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At least 847 records · Page 47

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory: by collapsing the wavefunction, it can enable phenomena such as teleportation and thereby alter the ‘arrow of time’ that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space–time that go beyond the established paradigms for characterizing phases, either in or out of equilibrium. For present-day noisy intermediate-scale quantum (NISQ) processors, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling to measurement-induced teleportation. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Infrared compatible rapid mixer to probe millisecond chemical kinetics

Fast microfluidic mixers are a valuable tool for studying solution-phase chemical reaction kinetics and molecular processes with spectroscopy. However, microfluidic mixers that are compatible with infrared vibrational spectroscopy have seen only limited development due to the poor infrared transparency of the current microfabrication material. We describe the design, fabrication, and characterization of CaF2-based continuous flow turbulent mixers, which are capable of measuring kinetics in the millisecond time window with infrared spectroscopy, when integrated into an infrared microscope. Kinetics measurements demonstrate the ability to resolve relaxation processes with 1 millisecond time resolution, and straightforward improvements are described that should result in sub-100 µs time-resolution.

Instruments & Instrumentation↗

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fiber-coupled digital photo sensors for large Time Projection Chambers

Here, this paper presents a novel approach to addressing challenges in neutrino event reconstruction within large Time Projection Chambers (TPCs). By integrating fiber-coupled digital silicon photomultipliers, we propose a design that enhances light detection and improves both energy resolution and event reconstruction. Advancements in power and signal over fiber technologies are leveraged to deploy digital sensors within the TPC bulk volume, enabling precise timing and robust particle identification.

47 OTHER INSTRUMENTATION↗

Characterization of the CMS Endcap Timing Layer readout chip prototype with charge injection

We present the characterization of a readout Application-Specific Integrated Circuit (ASIC) for the CMS Endcap Timing Layer (ETL) of the High-Luminosity LHC upgrade with charge injection. The ASIC, named ETROC and developed in a 65 nm CMOS technology, reads out a 16× 16 pixel matrix of the Low-Gain Avalanche Detector (LGAD). The jitter contribution from ETROC is required to be below 40 ps to achieve the 50 ps overall time resolution per hit. The analog readout circuits in ETROC consist of the preamplifier and the discriminator. The preamplifier handles the LGAD charge signal with the most probable value of around 15 fC. The discriminator generates the digital pulse, which provides the Time-Of-Arrival (TOA, leading edge) and Time-Over-Threshold (TOT, pulse width) information. The prototype of ETROC (ETROC0) that implements a single channel of analog readout circuits has been evaluated with charge injection. The jitter of the analog readout circuits, measured from the discriminator's leading edge, is better than 16 ps for a charge larger than 15 fC with the sensor capacitance. The time walk resulting from different pulse heights can be corrected using the TOT measurement. The time resolution distribution has a standard deviation of 29 ps after the time-walk correction from the charge injection. At room temperature, the preamplifier's power consumption is measured to be 0.74 mW and 1.53 mW per pixel in the low- and high-power mode, respectively. Finally, the measured power consumption of the discriminator is 0.84 mW per pixel. With the ASIC alone or the LGAD sensor, The characterization performances fulfill the ETL's challenging requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

Abstract The regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

58 GEOSCIENCES↗

Cyber-Physical System: Design for Sustainability and Resilience

When considering the design tools needed in the transition from numeric models to pilot plant, cyber-physical systems (CPS) come to the forefront as a method to model complex integrated energy systems. CPS approach has proven to be valuable to identify opportunities for economically viable early adoption of integrated energy technologies. This tutorial will introduce the concepts and the roles of CPS in co-design to minimize risks for pilot plant and technology deployment. This tutorial will also layout basic requirements for the CPS development, which requires a highly interdisciplinary effort with expertise in sensors, hardware testing, real-time modeling, controls, and system integration.

