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QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing
Resource constraints on the computing continuum require that we make smart decisions for serving AI-based services at the network edge. AI-based services typically have multiple implementations (e.g., image classification implementations include SqueezeNet, DenseNet, and others) with varying trade-offs (e.g., latency and accuracy). The question then is how should AI-based services be placed across Function-as-a-Service (FaaS) based edge computing systems in order to maximize total Quality-of-Service (QoS). To address this question, we propose a problem that jointly aims to solve (i) edge AI service placement and (ii) request scheduling. These are done across two time-scales (one for placement and one for scheduling). Here we first cast the problem as an integer linear program. We then decompose the problem into separate placement and scheduling subproblems and prove that both are NP-hard. We then propose a novel placement algorithm that places services while considering device-to-device communication across edge clouds to offload requests to one another. Our results show that the proposed placement algorithm is able to outperform a state-of-the-art placement algorithm for AI-based services, and other baseline heuristics, with regard to maximizing total QoS. Additionally, we present a federated learning-based framework, FLIES, to predict the future incoming service requests and their QoS requirements. Our results also show that our FLIES algorithm is able to outperform a standard decentralized learning baseline for predicting incoming requests and show comparable predictive performance when compared to centralized training.
SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans
Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lung were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R25GM109439.
Software Quality Metrics for Geant4: An Initial Assessment - Paper 122
In the context of critical applications, such as shielding and radiation protection, ensuring the quality of simulation software they depend on is of utmost importance. The assessment of simulation software quality is crucial both to determine its adoption in experimental applications and to guarantee reproducibility of outcome over time. Geant4 is a simulation system used in a wide range of experimental applications, some of which, such as radiation protection and biomedical studies, may involve critical use cases and would especially profit from an objective assessment of the software quality. In this study, we present the first results from an ongoing analysis of Geant4 code based on established software metrics from the perspective of software engineering. The analysis evaluates the current status of the code to quantify its characteristics with respect to documented quality standards; further appraisals concern evolutions over a series of release distributions. The quantitative assessment of the software is initially focused on a subset of Geant4 packages, which play a key role in scientific applications and are representative of different software development processes. We describe the chosen software metrics that map the entities of a software system to numeric values through mathematical definitions, quantifying software attributes ranging from functionality to maintainability. To measure such metrics, we exploited a set of software metrics tools, i.e. programs that implement a set of software metrics definitions. They allow software engineers to assess a software system by extracting the required attributes from the software and providing the corresponding metric values. To correlate software metrics values in a well-defined way, we used software quality standard models, such as the ISO/IEC 9126 standard, which aggregate numerical values to aid quality analysis and assessment. With this work we aim to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. Furthermore, we intend to highlight what metrics are most effective at evaluating radiation transport software quality. We are confident that the result will provide constructive guidance both to improve key software tools, such as Geant4, and to estimate their contribution in risk analysis concerning sensitive applications. The remainder of this paper is structured as follows. We first discuss the approach adopted to fulfil our assessment. Then, we present the setup of our experiments and the way we collected data. We provide an initial interpretation of a subset of data resulting from measurements made on the selected Geant4 packages. As the analysis is still ongoing at the time of submitting this abstract, some results will be documented in the final paper and in the conference presentation. With this work we aim to create a proper Geant4 data set for evaluating its software characteristics and identifying both strengths and weaknesses. In this initial study, we considered the geometry and processes packages, which play a major role in most simulation applications. The data analysis is in progress at the time of writing; its complexity is related to the differences among software metrics tools, to the large amount of data to be evaluated and to the pioneering character of this project. We are confident that the results will provide valuable indications for the Geant4 user community and constructive guidance to improve key Geant4 packages. Other Monte Carlo codes could profit from the methodology developed in this pilot project for similar assessments of their software quality. At the end of this study, we intend to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. (authors)
SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES
The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.
