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At least 55 records · Page 3

ACE Objectives, Current Status and the 2017 Decadal Survey

In this talk we present an overview of the Aerosol-Cloud-Ecosystems (ACE) preformulation studies, a tier-2 satellite mission recommended by the 2007 Decadal Survey. We discuss the current status of ACE measurement concepts and associated retrieval algorithms. We conclude with a brief discussion of the recommendations by the 2017 Decadal Survey and how ACE accomplishments can inform the future Aerosol and Cloud, Convection & Precipitation Designated Observables.

ACE↗

Progress of the NASA ACE Mission Polarimeter Working Group Instrument Inter-Comparison

The NASA Aerosol-Cloud-Ecosystem (ACE) mission is a National Research Council Decadal Survey recommended mission that will contain an imaging polarimeter for remote sensing of aerosols and clouds. A variety of airborne polarimeter prototypes exist, so the ACE Polarimeter Working Group (ACEPWG) was formed to share information between groups and collectively work for improved measurement techniques, uncertainty characterization, and algorithm development. The initial focus has been on observations made during the Polarimeter Definition Experiment (PODEX), conducted in early 2013 in Southern California. Three ACE mission supported polarimeters were deployed on the high altitude ER-2 aircraft as it flew over a variety of targets. Two of those instruments to date have successfully produced Level 1 (geolocated radiance and polarization) data. Initial matched scene inter-comparisons found little radiometric, but significant polarimetric, bias. After improvement to geolocation in one instrument, and calibration in the other, polarimetric comparisons have improved significantly. We will describe these results, remaining unresolved issues, and future plans.

Polarimeter↗

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Scalable Hyperpolarized MRI Enabled by Ace‐SABRE of [1‐ 13 C]Pyruvate

Abstract Hyperpolarized (HP) MRI using [1– 13 C]pyruvate is emerging as a promising molecular imaging approach. Among hyperpolarization methods, Signal Amplification By Reversible Exchange (SABRE) is attractive because SABRE polarizes the substrates directly in room‐temperature solutions avoiding complex hardware. Most SABRE experiments have historically been performed in methanol, a relatively toxic and difficult‐to‐remove solvent. Here we demonstrate the use of a 80/20 acetone/water (A/W) solvent system (Ace‐SABRE) to provide hyperpolarized [1– 13 C]pyruvate with up to 17% polarization, then implement a solvent processing protocol to achieve injectable solutions retaining 74% of the initial polarization, and lastly we demonstrate HP in vivo spectroscopy and imaging using the Ace‐SABRE platform to showcase metabolic tracking in a hepatocellular carcinoma (HCC) tumor as well as HP‐MRI, both in direct comparison to dissolution dynamic nuclear polarization (d‐DNP) experiments. The Ace‐SABRE technique promises faster adoption of SABRE hyperpolarization in biological experiments, overall lowering the barriers to entry for HP‐NMR and HP‐MRI.

Chemistry↗

ACES-GNN: can graph neural network learn to explain activity cliffs?

Graph Neural Networks (GNNs) have revolutionized molecular property prediction by leveraging graph-based representations, yet their opaque decision-making processes hinder broader adoption in drug discovery. This study introduces the Activity-Cliff-Explanation-Supervised GNN (ACES-GNN) framework, designed to simultaneously improve predictive accuracy and interpretability by integrating explanation supervision for activity cliffs (ACs) into GNN training. ACs, defined by structurally similar molecules with significant potency differences, pose challenges for traditional models due to their reliance on shared structural features. By aligning model attributions with chemist-friendly interpretations, the ACES-GNN framework bridges the gap between prediction and explanation. Validated across 30 pharmacological targets, ACES-GNN consistently enhances both predictive accuracy and attribution quality for ACs compared to unsupervised GNNs. Our results demonstrate a positive correlation between improved predictions and accurate explanations, offering a robust and adaptable framework to better understand and interpret ACs. This work underscores the potential of explanation-guided learning to advance interpretable artificial intelligence in molecular modeling and drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ACES: Infrastructure As Code. Model Optimization and Performance Capability

