An image-based equation for estimating the prospective CO2 storage resource of organic-rich shale formations
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Azenkeng, Alexander↗
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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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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↗
The “Fresnel Equations” for Diffuse radiation on Inclined photovoltaic Surfaces (FEDIS)
Here the well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. The transmission of diffuse radiation incident on a planar or domed surface is often needed for real-world applications. Due to the complexity of the Fresnel equations, the analytical solution of the integration has hitherto been unobtainable over the last centuries. Therefore, this problem was numerically solved by integrating the angular transmittances in space often leading to substantial computing burden and bias in the results. To efficiently estimate the solar energy resource for a glass-covered photovoltaic (PV) module, we derive an analytical solution of diffuse transmission based on the rigorous integration of an alternate form of the Fresnel equations. The approach leads to a simple yet accurate relative transmittance model that reconciles the solar energy sensed by pyranometers and PV panels. With limited and clearly stated approximations, the complex mathematical derivation resulted in an elegant solution. An experiment using 1-year of data at the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) shows that the new model dramatically decreases the disparity between the solar radiation measurements by a Kipp and Zonen CM Pyranometer 22 (CMP22) and an IMT reference cell on a 1-axis tracking system. The solution in this paper can be widely used in scientific and engineering research, development, and applications wherever the Fresnel equations are used.
14 SOLAR ENERGY↗
Long-time simulations for fixed input states on quantum hardware
Publicly accessible quantum computers open the exciting possibility of experimental dynamical quantum simulations. While rapidly improving, current devices have short coherence times, restricting the viable circuit depth. Despite these limitations, we demonstrate long-time, high fidelity simulations on current hardware. Specifically, we simulate an XY-model spin chain on Rigetti and IBM quantum computers, maintaining a fidelity over 0.9 for 150 times longer than is possible using the iterated Trotter method. Our simulations use an algorithm we call fixed state Variational Fast Forwarding (fsVFF). Recent work has shown an approximate diagonalization of a short time evolution unitary allows a fixed-depth simulation. fsVFF substantially reduces the required resources by only diagonalizing the energy subspace spanned by the initial state, rather than over the total Hilbert space. We further demonstrate the viability of fsVFF through large numerical simulations, and provide an analysis of the noise resilience and scaling of simulation errors.
97 MATHEMATICS AND COMPUTING↗
FEDIS (The “Fresnel Equations” for Diffuse radiation on Inclined photovoltaic Surfaces) [SWR-22-64]
The well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. The transmission of diffuse radiation incident on a planar or domed surface is often needed for real-world applications. Due to the complexity of the Fresnel equations, the analytical solution of the integration has hitherto been unobtainable over the last centuries. Therefore, this problem was numerically solved by integrating the angular transmittances in space often leading to substantial computing burden and bias in the results. To efficiently estimate the solar energy resource for a glass-covered photovoltaic (PV) module, we derive an analytical solution of diffuse transmission based on the rigorous integration of an alternate form of the Fresnel equations. The approach leads to a simple yet accurate relative transmittance model that reconciles the solar energy sensed by pyranometers and PV panels. With limited and clearly stated approximations, the complex mathematical derivation resulted in an elegant solution.
Xie, Yu↗
Integrating Health and Energy Efficiency in Multi-Family Buildings
The intersection between health and the built environment has long been known. Since the 18 th century, public health officials have been targeting building issues, such as crowding, poor sanitation, and inadequate ventilation in efforts to reduce infectious diseases and fire hazards. More recently, federal agencies, such as the U.S. Environmental Protection Agency (EPA), the Centers for Disease Control and Prevention, HUD, and the DOE have been working to reduce or eliminate indoor building factors that are known to have adverse health impacts on Americans, including reducing lead in housing and indoor air pollution that causes respiratory disease, and ensuring access to adequate heating, cooling, and moisture control. PNNL, in support of FEMP’s HBI, undertook a review of literature and existing best practices to identify current activities and research on the intersection between traditional energy-efficiency measures and occupant health within multi-family buildings. While the HBI methodology has focused on traditional office building spaces, it is now expanding into additional building use types. This overview explores some of the most impactful resources to help property owners and managers understand more about multi-family residential buildings that are both healthy and energy efficient. The federal government provides direct oversight and operation across several types of multi-family residential housing, including dormitories, barracks, and senior community living centers.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
One Million Open-source Cislunar Orbits
Cislunar space, encompassing the region from geosynchronous orbit to beyond the Moon, is poised to become a cornerstone for future exploration, scientific discovery, and national security. Missions in this region, spanning durations from weeks to decades, require robust infrastructure and reliable transit capabilities. The complex gravitational influences of the Moon, Sun, and planets, along with thermal radiation from Earth and the Sun, lead to significant trajectory deviations, resulting in kilometer-scale errors within days. Leveraging the high-performance computing resources at Lawrence Livermore National Laboratory (LLNL), we have simulated one million high-fidelity cislunar trajectories, now publicly available via LLNL’s Green Data Oasis and the Unified Data Library. Generated using the open-source Space Situational Awareness Python package, these trajectories match the precision of commercial tools such as AGI’s Systems Tool Kit and NASA’s General Mission Analysis Tool. This data set is a valuable resource for reference, statistical analysis of cislunar orbit populations, and training machine learning models for rapid orbit classification with minimal observational input. Preliminary analysis reveals stable bands in Keplerian element space, particularly around five geosynchronous radii across a range of inclinations and eccentricities. Beyond this threshold, the Moon’s influence disrupts most unassisted orbits, though co-orbiting L4/L5 Lunar Trojans persist throughout the six-year simulation.