Precision Measurement of Net-Proton-Number Fluctuations in Au + Au Collisions at RHIC
We report precision measurements on cumulants (𝐶 𝑛 ) and factorial cumulants (𝜅 𝑛 ) of (net) proton number distributions up to fourth order in Au + Au collisions over center-of-mass energies $\sqrt{s_{NN}}$ = 7.7–27 GeV from phase II of the Beam Energy Scan program at RHIC. (Anti)protons are selected at midrapidity (|𝑦| < 0.5) within a transverse momentum range of 0.4 < 𝑝 𝑇 < 2.0 GeV/𝑐. Relative to various noncritical-point model calculations and peripheral collision 70%–80% data, the net proton 𝐶 4 /𝐶 2 measurement in 0%–5% collisions shows a minimum around 19.6 GeV for significance of deviation at ∼2–5𝜎. A minimum in 𝐶 4 /𝐶 2 with respect to a noncritical baseline is expected to be a characteristic feature of the signature associated with a critical point in the QCD phase diagram. In addition, deviations from noncritical baselines around the same collision energy region are also seen in proton factorial cumulant ratios, especially in 𝜅 2 /𝜅 1 and 𝜅 3 /𝜅 1 . As a result, dynamical model calculations including a critical point are called for in order to understand these precision measurements.
Data Compression in the NEXT-100 Data Acquisition System
NEXT collaboration detectors are based on energy measured by an array of photomultipliers (PMT) and topological event filtering based on an array of silicon photomultipliers (SiPMs). The readout of the PMT sensors for low-frequency noise effects and detector safety issues requires a grounded cathode connection that makes the readout AC-couple with variations in the signal baseline. Strict detector requirements of energy resolution better than 1% FWHM require a precise baseline reconstruction that is performed offline for data analysis and detector performance characterization. Baseline variations make it inefficient to apply traditional lossy data compression techniques, such as zero-suppression, that help to minimize data throughput and, therefore, the dead time of the system. However, for the readout of the SiPM sensors with less demanding requirements in terms of accuracy, a traditional zero-suppression is currently applied with a configuration that allows for a compression ratio of around 71%. The third stage in the NEXT detectors program, the NEXT-100 detector, is a 100 kg detector that instruments approximately five times more PMT sensors and twice the number of SiPM sensors than its predecessor, the NEXT-White detector, putting more pressure in the DAQ throughput, expected to be over 900 MB/s with the current configuration, which will worsen the dead time of the acquisition data system. This paper describes the data compression techniques applied to the sensor data in the NEXT-100 detector, which reduces data throughput and minimizes dead time while maintaining the event rate to the level of its predecessor, around 50 Hz.
PIP-II Status and Strategy
Proton Improvement Plan-II (PIP-II) is the centerpiece of Fermilab's plan for upgrading the accelerator complex to establish the leading facility in the world for particle physics research based on intense proton beams. PIP-II has been developed to provide 1.2 MW of proton beam power at the start of operations of the Long Baseline Neutrino Facility (LBNF), while simultaneously providing a platform for eventual extension of LBNE beam power to >2MW and enabling future initiatives in rare processes research based on high duty factor/higher beam power operations. PIP-II is based on the construction of a new 800 MeV superconducting linac, augmented by improvements to the existing Booster, Recycler, and Main Injector complex. PIP-II is currently in the development stage with an R&D program underway targeting the front end and superconducting RF acceleration technologies. This paper will describe the status of the PIPII conceptual development, the associated technology R&D programs, and the strategy for project implementation.
Improvements to the operational efficiency of the Portsmouth 'Blue Box' Assay system - 15162
The 'Blue Box' in Building 326 at Portsmouth comprises a dual cargo container lined with high density polyethylene with 5% (elemental) boron that acts as a neutron shield. This construction provides a low environmental neutron background to support the capability to attain low values of minimal detectable activity (MDA). A Non-destructive Assay (NDA) measurement platform known as the Fluor B and W Portsmouth Slab Counter (FBPSC) is housed inside the Blue Box. This comprises four neutron slab detectors supported with an electronic system supplying power and associated signal processing. The system is operated by a laptop computer which has data acquisition and analysis capabilities. Each slab contains five {sup 3}He proportional counters embedded in polyethylene. The system is designed to measure the mass of U-235 in coolers from the Portsmouth site using passive neutron counting. The system was calibrated by taking measurements with {sup 252}Cf sources attached to various positions on the outside surfaces of a surrogate cooler. In addition, Monte-Carlo N-Particle (MCNP) simulations were performed to extend the baseline calibration for coolers of various sizes used in the gaseous-diffusion process. The basic principle of operation is to measure the total neutron emission from the item and determine the mass of {sup 235}U using the system efficiency (determined from MCNP calculations combined with the calibration measurements) combined with known isotopic information ({sup 235}U enrichment and U-235/U-234 ratio), assumed chemical composition, and gross cooler mass. The FBPSC analysis program calculates the mass of U-235 within the cooler being assayed, together with the associated Total Measurement Uncertainty (TMU). A