Harun, Nor Farida↗

Genomic region associated with run timing has similar haplotypes and phenotypic effects across three lineages of Chinook salmon

Abstract Conserving life‐history variation is a stated goal of many management programs, but the most effective means by which to accomplish this are often far from clear. Early‐ and late‐migrating forms of Chinook salmon ( Oncorhynchus tshawytscha ) face unequal pressure from natural and anthropogenic forces that may alter the impacts of genetic variation underlying heritable migration timing. Genomic regions of chromosome 28 are known to be strongly associated with migration variation in adult Chinook salmon, but it remains unclear whether there is consistent association among diverse lineages and populations in large basins such as the Columbia River. With high‐throughput genotyping (GT‐seq) and phenotyping methods, we examined the association of genetic variation in 28 markers (spanning GREB1L to ROCK1 of chromosome 28) with individual adult migration timing characteristics gleaned from passive integrated transponder recordings of over 5000 Chinook salmon from the three major phylogeographic lineages that inhabit the Columbia River Basin. Despite the strong genetic differences among them in putatively neutral genomic regions, each of the three lineages exhibited very similar genetic variants in the chromosome 28 region that were significantly associated with adult migration timing phenotypes. This is particularly notable for the interior stream‐type lineage, which exhibits an earlier and more constrained freshwater entry than the other lineages. In both interior stream‐type and interior ocean‐type lineages of Chinook salmon, heterozygotes of the most strongly associated linkage groups had largely intermediate migration timing relative to homozygotes, and results indicate codominance or possibly marginal partial dominance of the allele associated with early migration. Our results lend support to utilization of chromosome 28 variation in tracking and predicting run timing in these lineages of Chinook salmon in the Columbia River.

Willis, Stuart C.↗

Feasibility Study for Cathodic Protection of Waste Tanks at Hanford

The Hanford Nuclear Reservation site contains approximately 211 million liters of radioactive and chemically hazardous waste arising from nuclear weapons production, beginning with World War II, and continuing through the Cold War. The waste is stored in 177 carbon-steel underground storage tanks, of which 149 are single-shell tanks (SSTs) and the remaining are double-shell tanks (DSTs). The mission of an ongoing River Protection Project is to retrieve the waste from the underground storage tanks and then treat and immobilize (i.e., vitrify) it for disposal. Waste from the older SSTs is being progressively retrieved into the newer DSTs for storage pending treatment, immobilization, and disposal. Waste chemistry controls are in place to mitigate general corrosion, pitting corrosion, and stress corrosion cracking (SCC) and minimize corrosion risks to the carbon steel tank liners of DST at the Hanford Site. The chemistry control program focuses on preserving liner integrity while balancing the need for caustic/nitrite additions that have large downstream impacts on vitrification. Some of the DSTs store salt cake or sludge waste layers contain out-of-specification interstitial liquids that contact the primary tank bottom or sidewall. Remediation of such layers through chemical additions is not practical. At the present time, the most significant leak integrity concern at Hanford is for corrosion of the tank bottoms of DSTs where the solids layer is out of specification because of hydroxide ion depletion and consequently, pH values that are less than 12. Cathodic protection (CP) has been proposed as a possible way to protect the liners of such tanks against corrosion. The objective of this project was to investigate the feasibility of applying CP to Hanford DSTs to mitigate internal corrosion of the carbon steel tank primary liners. The scope of the project included (1) a literature review on the application of CP to storage tank systems, in general, and to waste tanks at the Savannah River Site (SRS) and Hanford, (2) a review of the finite element analysis (FEA) model recently developed to evaluate potentials for a DST, and (3) the development of a boundary element analysis (BEA) model for CP for a DST. Tank AN-107, one of the Hanford DSTs, was selected for this work because (1) the bottommost waste layer in the tank is out-of-specification, and (2) electrochemical and resistivity data, based on recent waste sampling and testing, are available for this tank. The overarching conclusion of this study is that, based on the available information, it is feasible to apply CP to mitigate internal corrosion of the primary liners of the Hanford DSTs. However, significant additional information and work are required before a CP system can be designed. Recommendations for next steps in the design of the CP system will be presented.

