited data is available. Here, this paper proposes a unique methodology for risk assessment of the wells penetrating the containment seals based on the proximity of these wells from the proposed injection location, mechanical integrity, and accessibility of these wells over the lifecycle of the CCS project. This helps in identifying the wells which need immediate attention from the wells that need little to no attention. It also highlights the corrective actions necessary for the success of the CCS project as well as help estimate the approximate cost required to perform the corrective actions. This methodology focuses on all wells (producers, injectors, orphan, abandoned, water, stratigraphic, etc) while the majority of the studies found in literature focused on wells with sustained casing pressure (SCP) reports and cement bond logs (CBL). The proposed risk matrix, if applied to future CCS projects across the globe, will uniformly categorize the wells within the Area of Review (AoR).

58 GEOSCIENCES↗

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗

Translational research in the MPICH project

The MPICH project is an example of translational research in computer science before that term was well known or even coined. The project began in 1992 as an effort to develop a portable, high-performance implementation of the emerging Message-Passing Interface (MPI) Standard. It has enabled the widespread adoption of MPI as a way to write scalable parallel applications on systems of all sizes including upcoming exascale supercomputers. In this paper, we describe how the translational research process was used in MPICH, how that led to its success, the challenges encountered and lessons learned, and how the process could be applied to other similar projects.

97 MATHEMATICS AND COMPUTING↗

Development and application of an environmental risk register for marine energy device and project developers

The marine energy industry is steadily advancing as more devices are deployed worldwide. However, several challenges and barriers remain, such as lingering uncertainty regarding the potential environmental effects of marine energy devices on marine animals, habitats, and ecosystems. Concerns have led to difficulty navigating permitting and consenting processes and receiving authorization to deploy devices in the marine environment, including extended timelines and costs. Based on existing risk registers, a novel marine energy environmental risk register was created to help the marine energy industry move beyond these barriers. This risk register aims to aid marine energy device and project developers identify and assess potential environmental risks early in device design or project planning, document and track potential environmental interactions, prioritize risks and determine risk responses, and make decisions throughout device or project development. It can also be used as a tool to assist in communicating with regulators and advisors during permitting processes and to inform stakeholder and community engagement efforts. This paper details the methods and process to develop a risk register specific to environmental effects of marine energy and describes two use cases (one for wave energy and another for tidal energy) to highlight example results. Due to the tool's novelty, the paper showcases its application for the marine energy industry and acknowledges limitations and possible future improvements. Overall, the environmental risk register shows promise to support marine energy developers when identifying, tracking, and addressing potential environmental risks and to help successfully navigate permitting and deploy marine energy devices responsibly.

Environmental effects↗

Exploiting ν-dependence of projected energy correlators in HICs

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Global wave energy resource classification system for regional energy planning and project development

Efforts to streamline and codify wave energy resource characterization and assessment for regional energy planning and wave energy converter (WEC) project development have motivated the recent development of resource classification systems. Given the unique interplay between WEC absorption and resource attributes, viz, available wave power frequency, directionality, and seasonality, various consensus resource classification metrics have been introduced. However, the main international standards body for the wave energy industry has not reached consensus on a wave energy resource classification system designed with clear goals to facilitate resource assessment, regional energy planning, project site selection, project feasibility studies, and selection of WEC concepts or archetypes that are most suitable for a given wave energy climate. In this work, a primary consideration of wave energy generation is the available energy that can be captured by WECs with different resonant frequency and directional bandwidths. Therefore, the proposed classification system considers combinations of three different wave power classifications: the total wave power, the frequency-constrained wave power, and the frequency-directionally constrained wave power. The dominant wave period bands containing the most wave power are sub-classification parameters that provide useful information for designing frequency and directionally constrained WECs. The bulk of the global wave energy resource is divided into just 22 resource classes representing distinct wave energy climates that could serve as a common language and reference framework for wave energy resource assessment if codified within international standards.

16 TIDAL AND WAVE POWER↗

Hydrological projections over the Upper Indus Basin at 1.5 °C and 2.0 °C temperature increase

We analyse an ensemble of statistically downscaled Global Climate Models (GCMs) to investigate future water availability in the Upper Indus Basin (UIB) of Pakistan for the time horizons when the global and/or regional warming levels cross Paris Agreement (PA) targets. The GCMs data is obtained from the 5th Phase of Coupled Model Inter-Comparison Project under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Based on the five best performing GCMs, we note that global 1.5 °C and 2.0 °C warming thresholds are projected in 2026 and 2047 under RCP4.5 and 2022 and 3036 under RCP8.5 respectively while these thresholds are reached much earlier over Pakistan i.e. 2016 and 2030 under RCP4.5 and 2012 and 2025 under RCP8.5 respectively. Interestingly, the GCMs with the earliest emergence at the global scale are not necessarily the ones with the earliest emergence over Pakistan, highlighting spatial non-linearity in GCMs response. The emergence of 2.0 °C warming at global scale across 5 GCMs ranges from 2031 (CCSM4) to 2049 (NorESM) under RCP8.5. Precipitation generally exhibits a progressive increasing trend with stronger changes at higher warming or radiative forcing levels. Hydrological simulations representing the historical, 1.5 °C and 2.0 °C global and region warming time horizons indicate a robust but seasonally varying increase in the inflows. The highest inflows in the baseline and future are witnessed in July. However, the highest future increase in inflows is projected in October under RCP4.5 (37.99% and 65.11% at 1.5 °C and 2.0 °C) and in April under RCP8.5 (37% and 62.05% at 1.5 °C and 2.0 °C). These hydrological changes are driven by increases in the snow and glacial melt contribution, which are more pronounced at 2.0 °C warming level. These findings should help for effective water management in Pakistan over the coming decades.

