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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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DOE OSTI2026

Data for Autonomous Transportation Awareness: Data Exchange Use Cases, Standards, and Barriers

This report examines the critical data exchanges between automated vehicle (AV) service providers and the cities and municipalities they serve. It assists municipal authorities in navigating the often complex and real-time digital data exchanges needed to support AV mobility services, with emphasis in three areas: (1) critical safety data for broad-area situational awareness of hazards typically associated emergency dispatch or roadway work zones; (2) performance metrics of AV services that inform the quantity, quality, spatial extents, and impact on the roadway network; and (3) regulatory and policy information, particularly dynamic information that governs how AV services interact with the roadway network, with emphasis on curb space. The report reviews existing practices and emerging protocols and standards and identifies key gaps to address moving forward.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Tula: Optimizing Time, Cost, and Generalization in Distributed Large-Batch Training

Distributed training increases the number of batches processed per iteration either by scaling-out (adding more nodes) or scaling-up (increasing the batch-size). However, the largest configuration does not necessarily yield the best performance. Horizontal scaling introduces additional communication overhead, while vertical scaling is constrained by computation cost and device memory limits. Thus, simply increasing the batch-size leads to diminishing returns: training time and cost decrease initially but eventually plateaus, creating a knee-point in the time/cost vs. batch-size pareto curve. The optimal batch-size therefore depends on the underlying model, data and available compute resources. Large batches also suffer from worse model quality due to the well-known “generalization gap”. In this paper, we present Tula, an online service that automatically optimizes time, cost, and convergence quality for large-batch training of convolutional models. It combines parallel-systems modeling with statistical performance prediction to identify the optimal batchsize. Tula predicts training time and cost within 7.5−14% error across multiple models, and achieves up to 20× overall speedup and improves test accuracy by ≈9% on average over standard large-batch training on various vision tasks, thus successfully mitigating the generalization gap and accelerating training at the same time.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗
DOE OSTI2024

Sustainable Public Transport: Providing Responsive, On-Demand Service with Clean Energy

The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2025

LANL Meteorology Program Self-Assessment 2025 Update

The LANL Meteorological (Met) Program has been subject to several external reviews over the past 19 years. The DOE Meteorological Coordinating Council (DMCC) conducted an initial Met Program Site Assist Visit (SAV) in August 2006 (DMCC 2006). A follow-up SAV in August 2015 assessed progress (DMCC 2015), and in June 2023, the DOE Meteorological Subcommittee (DMSC), successor to the DMCC, conducted a second follow-up SAV (DMSC 2023), in which the Met Program was evaluated relative to the following 8 high-level questions: • What is the state of the meteorological services provided to its customers? • What is the quality of meteorological data provided to its customers and is it adequate and available to meet all customer needs? • What is the quality of atmospheric transport and diffusion modeling provided to its customers and is it applicable to complex wind flow patterns at LANL? • Are the current and future meteorological service customers being serviced appropriately? • Are there adequate human resources to meet present and future program customer needs and are they being appropriately leveraged? • Are existing instrumentation, facilities, and systems adequate to meet present and future customer needs? • Are LANL meteorological services conducted in an efficient, cost-effective manner? • Is meteorological data used to ensure safety & health of LANL personnel? More specific evaluations were performed relative to 23 performance objectives extracted from the ANSI/ANS-3.11- 2024 national standard and 14 separate performance objectives associated with consequence assessment and atmospheric transport and diffusion modeling in the consequence assessment element of DOE G 151.1-1B. In 2023, the DMSC SAV Team also reviewed the status of each of the 18 remaining recommendations from its 2015 SAV. Based on this review, DMSC stated in its Exit Briefing that the LANL meteorological program has gotten much stronger and more robust since 2015 and now represents one of the better managed programs within the DOE complex.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Summer 2024 INL Intern Poster Session Submission - Brian Schumitz

