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At least 1,171 records · Page 65

Roadmap on basic research needs for laser technology

Motivated by the profound impact of laser technology on science, arising from an increase in focused light intensity by seven orders of magnitude and flashes so short electron motion is visible, this roadmap outlines the paths forward in laser technology to enable the next generation of science and applications. Despite remarkable progress, the field confronts challenges in developing compact, high-power sources, enhancing scalability and efficiency, and ensuring safety standards. Future research endeavors aim to revolutionize laser power, energy, repetition rate and precision control; to transform mid-infrared sources; to revolutionize approaches to field control and frequency conversion. These require reinvention of materials and optics to enable intense laser science and interdisciplinary collaboration. The roadmap underscores the dynamic nature of laser technology and its potential to address global challenges, propelling progress and fostering sustainable development. Ultimately, advancements in laser technology hold promise to revolutionize myriad applications, heralding a future defined by innovation, efficiency, and sustainability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

encore : an O ( N g2) estimator for galaxy N -point correlation functions

ABSTRACT We present a new algorithm for efficiently computing the N-point correlation functions (NPCFs) of a 3D density field for arbitrary N. This can be applied both to a discrete spectroscopic galaxy survey and a continuous field. By expanding the statistics in a separable basis of isotropic functions built from spherical harmonics, the NPCFs can be estimated by counting pairs of particles in space, leading to an algorithm with complexity $\mathcal {O}(N_\mathrm{g}^2)$ for Ng particles, or $\mathcal {O}(N_\mathrm{FFT}\log N_\mathrm{FFT})$ when using a Fast Fourier Transform with NFFT grid-points. In practice, the rate-limiting step for N > 3 will often be the summation of the histogrammed spherical harmonic coefficients, particularly if the number of radial and angular bins is large. In this case, the algorithm scales linearly with Ng. The approach is implemented in the encore code, which can compute the 3PCF, 4PCF, 5PCF, and 6PCF of a BOSS-like galaxy survey in ${\sim}100$ CPU-hours, including the corrections necessary for non-uniform survey geometries. We discuss the implementation in depth, along with its GPU acceleration, and provide practical demonstration on realistic galaxy catalogues. Our approach can be straightforwardly applied to current and future data sets to unlock the potential of constraining cosmology from the higher point functions.

79 ASTRONOMY AND ASTROPHYSICS↗

Magnets for a Muon Collider—Needs and Plans

We describe the magnet challenges for a Muon Collider, an exciting option considered for the future of particle physics at the energy frontier. Starting from the comprehensive work performed by the US Muon Accelerator Program, we have reviewed the performance specifications dictated by beam physics and the operating conditions to satisfy the accelerator needs. Among the many magnets that make up a muon collider, we have identified four systems that represent well the envelope of challenges: the target and capture solenoid, the final cooling solenoid, the accelerator dipoles and the collider dipoles. These systems provide focus for the development of novel concepts, largely based on HTS for reasons of performance, cost and sustainability. After giving a consolidated overview of the needs for the magnet systems, we describe here the basic technology options considered, and the plan for design and development activities.

43 PARTICLE ACCELERATORS↗

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗

Continuous removal of fission products from molten-salt-fueled reactors

A method based on separation of volatilized molten salt (MS) components, including by mass, is being developed to extract fission products (FPs) from operating molten-salt reactors. The initial application of this method is for accelerator-driven subcritical reactors fueled by (fluorinated molten salt) spent nuclear fuel (UNF) from any past, present, or future reactor. The actinides remain in the subcritical reactor to produce profitable energy and be transmuted while the extracted FPs can be buried without long-lived actinides such that a geologic repository is not necessarily needed to close the nuclear fuel cycle. By removing neutron-absorbing FPs and operating sub-critically, where the restrictive link between operation and criticality is broken, it is possible to envision complete burnup of the UNF fuel. The game-changing feature of continuously processing the molten salt inside the reactor while the reactor operates eliminates the need for a separate reprocessing plant. This feature also simultaneously improves the neutronics of the reactor, increasing the burnup of the fuel and extending its useful life for generating energy. Nuclear nonproliferation and need for geologic repositories are addressed by keeping actinides inside the reactor containment until they are consumed. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data driven methods to recognize patterns in EIC weak-strong simulation

Beam-Beam simulations are currently being studied in preparation for future EIC experiments to study beam-beam effects and, in turn, maximize luminosity. Weak-strong methods are studied for single-particle dynamics during collision. 1 million macro-particles for 1 million turns are typically tracked, corresponding to only 10 seconds in the EIC. The goal of this study is to predict beam properties over the scale of hours. A potential solution focuses on using data-driven methods such as machine learning methods to analyze and extend the insights of the beam properties such as long-term nonlinear effects. This would aid in long-term predictions where results would be more efficiently acquired than a typical tracking simulation. Some limitations such as inaccurate predictions and spatial complexity are also discussed. These methods can then be applied to strong-strong simulations in the future studies.