54 ENVIRONMENTAL SCIENCES↗

Heliostat sizing methodology for concentrating solar thermal industrial process heat projects

This study presents a method to obtain a heliostat size that minimizes the levelized cost of heat (LCOH) of a heliostat-based concentrating solar thermal system for applications of solar heating for industrial processes at operating temperatures from 565 to 1550°C. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model to supplement the previously developed cost models, which we update to reflect current pricing trends. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWh th . Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the LCOH, producing a characteristic U-shaped trend with a robust near-optimal window of 7-20 m 2 ; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats being deployed at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗

Nitrate loading projection is sensitive to freeze-thaw cycle representation

Climate change can have substantial impacts on nitrogen runoff, which is a major cause of eutrophication, harmful algal blooms, and hypoxia in freshwaters and coastal regions. We examined responses of nitrate loading to climate change in the Upper Mississippi River Basin (UMRB) with an enhanced Soil and Water Assessment Tool with physically based Freeze-Thaw cycle representation (SWAT-FT), as compared with the original SWAT model that employs an empirical equation. Driven by future climate projections from five General Circulation Models (GCMs) from 1960 to 2099 under the Representative Concentrations Pathways (RCP) 8.5 scenario, we analyzed changes in riverine nitrate loadings, as well as terrestrial surface and subsurface contributions of the UMRB in the 21st century relative to the baseline period of 1960–1999. By the end of the 21st century, the original SWAT model predicted about a 50% increase in riverine nitrate loadings which is nearly twice as much as that estimated by SWAT-FT (ca. 25%). Such a large difference in projected nitrate changes can potentially mislead mitigation strategies that aim to reduce nitrogen runoff from the UMRB. Further analysis shows that the difference between the original SWAT model and SWAT-FT led to substantial discrepancies in the spatial distribution of surface and subsurface nitrate loadings in the UMRB. In general, SWAT-FT predicted more nitrate leaching for northwestern parts of the UMRB which are more sensitive to freeze-thaw cycle, mainly because SWAT-FT simulated less frequent frozen soils. This study highlights the importance of using physically based freeze-thaw cycle representation in water quality modeling. Design of future nitrogen runoff reduction strategies should include careful assessment of effects that land management has on the freeze-thaw cycles to provide reliable projection of water quality under climate change.

Wang, Qianfeng↗

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-Dimensional Projected-Momentum Covariance Mapping for Coulomb Explosion Imaging

We introduce projected-momentum covariance mapping, an extension of recoil-frame covariance mapping for 2D ion imaging studies. By considering the two-dimensional projection of the ion momenta as recorded by the detector, one opens the door to a complex suite of analysis tools adapted from three-dimensional momentum imaging studies. This includes the use of different frames of reference to unravel the dynamics of fragmentation and the application of fragment momentum constraints to isolate specific fragmentation channels. The technique is demonstrated on data from a two-dimensional ion imaging study of the Coulomb explosion of the cis and trans isomers of 1,2-dichloroethene, following strong-field ionization by an intense near-infrared femtosecond laser pulse. Classical simulations are used to guide the interpretation of projected-momentum covariance maps. The results offer a detailed insight into the distinct Coulomb explosion dynamics for this pair of isomers and lay the groundwork for future time-resolved studies of photoisomerization dynamics in this molecular system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

The Influence of Ocean Coupling on Simulated and Projected Tropical Cyclone Precipitation in the HighResMIP–PRIMAVERA Simulations

This study aims to quantify the impacts of atmosphere–ocean coupling on simulated and projected tropical cyclone (TC) precipitation globally. We used global climate model (GCM) simulations over 1950–2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere–ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC–ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015–2050 relative to 1950–2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections

Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with and without BC) to better understand the physical impacts of BC, applied before downscaling, on regional climate output across the western United States. Without BC, downscaled precipitation is systematically and unrealistically wet biased compared to a hierarchy of observationally based datasets over the 1980–2014 period due to cascading mean–state Global Climate Model (GCM) biases: (a) overly strong lower–tropospheric lapse rates (5 K/km), (b) overly cold (2 K) tropospheric temperatures, and (c) anomalous mid–tropospheric cyclonic vorticity advection. With BC, downscaled precipitation (snow) biases are virtually eliminated (halved). Identified GCM biases are common to the broader Coupled Model Intercomparison Project ensemble. Physical effects of BC on the quality of the regionalized projections, pending an evaluation of BC's distortion of the downscaled climate response, may motivate its broader application by dynamical downscalers.

54 ENVIRONMENTAL SCIENCES↗