The Evolution of a Space Feeding Concept for Project Gemini
Space feeding concept for Gemini and Apollo projects as developed in Mercury project
SPACE FLIGHT FEEDING↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A Suggestion for Extension of the NASA RANGER Project in Support of Manned Space Flight
Proposal for utilizing Ranger project in support of Surveyor and Apollo projects
SURVEYOR PROJECT↗
Modeling the impact of measured and projected climate and management systems on agricultural fields: Surface runoff, soil moisture, and soil erosion
Abstract As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW‐CT; baseline system), (2) continuous winter wheat under no‐till (WW‐NT), and (3) cool and warm season forage cover crop mixes under no‐till (CC‐NT). The study indicates that the occurrence of agricultural drought is projected to increase while erosion rates will remain unchanged under the WW‐CT. In contrast, climate simulations imposed on the WW‐NT and CC‐NT systems significantly reduce runoff and sediment while preserving soil moisture levels. Especially, implementing the CC‐NT system can bolster food security and foster sustainable farming practices in Central Oklahoma in the face of a changing climate.
Environmental Sciences & Ecology↗
Roles of the atmosphere and ocean in the projected north atlantic warming hole
There exists a warming deficit in sea surface temperatures (SST) over the subpolar North Atlantic in response to quadrupled CO 2 , referred to as the projected North Atlantic warming hole (WH). This study employs a partial coupling technique to accurately verify the relative roles of oceanic and atmospheric processes in the formation of the projected WH within an atmosphere-ocean coupled framework. By decomposing the SST anomalies in the subpolar North Atlantic into two components: those induced by atmospheric processes (i.e., the atmosphere-forced component) and those driven by changes in ocean circulation (i.e., the ocean-driven component), we find that the projected WH is primarily driven by changes in ocean circulation, with almost no contribution from atmospheric processes. Specifically, the slowdown of the Atlantic Meridional Overturning Circulation (AMOC) results in a cooling of SST in the WH region due to reduced northward ocean heat transport into this region. This study further quantifies the influence of a positive coupled feedback through surface heat flux (SHF) on the AMOC response under greenhouse gas forcing within this self-consistent framework. It is found that the AMOC slowdown leads to a negative SST anomaly in the subpolar North Atlantic and subsequently a positive ocean-driven SHF anomaly, which in turn further weakens the AMOC. In conclusion, this positive feedback through the SHF contributes about 50% to the total AMOC slowdown in response to quadrupled CO 2 .
54 ENVIRONMENTAL SCIENCES↗
Climate models project increasing precipitation in the US Southwest in 2024–2100
We analyzed the measured precipitation in the southwestern US and found that, from 1900 to 2024, precipitation decreased at an average rate of − 1.2 cm per year per 100 years. The most significant precipitation decreases occurred in the three-month period from February to April. At the same time, precipitation during the southwestern monsoon season (July, August, and September) remained relatively stable. The ensemble mean of all CMIP6 (Coupled Model Intercomparison Project phase 6) climate models, along with the regression model incorporating anthropogenic aerosol (AER) and Pacific Decadal Oscillation (PDO) as predictors, projects precipitation to increase from 2024 to 2100. This projected precipitation increase relies on the anticipated decrease in emissions of anthropogenic aerosols, which is associated with the transition from fossil fuel burning to renewable and nuclear energy sources.
54 ENVIRONMENTAL SCIENCES↗
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↗
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↗
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↗
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↗
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↗
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↗
Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project
The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land-atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio-temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO 2 , climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote-sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO 2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (–0.58 ± 0.54 PgC/yr). Forests and semi-arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi-arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (–1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land-atmosphere exchange is simulated in the extratropical regions.