This LRS submission is my poster for the INL Intern Poster Session, Summer 2024. Abstract: The Software Engineering and Cybersecurity Lab (SECL) at Montana State University has developed PIQUE, a system for evaluating software quality. PIQUE's adaptability allows for language-specific static-analysis operations, including a model for assessing cloud microservice ecosystems. These ecosystems often rely on Docker for efficient deployment and management of containerized services. Our research focuses on evaluating the network quality within these microservice ecosystems. To automate this process, we're utilizing Snort, an open-source intrusion detection system renowned for its ability to detect and log network traffic. By leveraging Snort's customizable rules, we aim to construct comprehensive testing methods for measuring and quantifying the network quality based on traffic between Docker containers. This research aims to enhance the overall security and reliability of cloud microservice ecosystems by providing automated and robust quality evaluation mechanisms, ultimately contributing to the advancement of software engineering practices in these environments

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evaluating Hydropower Plants for Wildfire Resilient Microgrids

The increasing occurrence and severity of wildfires in recent years is severely impacting critical infrastructures, including the power grid, compromising the quality of life and provision of essential services, including electricity. The western parts of the United States, more specifically Washington, Oregon, and California, which are prone to large wildfires, are also rich in hydropower resources. Hydropower resources located close to communities vulnerable to wildfire can be utilized to develop wildfire-resilient microgrids to support critical needs of those communities. Therefore, this paper develops a framework to characterize hydropower plants and evaluate their feasibility to operate in microgrids during wildfire-related outages. In the proposed framework, hydropower plants are characterized using various plant and site attributes and evaluated in terms of capability and performance indicative metrics. A case study is carried out evaluating the Hills Creek hydropower plant located in a wildfire-prone region of Oregon for wildfire-resilient microgrid. The results of steady-state and dynamic simulations show that the hydropower plant is capable of providing the essential microgrid services and powering nearby communities during extended wildfire-related outages.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

Contrasting effects of land-use and local disturbance on plant and pollinator communities in wetlands

While pollinators and wetlands both provide important ecosystem services (e.g., the pollination of flowering plants and improving water quality), the relationship between the two is not well understood. Both biotic and abiotic effects can mediate the local wetland flower and pollinator community. In this study, we investigated how land use, including a land use gradient at five different radii, from 250 m to 2 km, along with anthropogenic disturbance affected pollinators in wetland ecosystems. We surveyed the abundance and diversity of plant-pollinator communities in fifteen different wetlands across two years. We also tested the relationship between water quality and temperature, and the abundance and diversity of flowering plants and pollinating insects. Our results suggest that increasing temperature, which was strongly associated with developed land use, had a negative effect on the floral display of wetland plants, as well as the abundance of all flower visitors and hover flies. Hover fly abundance was also positively associated with agricultural land use and total nitrogen in the water. Meanwhile, the abundance of female bees was affected by an interaction between temperature and disturbance: female bees were most abundant when temperatures were lower in areas of low disturbance. In contrast, pollinator species richness increased with temperature when developed land use was low, and floral diversity was strongly affected by several interactions between disturbance, land use, and water quality. Finally, the community composition of both plants and insects varied significantly among low, medium, and high disturbance categories, with weedier, non-native species being significantly associated with areas of higher disturbance and in sites with greater anthropogenic land use. We demonstrate that ecological communities shift significantly in response to anthropogenic change. Our work also illustrates the importance of quantifying interactions between land use and local disturbance with abiotic factors such as temperature and water quality on ecological systems.

Disturbance↗
DOE OSTI2025

From subsidies to stressors: Positively skewed ecological gradients alter biological responses to nutrients in streams