background correction is performed that accounts for the measured environmental background with a cosmic-ray spallation correction (based on the cooler's gross weight). The software suite developed for the system also includes the capability to track and trend measurement control data in order to quickly identify conditions where the system has drifted outside of its quality control envelope. The MDA of the system has been determined to be less the 15 g of U-235 for count times that are typically less than 5 minutes (depending on the uranium isotopics). This is primarily the result of the low neutron background rate inside the Blue Box (approximately 3 times lower than at nearby locations outside the box). Additionally, various software features have been designed to yield optimum counting performance for the system including count time adjustment and interval filtering to reject statistical outliers that are usually associated with cosmic spallation events. The operation of the system has proven to be very efficient, with the short measurement time providing a high throughput rate of coolers through the Blue Box NDA system. Significant operational benefits and improved data traceability have been yielded compared to the previous measurement process, which involved operators taking measurement with counter/scalers and manually entering data into spreadsheets. As of August 2014, this system successfully measured all coolers required to support completion of a contractually-required Performance Milestone. There are approximately 1900 coolers available for measurement. (authors)
Modbus RTU for Embedded Cyber Secure Inverter Controller
The Modbus communication protocol is a widely adopted communication standard in industrial control systems. This communication protocol is known for being reliable and straightforward to implement while being versatile in terms of its operating parameters while supporting multiple formats over various hardware infrastructures and architectures. Many intelligent devices such as Programmable Logic Controllers (PLCs), Human-Machine Interfaces (HMIs), Internet-of-Things (IoT), and various Operational Technologies (OT) utilize Modbus for their communication systems. These types of systems must communicate with each other through a standardized and central communication process. To support the integration of these modular systems, a Field-Programmable Gate Array (FPGA) can act as an embedded central routing fabric for this communication to take place. Embedded systems are versatile enough to interface with various devices and systems to accomplish various goals. Additionally, embedded systems require relatively small physical designs to minimize the required resources to facilitate the intended application by providing low-level system access. This minimization of system resources goes hand in hand with reducing the financial cost of a proposed solution or system. As remotely collaborating researchers often use FPGAs to prototype designs that are required to have a method for data transmission among systems, it is imperative to provide a baseline standard for communications among devices and systems. A typical method of implementing the Modbus RTU communication protocol in an embedded environment is using integrated logic architectures within the FPGA called “Intellectual Property (IP) cores.” IP cores can be designed using integrated logic or circuit designs to function as an embedded processor. These IP cores can then perform the required computational actions to support the Modbus RTU communication protocol by utilizing high-level programming languages such as the C programming language. The hardware description language of Very High-Speed Integrated Circuit Hardware Description Language (VHDL) allows for the control of real hardware at the logic gate and signal level. These logic gates and signals can be designed and controlled to perform desired actions based on the system design. Programming an FPGA using VHDL allows an individual to access the lowest abstraction level of the system during FPGA development. This level of abstraction is referred to as the register-transfer level (RTL), which gives access to manipulating values and variables at the register level. This register-level manipulation provides precision over creating the logical circuit within the FPGA, thus minimizing the required code to perform desired operations. The Modbus RTU communication protocol can be implemented within an FPGA using VHDL programming to establish a standardized and embedded serial communication pathway. This implementation provides a standardized communication protocol to streamline research efforts among researchers, thus increasing the efficiency of research efforts. Additionally, this Modbus RTU implementation requires fewer resources when compared to typical communication protocol implementations that utilize an IP core, reducing the hardware requirement for effective research efforts.
Surveillance and Monitoring Program Full-Scale Experiments to Evaluate the Potential for Corrosion in 3013 Containers
A set of six long-term, full-scale experiments were initiated to determine the type and extent of corrosion that occurs in 3013 containers packaged with chloride-bearing plutonium oxide materials. The materials were exposed to a high relative humidity environment representative of actual packaging conditions for the materials in storage. The materials were sealed in instrumented, inner 3013 containers with corrosion specimens designed to test the corrosiveness of the environment inside the containers under various conditions. This report focuses on initial loading conditions that are used to establish a baseline to show how the conditions change throughout the storage lifetime of the containers.