Infrastructure as Code (IaC) refers to managing infrastructure (networks, physical/virtual machines, storage, and connection topology) in a descriptive model/language, rather than configuring it manually or using interactive configuration tools. Just like source code can be compiled to generate the same binary code, IaC enables generating the same environment every time it is applied. IaC is a key DevOps practice and is generally used in conjunction with continuous integration (CI) and continuous delivery (CD). In CI, all code changes are merged into a mainline branch and validated multiple times a day as developers check in their changes to the source code. In CD on the other hand, code changes are automatically packaged for a new release-to-production on a regular basis. This typically enables teams to deliver software changes much more quickly and often. Developing and managing the ACES platform using (IaC) is vital for the robust deployment and continued sustainment of this foundational computing capability. IaC and DevOps practices will help us solve many of the common challenges often encountered in developing and maintaining compute infrastructure. First, it will make the provisioning, deployment, and maintenance of the compute infrastructure across multiple environments much more efficient. Second, these processes help make the overall system much more stable by continuously testing new changes as they are introduced to the system. Third, it allows us to be much more confident of the security controls in place since they can be tested as part of the CI process and all new changes can be audited and tracked. Finally, IaC enables the ACES Platform to be adaptable to the emerging technologies due to its ability to spin up different test beds to evaluate and incorporate these technologies. This document addresses common infrastructure-management challenges, describes what happens if they are not addressed, and highlights the value of utilizing IaC to tackle them. Finally, we will provide a high-level overview of the IaC and DevOps practices being utilized by the ACES Platform team.

97 MATHEMATICS AND COMPUTING↗

Release of ENDF/B-VIII.1β1-Based ACE Data Files

On March 1 st , 2023, the National Nuclear Data Center (NNDC) released the ENDF/B-VIII.1β1 nuclear data library, which contained neutron, spontaneous and neutron-induced fission yield, and alpha sublibraries. The library was released in the standard Evaluated Nuclear Data File (ENDF) format. The files can be accessed on Brookhaven National Laboratory’s GitLab. The thermal scattering law (TSL) sublibrary will be released at a later date. The files provided in the neutron sublibrary were processed into A Compact ENDF (ACE)-formatted files, verified, and validated by the XCP-5 Nuclear Data Team. The resulting collection of ACE files will be referred to as the “e81b1” library. This report details the processing of these files and the quality assurance approach taken. This is not intended to be a full validation effort; rather, this library is intended to simply reproduce the released files for further validation testing by the community. The e81b1 ACE library will be released to the NNDC for access through GitLab and hosted locally on LANL computing resources. This library is only intended for analysis to support the future ENDF/B-VIII.1 release and should not be used for production results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Examples of Mission-driven Data Science from Jefferson Lab and ACES

This presentation details mission-driven data science initiatives at Jefferson Lab and the Joint Institute for Advanced Computing on Environmental Studies (ACES). JLab, a U.S. Department of Energy Office of Science national laboratory, operates the Continuous Electron Beam Accelerator Facility (CEBAF), and is the lead institute for the new High Performance Data Facility (HPDF) Hub. The Joint Institute for ACES brings together interdisciplinary teams in health informatics, climate modeling, computer science, and physics to address environmental challenges, including flood modeling. The Hampton Roads region, particularly Norfolk and Virginia Beach, faces increasing flood risks, motivating the need for rapid, reliable, and risk-aware decision support. ACES’s flooding work has a focus on uncertainty quantification (UQ) and machine learning (ML) for coastal flood management. The work is motivated by the increasing vulnerability of communities such as Norfolk and Virginia Beach, Virginia, to frequent coastal flooding events, and the need for rapid, reliable decision support. The research develops computationally efficient ML surrogate models to forecast water levels and flooding risk. A central theme is the quantification and calibration of predictive uncertainty, especially for out-of-distribution (OOD) scenarios, using techniques such as Monte Carlo Dropout, Deep Ensembles, Gaussian Processes, and Deep Quantile Regression (DQR). The study demonstrates that distance-aware UQ is critical for reliable scientific AI, particularly in high-dimensional, safety-critical, and real-time applications.