Accelerator Physics↗

High Penetration of Photovoltaic Generation Study – Flagstaff Community Power (Final Technical Report, Results of Phases 2-5)

APS’s renewable energy portfolio, driven in part by Arizona’s Renewable Energy Standard (RES) currently includes more than 1100 MW of installed capacity, equating to roughly 3000 GWh of annual production. Overall renewable production is expected to grow to 6000 GWh by 2025. It is expected that distributed photovoltaics, driven primarily by lower cost, will contribute to much of this growth and that by 2025, distributed installations will account for half of all renewable production (3000GHW). As solar penetration increases, additional analysis may be required for routine utility processes to ensure continued safe and reliable operation of the electric distribution network. Such processes include residential or commercial interconnection requests and load shifting during normal feeder operations. Circuits with existing high solar penetration will also have to be studied and results will need to be evaluated for adherence to utility practices or strategy. Increased distributed PV penetration may offer benefits such as load offsetting, but it also has the potential to adversely impact distribution system operation. These effects may be exacerbated by the rapid variability of PV production. Detailed effects of these phenomena in distributed PV applications continue to be studied. Comprehensive, high-resolution electrical models of the distribution system were developed to analyze the impacts of PV on distribution circuit protection systems (including coordination and anti-islanding), predict voltage regulation and phase balance issues, and develop volt/VAr control schemes. Modeling methods were refined by validating against field measurements. To augment the field measurements, methods were developed to synthesize high resolution load and PV generation data to facilitate quasi-static time series simulations. The models were then extended to explore boundary conditions for PV hosting capability of the feeder and to simulate common utility practices such as feeder reconfiguration. The modeling and analysis methodology was implemented using open source tools and a process was developed to aid utility engineers in future interconnection requests. Methods to increase PV hosting capacity were also explored during the course of the study. A 700kVA grid-supportive inverter was deployed on the feeder and each grid support mode was demonstrated. Energy storage was explored through simulation and models were developed to calculate the optimum size and placement needed to increase PV hosting capacity. A tool was developed to aid planners in assigning relative costs and benefits to various strategies for increasing PV hosting capacity beyond current levels. Following the completion of the project, APS intends to use the tools and methods to improve the framework of future PV integration on its system. The tools and methods are also expected to aid other utilities to accelerate distributed PV deployment.

14 SOLAR ENERGY↗

2022 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report documents the eighth edition of the annual Standard Scenarios. It summarizes 70 forward-looking scenarios of the U.S. electricity sector that have been designed to capture a wide range of possible futures. In August 2022, the United States Congress passed the Inflation Reduction Act (IRA), a law aimed at accelerating U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. This year’s scenarios include representations of the main electricity-sector provisions from IRA and the potential impact on electricity demand. The Standard Scenarios are simulated using the Regional Energy Deployment System (ReEDS) model, which projects utility-scale electricity sector evolution for the contiguous United States using a system-wide, least-cost approach subject to policy and operational constraints. A subset of the scenarios are simulated in the PLEXOS production cost model to obtain a broader suite of metrics at the hourly resolution, which are made available through the National Renewable Energy Laboratory’s (NREL’s) annual Cambium data sets. The scenarios can be viewed and downloaded from NREL’s Scenario Viewer. Annual results are available for the full suite of scenarios in the Standard Scenarios projects in the viewer, whereas the Cambium projects contain hourly data for a subset of scenarios. The Standard Scenarios includes a scenario called the Mid-case, which has central or median values for core inputs such as technology costs and fuel prices, moderately paced demand growth averaging 1.3% per year, and electricity sector policies as they existed in September 2022 (including IRA). The remaining 69 scenarios are created by varying inputs such as technology and fuel prices, resource availability, demand growth, whether nascent generation technologies are allowed, and by introducing national decarbonization constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗

Fluid/chemistry modeling for hypersonic flight analysis

Design studies are underway for a variety of hypersonic flight vehicles. The National Aero-Space Plane will provide a reusable, single-stage-to-orbit capability for routine access to low earth orbit. Flight-capable satellites will dip into the atmosphere to maneuver to new orbits, while planetary probes will decelerate at their destination by atmospheric aerobraking. To supplement limited experimental capabilities in the hypersonic regime, computational fluid dynamics is being used to analyze the flow about these configurations. The governing equations include fluid dynamic as well as chemical species equations, which are being solved with new, robust numerical algorithms. Examples of CFD applications to hypersonic vehicles suggest an important role this technology will play in the development of future aerospace systems. The computational resources needed to obtain solutions are large, but solution-adaptive grids, convergence acceleration, and parallel processing may make run times manageable.

Edwards, Thomas A.↗

The effects of history and predictive information on the ability of the transport aircraft pilot to predict an alert

The early detection of a developing aircraft-subsystem fault has the potential to lessen its ultimate severity. The lack of capability for such early detection is becoming critical in the aviation community. In the commercial sector, for example, twin-engine aircraft are being used for extended transport operations over water. One method to decrease the severity of a developing problem is to predict its behavior and to take appropriate corrective action. In order to investigate pilots' ability to predict events, an experiment was conducted where eighteen airline pilots predicted the time to an alert using three different displays of dials and three different time profile complexities. The three displays of dials were as follows: standard, resembling current aircraft dial presentations; history, indicating the value five seconds in the past; and predictive, indicating the value five seconds into the future. The time profiles describing the behavior of the parameter consisted of constant velocity profiles, decelerating profiles, and accelerating then decelerating profiles. Although pilots indicated that they preferred the predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.

Trujillo, Anna C.↗

NASA and Education

President Bush endorsed a package of six goals developed by the governors of the 50 states, among them making the United States first in the world in mathematics and science achievement. The crux of the technical manpower problem is that too few people in the workforce today have the skills required to function in a technologically advanced society. All over the U.S., government, industry and academic organizations, individually and in concert, at the national, state and local levels, are accelerating efforts to find remedies for the educational and training maladies that threaten America's scientific and technological future. NASA is among the leading education promoting organizations and the agency is expanding its effort. In May 1990, NASA and the Department of Energy concluded an agreement for a cooperative program directed at encouraging more U.S. students to pursue careers in science, engineering and mathematics, and at improving the instructional process in those areas at the precollege and university levels.

Source record↗

The Impact of Geoengineering Aerosols on Stratospheric Temperature and Ozone

Anthropogenic greenhouse gas emissions are warming the global climate at an unprecedented rate. Significant emission reductions will be required soon to avoid a rapid temperature rise. As a potential interim measure to avoid extreme temperature increase, it has been suggested that Earth's albedo be increased by artificially enhancing stratospheric sulfate aerosols. We use a 3D chemistry climate model, fed by aerosol size distributions from a zonal mean aerosol model, to simulate continuous injection of 1-10 Mt/a into the lower tropical stratosphere. In contrast to the case for all previous work, the particles are predicted to grow to larger sizes than are observed after volcanic eruptions. The reason is the continuous supply of sulfuric acid and hence freshly formed small aerosol particles, which enhance the formation of large aerosol particles by coagulation and, to a lesser extent, by condensation. Owing to their large size, these particles have a reduced albedo. Furthermore, their sedimentation results in a non-linear relationship between stratospheric aerosol burden and annual injection, leading to a reduction of the targeted cooling. More importantly, the sedimenting particles heat the tropical cold point tropopause and, hence, the stratospheric entry mixing ratio of H2O increases. Therefore, geoengineering by means of sulfate aerosols is predicted to accelerate the hydroxyl catalyzed ozone destruction cycles and cause a significant depletion of the ozone layer even though future halogen concentrations will be significantly reduced.