Astronomy and AstroPhysics↗
Quantum simulations of SO(5) many-fermion systems using qudits
The structure and dynamics of many-body systems are the result of a delicate interplay between underlying interactions. Fermionic pairing, for example, plays a central role in various physical systems, ranging from condensed matter to nuclear systems, where it can lead to collective phenomena such as superconductivity and superfluidity. In atomic nuclei, the interplay between pairing and particle-hole interactions leads to a high degree of complexity and intricate entanglement structures. Despite this apparent complexity, symmetries emerge and manifest themselves in observable regular patterns. These symmetries and their breakings have long been used to determine relevant degrees of freedom and simplify classical descriptions of many-body systems. Here, this work explores the potential utility of quantum computers with arrays of qudits in simulating interacting fermionic systems, when the qudits can naturally map the relevant degrees of freedom determined by an underlying symmetry group. The Agassi model of fermions interacting via particle-hole and pairing interactions is based on an underlying so(5) algebra. Such systems can intuitively be partitioned into pairs of modes with five basis states, which thus naturally map to arrays of d = 5 qudits (qu5its). Classical noiseless simulations of the time evolution of systems with up to twelve qu5its are performed, by implementing quantum circuits that are developed herein, using PYTHON codes invoking Google's CIRQ software. The resource requirements of the qu5it circuits are analyzed and compared with two different mappings to qubit systems: a physics-aware Jordan-Wigner mapping requiring four qubits per mode pair and a state-to-state mapping requiring three qubits per mode pair. While the dimensionality of Hilbert spaces in mappings to qu5it systems are less than those for the corresponding qubit systems, the number of entangling operations, depending on the available hardware, can either be greater or smaller than for the physics-aware Jordan-Wigner mapping. The state-to-state mapping, while having a smaller Hilbert space than Jordan-Wigner mappings, appears to be the least efficient in gate counts. Further, a previously unknown sign problem has been identified from Trotterization errors in time evolving high-energy excitations. There appear to be advantages in employing quantum computers with arrays of qudits to perform simulations of many-body dynamics that exploit the role of underlying symmetries, specifically in lowering the required quantum resources and in reducing anticipated errors that take the simulation out of the physical space. If the necessary entangling gates are not directly supported by the hardware, physics-aware mappings to qubits may, however, be advantageous for other aspects.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning
We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.
Geophysics↗
RCSB Protein Data Bank 1D tools and services
Abstract Motivation Interoperability between polymer sequences and structural data is essential for providing a complete picture of protein and gene features and helping to understand biomolecular function. Results Herein, we present two resources designed to improve interoperability between the RCSB Protein Data Bank, the NCBI and the UniProtKB data resources and visualize integrated data therefrom. The underlying tools provide a flexible means of mapping between the different coordinate spaces and an interactive tool allows convenient visualization of the 1-dimensional data over the web. Availabilityand implementation https://1d-coordinates.rcsb.org and https://rcsb.github.io/rcsb-saguaro. Supplementary information Supplementary data are available at Bioinformatics online.
59 BASIC BIOLOGICAL SCIENCES↗
Incremental Threshold Scheme Enabled IoT Group Key Management
Cyber landscape evolves rapidly. Internet of Things (IoT) and Edge Computing (EC) have rapidly become an integral part of the modern computing infrastructure. It is expected that there will be more than 50 billion active and connected IoT devices by 2025 [1]. Pervasive IoT/EC creates unprecedented opportunities bridging the gap between previously segregated cyber and physical spaces. However, this progress also brings along new security challenges. IoT devices typically have limited computation, communication, and storage resources. This leads to security architecture designs such as using symmetric keys for group communication. While secure and efficient in stable network settings, symmetric key solutions are ill-adapted for IoT's highly dynamic device mobility behavior and frequent group membership turnover. Whenever IoT members leave a group, the known symmetric keys cannot be made forgotten, posing a serious vulnerability. This leads to frequent re-groupings that require expensive re-authentication, key regeneration, and key redistribution in order to maintain IoT/EC security. We present a novel symmetric key management framework that integrate an Incremental Threshold Scheme (ITS) cryptographical function into communication protocol's key rotation mechanism to allow for secure and efficient symmetric key communication group member node revocation. This ITS-enabled key management framework alleviates the need of frequent and expensive re-grouping and re-keying needed by today's large and dynamic IoT/EC operations. We further applied this ITS-enabled key management framework to a distributed IoT/EC-integrated publish and subscribe framework for applicability validation.