McSpadden, Diana [Thomas Jefferson National Accele↗

Advanced control evaluation for structures (ACES) programs

The ACES programs are a series of past, present, and future activities at the Marshall Space Flight Center (MSFC) Ground facility for Large Space Structure Control Verification (GF/LSSCV). The main objectives of the ACES programs are to implement control techniques on a series of complex dynamical systems, to determine the control/structure interaction for the control techniques, and to provide a national facility in which dynamics and control verification can be effected. The focus is on these objectives and how they are implemented under various engineering and economic constraints. Future plans that will be effected in upcoming ACES programs are considered.

Pearson, Jerome↗

Measurement and Analysis of Atmospheric Spectral Optical Depths with NASA Ames Airborne Sunphotometers During TARFOX and ACE-2

In accordance with the scope of work of this contract, the following tasks were undertaken and completed during the course of the contract: (1) Participation in the design and development of the 14-channel Ames Airborne Tracking Sunphotometer (AATS-14), including the development and implementation of Visual Basic software for real-time data processing and display and post-acquisition data reduction and analysis. (2) Operation of the six-channel Ames Airborne Tracking Sunphotometer (AATS-6) aboard the University of Washington C-131A during TARFOX and in-field analysis and presentation of data acquired with the AATS-6. (3) Post-mission analysis of data acquired during TARFOX with the AATS-6 and the AATS-14. (4) Pre-TARFOX calibration of the AATS-6 at Mauna Loa Observatory in May 1996, and post-TARFOX calibration of the AATS-6 and AATS- 14 at Zugspitze, Germany in October 1996, including analyses of all data sets. (5) Analysis of AATS-14 airborne calibration data acquired on 17 November 1996 during a late afternoon Pelican flight over the central California coast. (6) Operational training, instrument preparation, field coordination, and analysis of shipboard measurements of aerosol optical depth with the AATS-6 during ACE-2. (7) Coordination of data acquisition with the AATS-14 aboard the Pelican during ACE-2 and in-field preliminary data analysis and presentation. (8) Calibration of the AATS-6 and AATS-14 in April/May 1997 at Mauna Loa prior to ACE-2, and post-mission calibration of the AATS-6 at Mauna Loa in August 1997.

Livingston, John M.↗

ACE

This document describes the progress made during the fourth year of the Center for Autonomous Control Engineering (ACE). We currently support 30 graduate students, 52 undergraduate students, 9 faculty members, and 4 staff members. Progress will be divided into two categories. The first category explores progress for ACE in general. The second describes the results of each specific project supported within ACE.

Lumia, R.↗

Characterization of Dust Properties at the Source Region During ACE-Asia

ACE (Aerosol Characterization Experiment)-Asia is designed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally-occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. The phase-I of ACE-Asia was conducted from March-May 2001 in the vicinity of the Gobi desert, east coast of China, Yellow Sea, Korea, and Japan, along the pathway of Kosa (severe events that blanket East Asia with yellow desert dust, peaked in the Spring season). Asian dust typically originates in desert areas far from polluted urban regions. During transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian dust is of special importance in regional-to-global climate issues such as radiative forcing, the hydrological cycle, and primary biological productivity in the mid-Pacific Ocean. During ACE-Asia we have measured continuously aerosol optical/radiative properties, column precipitable water amount, and surface reflectivity over homogeneous areas from surface. The inclusion of flux measurements permits the determination of dust aerosol radiative flux in addition to measurements of loading and optical thickness. At the time of the Terra/MODIS overpass, these ground-based observations can provide valuable data to compare with MODIS retrievals over land. Preliminary results will be presented and discussed their implications in regional climatic effects.

Tsay, Si-Chee↗

Dust Aerosols at the Source Region During ACE-ASIA: A Surface/Satellite Perspective

ACE (Aerosol Characterization Experiment)-Asia is designed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. The phase-I of ACE-Asia was conducted from March-May 2001 in the vicinity of the Gobi desert, East Coast of China, Yellow Sea, Korea, and Japan, along the pathway of Kosa (severe events that blanket East Asia with yellow desert dust, peaked in the Spring season). Asian dust typically originates in desert areas far from polluted urban regions. During transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian dust is of special importance in regional-to-global climate issues such as radiative forcing, the hydrological cycle, and primary biological productivity in the mid-Pacific Ocean. During ACE-Asia we have measured continuously aerosol physical/optical/radiative properties, column precipitable water amount, and surface reflectivity over homogeneous areas from surface. The inclusion of flux measurements permits the determination of dust aerosol radiative flux in addition to measurements of loading and optical thickness. At the time of the Terra/MODIS, SeaWiFS, TOMS and other satellite overpasses, these ground-based observations can provide valuable data to compare with satellite retrievals over land. Preliminary results will be presented and discussed their implications in regional climatic effects.