Heckendorn, P.↗

The Impact of Geoengineering Aerosols on Stratospheric Temperature and Ozone

Anthropogenic greenhouse gas emissions are warming the global climate at an unprecedented rate. Significant emission reductions will be required soon to avoid a rapid temperature rise. As a potential interim measure to avoid extreme temperature increase, it has been suggested that Earth's albedo be increased by artificially enhancing stratospheric sulfate aerosols. We use a 3D chemistry climate model, fed by aerosol size distributions from a zonal mean aerosol model. to simulate continuous injection of 1-10 Mt/a into the lower tropical stratosphere. In contrast to the case for all previous work, the particles are predicted to grow to larger sizes than are observed after volcanic eruptions. The reason is the continuous supply of sulfuric acid and hence freshly formed small aerosol particles, which enhance the formation of large aerosol particles by coagulation and, to a lesser extent, by condensation. Owing to their large size, these particles have a reduced albedo. Furthermore, their sedimentation results in a non-linear relationship between stratospheric aerosol burden and annual injection, leading to a reduction of the targeted cooling. More importantly, the sedimenting particles heat the tropical cold point tropopause and, hence, the stratospheric entry mixing ratio of H2O increases. Therefore, geoengineering by means of sulfate aerosols is predicted to accelerate the hydroxyl catalyzed ozone destruction cycles and cause a significant depletion of the ozone layer even though future halogen concentrations will he significantly reduced.

Heckendorn, P.↗

Development of a Refined Space Vehicle Rollout Forcing Function

For several decades, American manned spaceflight vehicles and the associated launch platforms have been transported from final assembly to the launch pad via a pre-launch phase called rollout. The rollout environment is rich with forced harmonics and higher order effects can be used for extracting structural dynamics information. To enable this utilization, processing tools are needed to move from measured and analytical data to dynamic metrics such as transfer functions, mode shapes, modal frequencies, and damping. This paper covers the range of systems and tests that are available to estimate rollout forcing functions for the Space Launch System (SLS). The specific information covered in this paper includes: the different definitions of rollout forcing functions; the operational and developmental data sets that are available; the suite of analytical processes that are currently in-place or in-development; and the plans and future work underway to solve two immediate problems related to rollout forcing functions. Problem 1 involves estimating enforced accelerations to drive finite element models for developing design requirements for the SLS class of launch vehicles. Problem 2 involves processing rollout measured data in near real time to understand structural dynamics properties of a specific vehicle and the class to which it belongs.

James, George↗

Predicting Patterns of Solar Energy Buildout to Identify Opportunities for Biodiversity Conservation

The construction of solar energy facilities can have positive or negative impacts on biodiversity depending on siting and associated land use transitions. We identified drivers of solar siting and quantified patterns of buildout in states surrounding the Chesapeake Bay watershed – a biodiversity hotspot with numerous ecosystem services. Using a convolutional neural network, we mapped the footprints of ground-mounted solar arrays present in satellite imagery annually from 2017 to 2021 in Delaware, Maryland, Pennsylvania, New York, Virginia, and West Virginia. As of 2021, we identified 958 solar arrays covering 52.3 km2 built primarily on previously cultivated land, while avoiding natural landcover. We fit a binomial-Weibull model to these solar timeseries data in a hierarchical, Bayesian framework to quantify the relationship between geospatial covariates and rate of solar development. Solar array construction rate increased in cultivated areas, areas of lower agricultural suitability, lower slope, lower forest cover, lower biodiversity protection, and greater distances from roads. We also estimated changes in the rate of solar construction over time and found differences among states: acceleration in Virginia and deceleration in New York. We used parameter estimates to map the relative likelihood of future solar development across the study area. This methodology can be used to anticipate where solar is likely to be built in different landscapes and how these patterns align with conservation goals. Around the Chesapeake Bay watershed, the selection of lower quality agricultural areas for solar energy minimizes removal of important habitat and provides opportunities for native plant and pollinator restoration.

Artificial Intelligence↗

Behaviors of Lunar Regolith Simulant Under Varying Gravitational Conditions

Understanding the behavior of regolith in varying gravity conditions is critical for space exploration and future missions. In this work, the gravity-driven hopper flow of lunar regolith simulant in different gravitational accelerations (terrestrial, lunar) is first observed experimentally. Numerical simulations (DEM) are then developed to understand the role which cohesive inter-particle forces play in such gravity-driven flow, using the theoretical framework of granular Bond number. Qualitative comparison between a terrestrial experiment and numerical simulation validated this framework. Following that, we numerically studied the dynamic behavior under varying gravitational conditions (from terrestrial to lunar to asteroid gravitational accelerations). We find that this behavior is extremely sensitive to the interplay of the gravity conditions and the attractive/cohesive forces among particles. The numerical and experimental results show that the complex interaction of these forces can drastically change the dynamics of the material producing effects relevant for variable gravity applications.

Soft Matter↗