Li, Mingyan↗
Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing
A coloring of a graph is an assignment of colors to vertices such that no two neighboring vertices have the same color. The need for memory-efficient coloring algorithms is motivated by their application in computing clique partitions of graphs arising in quantum computations where the objective is to map a large set of Pauli strings into a compact set of unitaries. We present Picasso, a randomized memory-efficient iterative parallel graph coloring algorithm with theoretical sublinear space guarantees under practical assumptions. The parameters of our algorithm provide a trade-off between coloring quality and resource consumption. To assist the user, we also propose a machine learning model to predict the coloring algorithm’s parameters considering these trade-offs. We provide a sequential and a parallel implementation of the proposed algorithm. We perform an experimental evaluation on a 64-core AMD CPU equipped with 512 GB of memory and an Nvidia A100 GPU with 40GB of memory. For a small dataset where existing coloring algorithms can be executed within the 512 GB memory budget, we show up to 68× memory savings. On massive datasets we demonstrate that GPU-accelerated Picasso can process inputs with 49.5× more Pauli strings (vertex set in our graph) and 2,478× more edges than state-of-the-art parallel approaches.
artificial intelligence, quantum computing↗
Evaluation of Modular and Scalable Downstream Passage Systems for Silver American Eels
Implementation of effective downstream passage for silver-phase American Eel (Anguilla rostrata) at hydropower dams using methods that are economically feasible has been a challenge for many project owners. Due to the potential for high mortality rates during turbine passage, resource agencies have focused on mandatory prescriptions that prevent entrainment by physically excluding eels (i.e., narrow trash rack bar spacing) or eliminating turbines as a passage route (i.e., unit shutdowns at night when eel movement is greatest). Both of these options can significantly impact the economic viability of a project. Consequently, there is a need for alternative technologies that can provide safe and effective downstream passage for silver eels without having a major impact on the ability of a project to generate power during the eel downstream migration period. This need is of particular concern now because about 300 hydropower projects within the range of American Eel freshwater habitats are scheduled to be relicensed by the Federal Energy Regulatory Commission (FERC) in the next 15 years
13 HYDRO ENERGY↗
Closure models for the feedback of energetic particles on plasma turbulence
Energetic particles interact with the plasma surrounding them, resonating with certain types of plasma waves to stabilize them while destabilizing others, and changing the character of the background turbulence in ways that have not been fully quantified or understood. Interaction with the turbulent background plasma is key to the acceleration of many types of energetic particles including high-energy cosmic rays, solar energetic particles, and pick-up ions. The acceleration of particles is a process that would ideally be described by a kinetic model, a type of model that follows a probability distribution function (PDF) for all particles in 7-dimensional (x, y, z, v x , v y , v z , t) space. Because of the high dimensionality of a kinetic model, simulations that solve kinetic equations use the largest computational resources currently available, and are yet unable to simulate a realistic number of particles, reach the large scales necessary for astrophysical problems, and use high-precision numerical methods. Two available alternatives to kinetic plasma models have been explored for this problem, with limited success. One is a multi-fluid model produced by a cumulant discarding closure, which evolves coupled equations for the velocity, magnetic field, and internal energy for both the background plasma and the fluid of energetic particles. However, simulations that solve multi-fluid magnetohydrodynamic (MHD) equations are able to include the interaction with energetic particles only in crude ways, typically as an add-on pressure term. The second alternative is to use a hybrid method to couple a fluid description of the background plasma to a kinetic model or a Fokker–Planck model for the energetic particles. These methods are hampered by the physical modeling of the coupling. In this work, we develop a new model, which follows the PDF for all particles; this can be viewed as a step toward physical realism above a multi-fluid MHD model, while also being more computationally efficient than a kinetic model. The equations we develop model both the background plasma and the energetic particles self-consistently. Over the last decade, similar PDF methods have been developed to a high level of sophistication to model reactive flows and turbulent combustion for engineering applications. For treatment of the feedback of the energetic particles on a background plasma, a PDF closure approach should evaluate the mean characteristics, including the density, with better statistical quality than will particle-sampling procedures.