Tsay, Si-Chee↗

ACE-Asia Aerosol Optical Depth and Water Vapor Measured by Airborne Sunphotometers and Related to Other Measurements and Calculations

In the Spring 2001 phase of the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia), the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated on 15 of the 19 research flights of the NCAR C-130, while its 14-channel counterpart (AATS- 14) flew successfully on all 18 research flights of the CIRPAS Twin Otter. ACE-Asia studied aerosol outflow from the Asian continent to the Pacific basin. It was designed to integrate suborbital and satellite measurements and models so as to reduce the uncertainty in calculations of the climate forcing due to aerosols. AATS-6 and AATS-14 measured solar beam transmission at 6 and 14 wavelengths (380-1021 and 354-1558 nm, respectively), yielding aerosol optical depth (AOD) spectra and column water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction spectra and water vapor concentration. The wavelength dependence of these AOD and extinction spectra indicates that supermicron dust was often a major component of the ACE-Asia aerosol. Frequently this dust-containing aerosol extended to high altitudes. For example, in AATS- 14 profiles analyzed to date, 36% of full-column AOD at 525 nm was above 3 km. In contrast, only 10% of CWV was above 3 km. Analyses and applications of AATS-6 and AATS-14 data to date include comparisons to (i) extinction products derived using in situ measurements, (ii) extinction profiles derived from lidar measurements, and (iii) AOD retrievals from the Multi-angle Imaging Spectro-Radiometer (MISR) aboard the TERRA satellite. Other planned collaborative studies include comparisons to results from size spectrometers, chemical measurements, other satellite sensors, flux radiometers, and chemical transport models. Early results of these studies will be presented.

Livingston, John M.↗

Airborne Sunphotometry of Aerosol Optical Depth and Columnar Water Vapor During ACE-Asia

During the Intensive Field Campaign (IFC) of the Aerosol Characterization Experiment - Asia (ACE-Asia), March-May 2001, the 6-channel NASA Ames Airborne Tracking Sunphotometer (AATS-6) operated during 15 of the 19 research flights aboard the NCAR C- 130, while its 14-channel counterpart (AATS- 14) was flown successfully on all 18 research flights of a Twin Otter aircraft operated by the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS), Monterey, CA. ACE-Asia was the fourth in a series of aerosol characterization experiments and focused on aerosol outflow from the Asian continent to the Pacific basin. Each ACE was designed to integrate suborbital and satellite measurements and models so as to reduce the uncertainty in calculations of the climate forcing due to aerosols. The Ames Airborne Tracking Sunphotometers measured solar beam transmission at 6 (380-1021 nm, AATS-6) and 14 wavelengths (353-1558 nm, AATS-14) respectively, yielding aerosol optical depth (AOD) spectra and column water vapor (CWV). Vertical differentiation in profiles yielded aerosol extinction and water vapor concentration. The wavelength dependence of AOD and extinction indicates that supermicron dust was often a major component of the aerosol. Frequently this dust-containing aerosol extended to high altitudes. For example, in data flights analyzed to date 34 +/- 13% of full-column AOD(525 nm) was above 3 km. In contrast, only 10 +/- 4% of CWV was above 3 km. In this paper, we will show first sunphotometer-derived results regarding the spatial variation of AOD and CWV, as well as the vertical distribution of aerosol extinction and water vapor concentration. Preliminary comparison studies between our AOD/aerosol extinction data and results from: (1) extinction products derived using in situ measurements and (2) AOD retrievals using the Multi-angle Imaging Spectro-Radiometer (MISR) aboard the TERRA satellite will also be presented.