58 GEOSCIENCES↗
A Novel Framework to Project the Permafrost Fate With Explicit Quantification of Soil Property and Future Climate Uncertainties
This study develops a novel general framework to project the permafrost fate with rigorous uncertainty quantification to assess dominant sources. Borehole temperature records from three sites in the Russian western Arctic are used to constrain the uncertainty of a high‐fidelity freeze‐thaw model. Projections from 9 Global Climate Models (GCM) are stochastically downscaled to generate future trajectories of surface ground heat flux. Under the two emission scenarios SSP2‐4.5 and SSP5‐8.5, the projected average thawing depths by 2100 vary from 0.4 to 14.4 m or 2.1 to 17.7 m, and the increase in the top 10 m average temperature from 2015 to 2100 is 1.2–2.7°C or 1.9–3.0°C. The results show that the freeze‐thaw model uncertainty can sometimes dominate over that of GCM outputs, calling for site‐specific information to improve model accuracy. The framework is applicable for understanding permafrost degradation and related uncertainties at larger scales.
Bayesian downscaling↗
Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection
The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.
Mongird, Kendall↗
“Which Projections Do I Use?” Strategies for Climate Model Ensemble Subset Selection Based on Regional Stakeholder Needs
Climate model (or earth system model) projections are increasingly used for climate adaptation planning and impact assessments. As part of this process, many end‐users evaluate a subset of downscaled climate projections without being aware of the implications of downscaling methodology for statistics or event outcomes. Approaches for determining a subset of global climate models to use often focus on values from the raw models, rather than from their downscaled counterparts, in other words assuming that the statistical distribution of the multi‐model ensemble does not change post downscaling. This study demonstrates that a downscaled ensemble will typically retain the change distribution as a raw ensemble, but individual models can differ dramatically post‐downscaling. We recommend that subset‐selection methods account for this possibility and that decision‐relevant downscaled climate projections provide proper descriptions of fitness‐for‐purpose and essential caveats, so that non‐specialists can interpret the results with an appropriate level of confidence.
54 ENVIRONMENTAL SCIENCES↗
Assay-based background projection for the Majorana Demonstrator using Monte Carlo uncertainty propagation
The background index (BI) is an important quantity to project and calculate the half-life sensitivity of neutrinoless double-𝛽 decay (0𝜈𝛽𝛽) experiments. An analysis framework is presented to calculate the BI using the specific activities, masses, and simulated efficiencies of an experiments components as distributions. This Bayesian framework includes a unified approach to combine specific activities from assay. Monte Carlo uncertainty propagation is used to build a BI distribution from the specific activity, mass, and efficiency distributions. This method is applied to the M AJORANA D EMONSTRATOR , which deployed arrays of high-purity Ge detectors enriched in 76 Ge to search for 0𝜈𝛽𝛽. The original assay-based projection is requantified in the new framework, using the as-built geometry of the Demonstrator and additional assay information. While 47% higher than the original projection, the resulting BI of [8.95±0.36]×10 −4 cts/(keVkgyr) from the 232 Th and 238 U decay chains does not account for the higher-than-expected BI observed by the D EMONSTRATOR . Finally, this method enables us to demonstrate the statistical incompatibility between the D EMONSTRATOR 's observed background and the assay results.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Partial-wave projection of the one-particle exchange in three-body scattering amplitudes
As the study of three-hadron physics from lattice QCD matures, it is necessary to develop proper analysis tools in order to reliably study a variety of phenomena, including resonance spectroscopy and nuclear structure. Reconstructing the three-particle scattering amplitude requires solving integral equations, which can be written in terms of data-constrained dynamical functions and physical on shell quantities. The driving term in these equations is the so-called one-particle exchange, which leads to a kinematic divergence for particles on mass shell. A vital component in defining three-particle amplitudes with definite parity and total angular momentum, which are used in spectroscopic studies, is to project the one-particle exchange into definite partial waves. We present a general procedure to construct exact analytic partial-wave projections of the one-particle exchange contribution for any system composed of three spinless hadrons. Our result allows one full control over the analytic structure of the projection, which we explore for some low-lying partial waves with applications to three pions. Published by the American Physical Society 2024
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