79 ASTRONOMY AND ASTROPHYSICS↗
Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment
This paper presents updated Monte Carlo configurations used to model the production of single electroweak vector bosons (W, Z/γ$^{∗}$) in association with jets in proton-proton collisions for the ATLAS experiment at the Large Hadron Collider. Improvements pertaining to the electroweak input scheme, parton-shower splitting kernels and scale-setting scheme are shown for multi-jet merged configurations accurate to next-to-leading order in the strong and electroweak couplings. The computational resources required for these set-ups are assessed, and approximations are introduced resulting in a factor three reduction of the per-event CPU time without affecting the physics modelling performance. Continuous statistical enhancement techniques are introduced by ATLAS in order to populate low cross-section regions of phase space and are shown to match or exceed the generated effective luminosity. This, together with the lower per-event CPU time, results in a 50% reduction in the required computing resources compared to a legacy set-up previously used by the ATLAS collaboration. The set-ups described in this paper will be used for future ATLAS analyses and lay the foundation for the next generation of Monte Carlo predictions for single vector-boson plus jets production.[graphic not available: see fulltext]
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Historical Bolide Infrasound Dataset (1960–1972)
We present the first fully curated, publicly accessible archive of infrasonic records from ten large bolide events documented by the U.S. Air Force Technical Applications Center’s global microbarometer network between 1960 and 1972. Captured on analog strip-chart paper, these waveforms predate modern digital arrays and space-based sensors, making them a unique window on meteoroid activity in the mid-twentieth century. Prior studies drew important scientific conclusions from the records but released only limited artifacts, chiefly period–amplitude tables and unprocessed scans, leaving the underlying data inaccessible for independent study. The present release transforms those limited excerpts into a research-ready resource. By capturing ten large events in the mid-20th century, the dataset constitutes a critical reference point for assessing bolide activity before the advent of modern space-based and digital ground-based monitoring. The multi-year coverage and worldwide distribution of events provide a valuable reference for comparing past and more recent detections, facilitating assessments of long-term flux and the dynamics of acoustic wave propagation in Earth’s atmosphere. The dataset’s availability in a consolidated format ensures straightforward access to waveforms and derived measurements, supporting a wide range of scientific inquiries into bolide physics and infrasound monitoring. By preserving these historical acoustic observations, the collection maintains a significant record of mid-20th-century meteoroid entries. It thereby establishes a basis for further refinement of impact hazard evaluations, contributes to historical continuity in atmospheric observation, and enriches the study of meteoroid-generated infrasound signals on a global scale.
79 ASTRONOMY AND ASTROPHYSICS↗
A Review of Infrasound and Seismic Observations of Sample Return Capsules since the End of the Apollo Era in Anticipation of the OSIRIS-REx Arrival
Advancements in space exploration and sample return technology present a unique opportunity to leverage sample return capsules (SRCs) towards studying atmospheric entry of meteoroids and asteroids. Specifically engineered for the secure transport of valuable extraterrestrial samples from interplanetary space to Earth, SRCs offer unexpected benefits that reach beyond their intended purpose. As SRCs enter the Earth’s atmosphere at hypervelocity, they are analogous to naturally occurring meteoroids and thus, for all intents and purposes, can be considered artificial meteors. Furthermore, SRCs are capable of generating shockwaves upon reaching the lower transitional flow regime, and thus can be detected by strategically positioned geophysical instrumentation. NASA’s OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) SRC is one of only a handful of artificial objects to re-enter the Earth’s atmosphere from interplanetary space since the end of the Apollo era and it will provide an unprecedented observational opportunity. This review summarizes past infrasound and seismic observational studies of SRC re-entries since the end of the Apollo era and presents their utility towards the better characterization of meteoroid flight through the atmosphere.
79 ASTRONOMY AND ASTROPHYSICS↗
Evaluation of hybrid evaporative-vapor compression air conditioners for different global climates
Currently, a majority of global residential air-conditioning requirements are met using cooling systems based on the vapor compression cycle (VCC). To meet the future demand for space cooling and to reduce the corresponding environmental impact, there is a need for alternative cooling systems which require less resources and exhibit a higher coefficient of performance (COP). One of proposed alternatives is called the hybrid evaporative-vapor compression (HEVC) cycle, which utilizes adiabatic latent cooling in combination with the VCC. In this paper, we conducted a feasibility analysis of a HEVC system by comparing its performance to that of VCC for various global climates. To accomplish this, we developed and validated models to simulate the performance of residential VCC and HEVC systems. ASHRAE weather data and design conditions were then used to compare the performance of the two systems. In general, HEVC systems are best suited for hot arid climates with energy reduction greater than 20%. Conversely, humid climates are not suitable for HEVC adoption due to degraded performance of evaporative coolers in these climates. In addition to comparing the energy savings from HEVC systems, it is also critical to analyze their water consumption. Generally, climates that benefit the most from HEVC technology tend to also experience water scarcity issues. Thus, both the energy savings and water consumption of HEVC systems must be analyzed to guide the discussion on their adoption.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