Redemann, Jens↗

Radiative Flux Changes by Aerosols from North America, Europe, and Africa over the Atlantic Ocean: Measurements and Calculations from TARFOX and ACE-2

Aerosol effects on atmospheric radiative fluxes provide a forcing function that is a major source of uncertainty in understanding the past climate and predicting climate change. To help reduce this uncertainty, the 1996 Tropospheric Aerosol Radiative Forcing Experiment (TARFOX) and the 1997 second Aerosol Characterization Experiment (ACE-2) measured the properties and radiative effects of American, European, and African aerosols over the Atlantic. In TARFOX, radiative fluxes and microphysics of the American aerosol were measured from the UK C-130 while optical depth spectra, aerosol composition, and other properties were measured by the University of Washington C-131A and the CIRPAS Pelican. Closure studies show that the measured flux changes agree with those derived from the aerosol measurements using several modelling approaches. The best-fit midvisible single-scatter albedos (approx. 0.89 to 0.93) obtained from the TARFOX flux comparisons are in accord with values derived by independent techniques. In ACE-2 we measured optical depth and extinction spectra for both European urban-marine aerosols and free-tropospheric African dust aerosols, using sunphotometers on the R/V Vodyanitskiy and the Pelican. Preliminary values for the radiative flux sensitivities (Delta Flux / Delta Optical depth) computed for ACE-2 aerosols (boundary layer and African dust) over ocean are similar to those found in TARFOX. Combining a satellite-derived optical depth climatology with the aerosol optical model validated for flux sensitivities in TARFOX provides first-cut estimates of aerosol-induced flux changes over the Atlantic Ocean.

Russell, P. B.↗

A Global Aerosol Model Forecast for the ACE-Asia Field Experiment

We present the results of aerosol forecast during the Aerosol Characterization Experiment (ACE-Asia) field experiment in spring 2001, using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model and the meteorological forecast fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The aerosol model forecast provides direct information on aerosol optical thickness and concentrations, enabling effective flight planning, while feedbacks from measurements constantly evaluate the model, making successful model improvements. We verify the model forecast skill by comparing model predicted total aerosol extinction, dust, sulfate, and SO2 concentrations with those quantities measured by the C-130 aircraft during the ACE-Asia intensive operation period. The GEOS DAS meteorological forecast system shows excellent skills in predicting winds, relative humidity, and temperature for the ACE-Asia experiment area as well as for each individual flight, with skill scores usually above 0.7. The model is also skillful in forecast of pollution aerosols, with most scores above 0.5. The model correctly predicted the dust outbreak events and their trans-Pacific transport, but it constantly missed the high dust concentrations observed in the boundary layer. We attribute this missing dust source to the desertification regions in the Inner Mongolia Province in China, which have developed in recent years but were not included in the model during forecasting. After incorporating the desertification sources, the model is able to reproduce the observed high dust concentrations at low altitudes over the Yellow Sea. Two key elements for a successful aerosol model forecast are correct source locations that determine where the emissions take place, and realistic forecast winds and convection that determine where the aerosols are transported. We demonstrate that our global model can not only account for the large-scale intercontinental transport, but also produce the small-scale spatial and temporal variations that are adequate for aircraft measurements planning.

Chin, Mian↗

Aerosols, Chemistry, and Radiative Forcing: A 3-D Model Analysis of Satellite and ACE-Asia data (ACMAP)

We propose a research project to incorporate a global 3-D model and satellite data into the multi-national Aerosol Characterization Experiment-Asia (ACE-Asia) mission. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosols and the processes that control those properties over the Asian-Pacific region, (2) to investigate the interaction between aerosols and tropospheric chemistry, and (3) to determine the aerosol radiative forcing over the Asia-Pacific region. We will use the Georgia TecWGoddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to link satellite observations and the ACE-Asia measurements. First, we will use the GOCART model to simulate aerosols and related species, and evaluate the model with satellite and in-situ observations. Second, the model generated aerosol vertical profiles and compositions will be used to validate the satellite products; and the satellite data will be used for during- and post- mission analysis. Third, we will use the model to analyze and interpret both satellite and ACE- Asia field campaign data and investigate the aerosol-chemistry interactions. Finally, we will calculate aerosol radiative forcing over the Asian-Pacific region, and assess the influence of Asian pollution in the global atmosphere. We propose a research project to incorporate a global 3-D model and satellite data into

Chin, Mian↗