Abstract Subsidy–stress gradients offer a useful framework for understanding ecological responses to perturbation and may help inform ecological metrics in highly modified systems. Historic, region‐wide shifts from bottomland hardwood forest to row crop agriculture can cause positively skewed impact gradients in alluvial plain ecoregions, resulting in tolerant organisms that typically exhibit a subsidy response (increased abundance in response to environmental stressors) shifting to a stress response (declining abundance at higher concentrations). As a result, observed biological tolerance in modified ecosystems may differ from less modified regions, creating significant challenges for detecting biological responses to restoration efforts. Using the agriculturally dominated Mississippi Alluvial Plain (MAP) ecoregion in Mississippi, USA, as a case study, we tested the hypothesis that macroinvertebrate taxa that typically display a subsidy response to nutrient enrichment in less modified ecoregions (i.e., nutrient‐tolerance) shift to a stress response to increasing nutrients in highly modified watersheds with elevated baseline nutrient conditions (i.e., nutrient intolerance). The abundance and diversity of MAP‐specific intolerant taxa identified with threshold indicator taxa analysis were either unresponsive or exhibited a subsidy response to increasing nutrients in less modified ecoregions in Mississippi with less land alteration and lower nutrient concentrations, but declined at higher concentrations, providing evidence for a stress response to elevated nutrients in the MAP. Additionally, MAP‐specific tolerant and intolerant taxa richness responded to increased nutrients predictably and consistently across space and time within the MAP. However, in MAP streams, elevated specific conductance was predicted to dampen the response of tolerant and intolerant taxa richness to increasing nutrient concentrations, highlighting the importance of considering multistressor interactions when interpreting biological data. Lastly, we demonstrate the efficacy of this approach with sediment bacterial communities characterized with amplicon sequencing, which lack sufficient life history characteristics necessary for the development of multimetric indices. Both macroinvertebrate and bacterial communities responded similarly to increasing nutrient concentrations, suggesting DNA‐based approaches may provide an efficient biological assessment tool for monitoring water quality improvements in highly modified watersheds.

DeVilbiss, Stephen E. [U.S. Geological Survey Lowe↗
DOE OSTI2026

The Next Stage for Smart Cities: Metrics to Spur an Evolution from Technology for Efficiency to Technology for People's Needs

The Smart Cities movement is about a decade old, energized by the USDOT Smart Cities grant that sparked cities to dream big. Now, 10 years later, and multitudes of conferences and papers later, the biggest question regarding Smart Cities is whether any progress has been made? Smart Cities forums are typically led by the technology sector, either telecommunications, internet access, or most recently artificial intelligence (AI) concerns. Each of these areas have grown and found new applications in the context of Smart Cities, however, these technology applications are just tools toward ends. Do digital communications and assistance enable or foster improved access to real, tactile, non-virtual goods and services such as transportation, food, housing, trash removal, health care, education, social interaction? These and other topics are not 'big tech', but are each critical to quality of life outcomes and are day-to-day necessities, comprising many of the touch points through which citizens interact with municipal agencies. Regarding Smart Cities, relationships have not been fully refined as to how best to merge the emerging generation of technology and related trends with more mundane but essential requirements of tactile services. How should municipal managers and operators bring the range of new technology tools (e.g. on-demand transit, automated vehicles, digital connectivity) to bear to improve functions serving real- physical- non-virtual needs? How do we make cities more efficient in providing access to services and opportunities for improved quality of life? This paper examines the current Smart City movement, emerging trends, and the need to put metrics with respect to the delivery, access, and provision of real-life needs. Using a few case studies of past, present, and projected future scenarios, this paper attempts to bring Smart Cities into the real cities domain, perhaps pushing the moniker away from 'Smart' to 'Efficient' - something that can be measured, counted, and assessed. Through the consideration of the next stage of the evolution of cities from 'Smart' to 'Efficient', the combined efforts and experience of multiple researchers at the NREL and their network of collaborators highlights the need for updates metrics that can be used to start guiding efforts toward productive initiatives to improve quality of life.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Optimizing Residential HVAC Systems: Evaluating How the Usage of Smart Diagnostic Tools for Quality Installation and Commissioning Impacts System Performance and HVAC Contractor Businesses

The adoption of digital quality installation and fault detection tools has the potential to transform the $14 billon residential heating, ventilating, and air conditioning (HVAC) service and installation industry. Increased market penetration can be accelerated by providing an increased understanding of the energy and economic value proposition of the usage of these tools. In tandem with energy and HVAC system performance impact research and analysis, the Southface Team investigated the economic business implications for HVAC service and installation contractors adopting the use of measureQuick (mQ), a smart diagnostic app that aids in quality installation and fault detection and works agnostically with Bluetooth-enabled HVAC technician tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Identifying genomic data use with the Data Citation Explorer

Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data that was not formally cited. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Biophysical model of eelgrass and water quality in Coos Bay, OR shows greater mitigation potential for ocean acidification than hypoxia

Seagrass beds provide important ecosystem services and are valued, in part, for their potential to mediate stressors such as ocean acidification and hypoxia (OAH) for sensitive species. However, the susceptibility of seagrasses to anthropogenic impacts and recent declines motivate the need to better understand the drivers of seagrass and the water quality consequences that occur with variation in seagrass abundance. To meet this need, we leveraged existing monitoring data (water quality and seagrass), hydrodynamic circulation model, and biogeochemical model framework with seagrass submodel, to produce a biophysical model of Coos Bay estuary, Oregon, U.S. The model includes biogeochemical processes involving water quality, plankton, seagrass, and sediment-water interactions. Ecosystem models like this are useful for evaluating complex estuarine systems because they allow us to extend our understanding of system dynamics beyond existing observations and perform experiments to identify the processes driving observed patterns. We used the biophysical model of Coos Bay to evaluate the dynamics of water quality and native eelgrass (Zostera marina) under three eelgrass abundance scenarios (zero eelgrass, current extent, and maximum observed extent) to elucidate the relationship between eelgrass and OAH. Including eelgrass in the Coos Bay model produced results that more closely resembled water quality observations - dissolved oxygen (DO) and pH were more dynamic in simulations with eelgrass, often having both higher highs and lower lows. While there were some areas of the estuary where DO improved with the addition of eelgrass to the model there was overall a small net increase in harmful DO conditions (based on a salmon physiological threshold). In contrast, ocean acidification conditions, pH and calcium carbonate saturation state for aragonite (Ω), were improved (based on oyster requirements) with the addition of eelgrass - although the magnitude of improvement differed seasonally and spatially. Our new model represents a useful tool - one which accounts for and controls the relevant physical and biogeochemical processes - to evaluate conditions that confer resilience or enhance vulnerability to OAH in an important Pacific Northwest coastal estuary and results can inform the OAH-related dynamics occurring in other eastern boundary current estuaries.

FVCOM-ICM↗
DOE OSTI2024

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Initial Testing of an In Situ Load Retention Aging Vessel

A thermal aging vessel instrumented with load cells was fabricated. The primary function of the vessel is to continuously monitor the in situ load retention of up to three compressed polymer coupons undergoing thermally accelerated aging under nitrogen. A secondary function is to enable gas sampling of the vessel headspace during thermal aging. Heating of the vessel is achieved using a custom heater jacket. To improve upon our conventional aging study methods which require periodic interruption of aging to perform load testing in an Instron machine at room temperature, this technology aims to automate/facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of the polymer which represents the service condition. As an example case to assess functionality of the in situ vessel, the load retention of a siloxane elastomer material additively manufactured by direct-ink-writing (DIW) was measured at three different isothermal aging temperatures for ~1 month. Initial compression of the coupons while near the aging temperature was achieved by temporarily opening the heated vessel to access the interior chamber and manually tightening four nuts to drive the heated compression plate down onto the heated coupons. Initial testing demonstrated achievement of the primary load retention monitoring function. Unfortunately, the vessel leaked which prevented gas sampling; an active purge was used to maintain a nitrogen atmosphere. Welded or otherwise sealed joints, which could be implemented in a future design, would likely eliminate leak paths. To apply time-temperature superposition (TTS), a technique used to provide long-term prediction of the load retention from short-term isothermal data, the load retention needed to be calculated relative to the load at an estimated “equilibrium” time, after most of the transient viscoelastic physical relaxation occurred. The peak load immediately after compression could not be used as the load retention basis for two reasons: (1) age-related changes must be isolated from non-age-related physical relaxation before applying TTS and (2) the manual mechanism used to compress the specimens at the aging temperature was neither smooth nor repeatable which affected the peak load value. To better understand the effect of the mode of initial compression on the measured load, and possibly better estimate “equilibrium” physical relaxation times, systematic stress relaxation experiments were performed using an Instron machine with a thermal chamber. At a given temperature, the DIW polymer was compressed to a fixed strain in either a stepped or continuous manner at two different rates, then held at that strain for 24 hrs. The results indicated that, at a given temperature, the different stress relaxation curves appeared to converge to the same curve at some “equilibrium” time when the non-age-related physical relaxation was mostly complete. Though this observation suggests that the discontinuous manual compression employed by the vessel is feasible, a compression mechanism that is rapid, smooth, and repeatable would enhance its use.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MaPSA Quality Control and AI-Enhanced Grading For the CMS Phase-II Tracker Upgrade