Ford Thermoelectric HVAC Project (Final Report)
Current light-duty vehicles provide passenger thermal comfort primarily through the use of a centralized HVAC (Heating, Ventilation, and Air Conditioning) unit that distributes conditioned air to vent locations throughout the vehicle. A substantial portion of the air energy content is spent conditioning various elements of the vehicle's interior structures. This is not an overwhelming issue in today’s vehicles, but as pressure builds to improve powertrain efficiency, the energy available to provide occupant comfort will decrease. Thermoelectric devices were identified by the US Department of Energy as one method to potentially reduce HVAC-related energy consumption in vehicles. The objective of the Ford Thermoelectric HVAC Project was to identify a technical and business approach to accelerate research and development of light-duty automotive thermoelectric HVAC technology. A zonal HVAC system was developed to provide thermal comfort to each occupant, with the objective of reducing the overall power consumed by the HVAC system compared with a baseline system. The system was designed to provide a basis for a down-sized central HVAC unit, while providing equivalent comfort and equivalent heating/cooling time-to-comfort at startup, and reduce the energy consumed to provide these functions. Project success was evaluated using occupant comfort and energy consumption metrics, based on a novel thermal comfort-modeling approach, and empirical testing. The ability to produce and market the thermoelectric devices developed in this program was assessed by a business analysis that outlined key steps required for thermoelectric HVAC devices to come to market. Key hardware and controls attribute requirements were identified to determine how they contribute to the commercialization potential of the technology. Final testing and analysis showed that use of thermal comfort and zonal design criteria reduced the energy consumption of the climate control system in both heating and cooling tests, and were significantly better in low vehicle occupancy cases where zonal strategies could be employed. Thermoelectric devices were utilized in the vehicle design to support achieving the technical performance goals of the project. It was found that these devices need additional development in order to address commercial issues, due to their cost and performance limitations.
Hydrogeological assessment of CO2 containment assurance and wellbore integrity at a Gulf Coast storage site
Abstract A large-scale carbon capture and storage (CCS) initiative on the Texas Gulf Coast serves as a premier demonstration of the U.S. Department of Energy’s CarbonSAFE program. Targeting deep saline formations, specifically Oligo-Miocene deltaic sequences, the project aims to establish technical and commercial viability for geologic CO2 storage within a major industrial corridor. This study provides a rigorous hydrogeological assessment to support Class VI permitting by quantifying the high degree of containment security. Utilizing a compositional reservoir simulator, we developed a suite of 27 distinct simulation cases to evaluate vertical plume dynamics near both planned injection wells and proximal legacy infrastructure. To ensure numerical accuracy near wellbores, we implemented a refined mesh strategy, determining that a 5.6 ft × 5.6 ft grid refinement offered the optimal balance between computational efficiency and descriptive precision. The modeling framework utilized a systematic sensitivity-based approach to evaluate the mechanical redundancy of the subsurface system by performing a bounding analysis of wellbore interfaces against hypothetical high-permeability microannuli. By systematically isolating competing physical drivers, including permeability, porosity, gas hysteresis, thermal gradients, salinity, and solubility trapping (quantified via Henry’s law with dynamically adjusted coefficients), this work moves beyond binary assessments to establish a nuanced hierarchy of containment factors. The results confirm that primary trapping mechanisms (e.g., gas hysteresis and solubility), combined with the site's unique geomechanical stratigraphy, significantly restrict vertical mobility and reinforce the robust containment security of the reservoir. Baseline results demonstrate substantial vertical separation between the CO2 plume and the upper confining system, ensuring robust containment. Sensitivity analysis reveals that even under highly conservative bounding scenarios—assuming theoretical 10-Darcy pathways at specific wellbore locations—the 2,900-ft thick multi-layered confining zone remains a reliable barrier. In these hypothetical upper-bound cases, peak upward fluxes of CO2 and saltwater after 15 years of injection remain localized and dissipate rapidly within the lower sections of the confining interval, leaving the integrity of the seal uncompromised. Furthermore, the study identifies that while localized wellbore pathways define theoretical upper bounds of vertical migration, the Area of Review (AoR) is primarily sensitive to regional thermal gradients and hysteresis, which can influence the AoR by over 3,000 acres in pessimistic configurations. Also, primary trapping mechanisms, specifically gas hysteresis and solubility, work in tandem with the Gulf Coast’s unique geomechanical stratigraphy to significantly restrict vertical mobility. Ductile, smectite-rich mudstones facilitate natural borehole convergence and the self-healing of potential conduits, creating a natural geomechanical bridge that effectively mitigates migration potential at both current injection points and