The Compact Muon Solenoid (CMS) experiment will undergo changes as part of the Large Hadron Collider upgrade. The CMS tracker will be upgraded to cope with the new radiation environment and to provide tracking at the first level trigger. This upgrade features a new type of silicon module called PS Module, which combines a Pixel sensor and a Strip sensor in the same module. The pixel portion of the PS module has a sensor bump bonded to 16 Macro Pixel ASICs (MPA) to form a Macro Pixel Sub Assembly (MaPSA). At Fermilab, MaPSAs are tested for quality control before being assembled with the strip sensors, readout and service electronics to form a PS Module. All of this test data is stored in a centralized database, and is used to grade the final module to determine if it will be installed in the detector. The Phase II Outer Tracker Analyzer of Test Outputs (POTATO) is the software that processes this data and determines the module grades. Using recent technologies, an AI agent is being im plemented into POTATO in order to allow users to more efficiently sort through the large amounts of analysis data and ensure that only the user specified data is being considered. This poster will display the process of testing a MaPSA, how that test data is relevant to module assembly and grading, and how the POTATO grading tool is being improved with the use of an embedded AI agent.

Gzamouranis, Olivia [Purdue U.]↗
DOE OSTI2025

The git based ATLAS data acquisition configuration service in LHC Run 3

The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and data acquisition system composed of many computing nodes, networks, and hardware modules. Its configuration service is used to provide descriptions of control, monitoring, diagnostic, recovery, dataflow and data quality configurations, interconnections, and parameters for modules, chips, and channels of various online systems, detectors, and the whole ATLAS experiment. Those descriptions have historically been stored in more than one thousand interconnected XML files, which are updated by various experts many times per day. Maintaining error-free and consistent sets of such files and providing reliable and fast access to current and historical configurations is a major challenge. This paper gives details of the configuration service upgrade on the modern Git version control system backend for LHC Run 3 and its exploitation experience. It may be interesting for developers using human-readable file formats, where consistency of the files, performance, access control, traceability of modifications, and effective archiving are key requirements.

Soloviev, Igor [Univ. of California, Irvine, CA (U↗
DOE OSTI2025

Observed declines in leaf nitrogen explained by photosynthetic acclimation to CO 2

Widespread evidence of decreasing leaf nutrients has raised concerns about ecosystem productivity under global change. Interpreting trends in leaf nutrients has important implications for the fate of ecosystem services, particularly the role of forests in mitigating climate change and sustaining quality food sources. Here, we challenge the common interpretation that decreasing leaf nitrogen concentration (LNC) is evidence of increasing nutrient limitations on ecosystem primary productivity. Instead, we show that declines in LNC (4% decrease per 50 ppm CO 2 increase), observed across 409 European forest plots over 22 y, can be explained by reduced photosynthetic nitrogen demand. This regional trend is consistent with leaf acclimation to increasing atmospheric CO 2 according to optimality theory. This finding suggests that enhanced photosynthetic nitrogen use efficiency due to CO 2 fertilization may lead to less nitrogen uptake and/or reallocation of nitrogen for plant growth and other functions. Our results have large implications for understanding and simulating interactions between ecosystem nitrogen and carbon cycles and suggest nitrogen requirements for terrestrial carbon uptake under elevated CO 2 may be lower than previously thought.

CO2 fertilization↗