legacy-well locations. This comprehensive modeling effort demonstrates that the integration of high-resolution wellbore simulations and regional geomechanical observations confirms the long-term storage security of the studied site, providing a physics-based foundation for industrial-scale CCS deployments. This modeling framework establishes a baseline for future research into coupled geomechanical effects, such as time-dependent borehole convergence, to further refine long-term containment projections. Acknowledgements We thank the Gulf Coast Carbon Center (GCCC) at the Bureau of Economic Geology for foundational research support. We appreciate Alex Bump for technical guidance and David Hoffman for model mesh generation. This work used TACC’s Frontera cluster for simulations and CMG Ltd. software licenses provided to UT-Austin. This material is based upon work supported by the Department of Energy under Award Number DE-FE0032338. Disclaimer This material is based upon work supported by the U.S. Department of Energy’s Fossil Energy and Carbon Management Office under the CarbonSAFE program, award Number DE-FE0032338. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
Hydrogeological assessment of CO2 containment assurance and wellbore integrity at a Gulf Coast storage site
Abstract A large-scale carbon capture and storage (CCS) initiative on the Texas Gulf Coast serves as a premier demonstration of the U.S. Department of Energy’s CarbonSAFE program. Targeting deep saline formations, specifically Oligo-Miocene deltaic sequences, the project aims to establish technical and commercial viability for geologic CO2 storage within a major industrial corridor. This study provides a rigorous hydrogeological assessment to support Class VI permitting by quantifying the high degree of containment security. Utilizing a compositional reservoir simulator, we developed a suite of 27 distinct simulation cases to evaluate vertical plume dynamics near both planned injection wells and proximal legacy infrastructure. To ensure numerical accuracy near wellbores, we implemented a refined mesh strategy, determining that a 5.6 ft × 5.6 ft grid refinement offered the optimal balance between computational efficiency and descriptive precision. The modeling framework utilized a systematic sensitivity-based approach to evaluate the mechanical redundancy of the subsurface system by performing a bounding analysis of wellbore interfaces against hypothetical high-permeability microannuli. By systematically isolating competing physical drivers, including permeability, porosity, gas hysteresis, thermal gradients, salinity, and solubility trapping (quantified via Henry’s law with dynamically adjusted coefficients), this work moves beyond binary assessments to establish a nuanced hierarchy of containment factors. The results confirm that primary trapping mechanisms (e.g., gas hysteresis and solubility), combined with the site's unique geomechanical stratigraphy, significantly restrict vertical mobility and reinforce the robust containment security of the reservoir. Baseline results demonstrate substantial vertical separation between the CO2 plume and the upper confining system, ensuring robust containment. Sensitivity analysis reveals that even under highly conservative bounding scenarios—assuming theoretical 10-Darcy pathways at specific wellbore locations—the 2,900-ft thick multi-layered confining zone remains a reliable barrier. In these hypothetical upper-bound cases, peak upward fluxes of CO2 and saltwater after 15 years of injection remain localized and dissipate rapidly within the lower sections of the confining interval, leaving the integrity of the seal uncompromised. Furthermore, the study identifies that while localized wellbore pathways define theoretical upper bounds of vertical migration, the Area of Review (AoR) is primarily sensitive to regional thermal gradients and hysteresis, which can influence the AoR by over 3,000 acres in pessimistic configurations. Also, primary trapping mechanisms, specifically gas hysteresis and solubility, work in tandem with the Gulf Coast’s unique geomechanical stratigraphy to significantly restrict vertical mobility. Ductile, smectite-rich mudstones facilitate natural borehole convergence and the self-healing of potential conduits, creating a natural geomechanical bridge that effectively mitigates migration potential at both current injection points and legacy-well locations. This comprehensive modeling effort demonstrates that the integration of high-resolution wellbore simulations and regional geomechanical observations confirms the long-term storage security of the studied site, providing a physics-based foundation for industrial-scale CCS deployments. This modeling framework establishes a baseline for future research into coupled geomechanical effects, such as time-dependent borehole convergence, to further refine long-term containment projections. Acknowledgements We thank the Gulf Coast Carbon Center (GCCC) at the Bureau of Economic Geology for foundational research support. We appreciate Alex Bump for technical guidance and David Hoffman for model mesh generation. This work used TACC’s Frontera cluster for simulations and CMG Ltd. software licenses provided to UT-Austin. This material is based upon work supported by the Department of Energy under Award Number DE-FE0032338. Disclaimer This material is based upon work supported by the U.S. Department of Energy’s Fossil Energy and Carbon Management Office under the CarbonSAFE program, award Number DE-FE0032338. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search
High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.
U.S. Department of Energy Pacific Region Clean Energy Application Center (PCEAC)
The U.S. Department of Energy Pacific Region Clean Energy Application Center (PCEAC) was formed in 2009 by the U.S. Department of Energy (DOE) and the California Energy Commission to provide education, outreach, and technical support to promote clean energy -- combined heat and power (CHP), district energy, and waste energy recovery (WHP) -- development in the Pacific Region. The region includes California, Nevada, Hawaii, and the Pacific territories. The PCEAC was operated as one of nine regional clean energy application centers, originally established in 2003/2004 as Regional Application Centers for combined heat and power (CHP). Under the Energy Independence and Security Act of 2007, these centers received an expanded charter to also promote district energy and waste energy recovery, where economically and environmentally advantageous. The centers are working in a coordinated fashion to provide objective information on clean energy system technical and economic performance, direct technical assistance for clean energy projects and additional outreach activities to end users, policy, utility, and industry stakeholders. A key goal of the CEACs is to assist the U.S. in achieving the DOE goal to ramp up the implementation of CHP to account for 20% of U.S. generating capacity by 2030, which is estimated at a requirement for an additional 241 GW of installed clean technologies. Additional goals include meeting the Obama Administration goal of 40 GW of new CHP by 2020, key statewide goals such as renewable portfolio standards (RPS) in each state, California’s greenhouse gas emission reduction goals under AB32, and Governor Brown’s “Clean Energy Jobs Plan” goal of 6.5 GW of additional CHP over the next twenty years. The primary partners in the PCEAC are the Department of Civil and Environmental Engineering and the Energy and Resources Group (ERG) at UC Berkeley, the Advanced Power and Energy Program (APEP) at UC Irvine, and the Industrial Assessment Centers (IAC) at San Diego State University and San Francisco State University. The center also worked with a wide range of affiliated groups and industry, government, NGO, and academic stakeholders to conduct a series of CHP education and outreach, project technical support, and related activities for the Pacific region. Key PCEAC tasks have included: - Preparing, organizing and conducting educational seminars on various aspects of CHP - Conducting state baseline assessments for CHP - Working with state energy offices to prepare state CHP action plans - Providing technical support services including CHP/district energy project feasibility screenings - Working with state agencies on CHP policy development - Developing additional CHP educational materials The primary specific services that PCEAC has offered include: - A CHP “information clearinghouse “ website: http://www.pacificcleanenergy.org - Site evaluations and potential projects screenings - Assessment of CHP status, potential, and key issues for each state - Information and training workshops - Policy and regulatory guidance documents and other interactions These services were generally offered at no cost to client groups based on the DOE funding and additional activities supported by the California Energy Commission, except for the in-kind staff resources needed to provide input data and support to PCEAC assessments at host sites. Through these efforts, the PCEAC reached thousands of end-users and directly worked with several dozen organizations and potential CHP “host sites” from 2009-2013. The major activities and outcomes of PCEAC project work are described.
Commercial Building Prototypes Based on ANSI/ASHRAE/IES Standard 90.1-2019 Appendix G PRM: Technical Support Document
The two paths for documenting compliance with ANSI/ASHRAE/IES Standard 90.1 are the prescriptive path and the performance path. Beyond code programs and rating systems (for example, USGBC-LEED ) are primarily known to use a third path – the Appendix G Performance Rating Method. An update in the 2016 edition of Standard 90.1 approved the Appendix G Performance Rating System for code compliance, extending its application and allowing for greater consistency of modeling rules for code and beyond code building energy modeling. The Appendix G PRM provides rules for the development of whole building energy models of baseline and proposed models for calculating the “performance cost index target” value using the simulated energy results of the baseline and proposed models and the building performance factors published in Table 4.2.1.1 of the Standard. This report documents (1) the methodology used for development of the baseline and proposed energy models of the Pacific Northwest National Laboratory and U.S. Department of Energy commercial building prototypes using the Appendix G Performance Rating Method; and (2) the building performance factors that were calculated using those models.
Non-destructive structural characterization of graphite components using mechanical resonance and deep learning
As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.