WIERSMA, BRUCE↗

Monitoring the Possible Effects of Corroding Fuel Cladding in Nuclear Ponds: a Modified ROV for Storage Ponds - 20144

Nuclear ponds are used worldwide to store radioactive nuclear material, often for extended periods of time. The pond water conditions need to be closely monitored so that mitigation strategies can be put in place should any leakage of radioactive material occur. This paper describes the selection, development and on-site deployment of a bespoke system whose design was based on of-the-shelf components. The system is able to identify, locate and differentiate the leakage of radioactive material stored in nuclear ponds from the background activity of the water in the pond. The selection of an appropriate detector and monitoring geometry was supported by MCNP modelling which allowed a high degree of confidence in the proposed design. The development of the system allowed a real-time indication of the canister integrity, without incurring the increased operator doses from manual sampling operations that were previously used on site. The benefits of the developed system include the fact that the system is lightweight, easily deployable, retrievable, decontaminable and results in negligible waste products. Moreover, it is able to analyse the samples in-situ, in this way reducing the time needed to manually collect and send the samples to a laboratory for lengthy analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗

Catalyst Layer Design, Manufacturing and In-line Quality Control

In this project we successfully demonstrated the capabilities of the Reactive Spray Deposition Technology (RSDT) to fabricate large-scale CCMs for advanced PEMWEs that have one-order of magnitude lower PGM loading in their catalyst layers, and performance comparable with the commercial state-of-the-art CCMs. The RSDT is a unique methodology that combines the catalyst synthesis and CCM fabrication in one step and reduces dramatically the time for CCM manufacturing. As fabricated large-scale CCMs with geometric area of 680 cm2 demonstrated excellent activity and durability performance, and the novel duo-recombination layer design paves the way for solving the safety concerns related to PEMWEs. In addition, excellent activity and durability performance has been demonstrated with RSDT fabricated CCMs with thinner membranes and duo RL design. This is a novel approach for further performance improvement of the MEAs for PEMWEs that has been successfully demonstrated for the first time in this project. The integration of the in-situ laser diagnostics system along with the in-line optical quality control system within the RSDT that has been achieved and demonstrated in this project, is an example for possibility of designing and building advanced manufacturing technologies that can meet the requirements of the future manufacturing. Therefore, the RSDT offers a precise real-time monitoring and control of the particles size, composition, loading, porosity, thickness, and defects in the catalysts’ layers, which render this technology as the best candidate for manufacturing of cost effective CCMs for PEMWEs. By using RSDT we successfully met all project’s milestones, Go/No-Go decision, objectives, goals, and deliverables.

08 HYDROGEN↗

Probabilistic Discrete‐Time Models for Spreading Processes in Complex Networks: A Review

Abstract Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread.

Granell, Clara↗

Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems

In this article, we introduce an adaptive on-line model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on historical data for offline model identification, our approach utilizes real-time data for continuous model updates. This method integrates seamlessly with existing online control and optimization algorithms and provides timely updates in response to real-time changes. This methodology offers significant advantages, including a reduction in the communication network bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt after disturbances. Furthermore, our algorithm is tailored for non-linear convex models, enhancing its applicability to practical scenarios. The efficacy of the proposed method is validated through a numerical study, demonstrating improved control performance using a synthetic IEEE test case.

data-driven model predictive control↗

2022 FORCE Development Status Update

Integrated energy systems (IESs) are essential for decarbonizing electricity and industrial sectors and fully exploiting these systems requires sophisticated planning, scheduling, and dispatching tools to maximize their socio-economic benefits. The Framework for Optimization of Resources and Economics (FORCE) is a tool suite developed at Idaho National Laboratory and is dedicated to making robust analyses of IESs easier for analysts and researchers. The report summarizes the improvements and updates to FORCE during the most recent development cycle. Particularly, we demonstrate improvements to user accessibility, stochastic time-series analysis, and vertical integration with the software tools provided in FORCE.

97 MATHEMATICS AND COMPUTING↗

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

Multi-Commodity Traffic Signal Control and Routing With Connected Vehicles

We report a real-time traffic management policy that integrates traffic signal control and multi-commodity routing of connected vehicles in networks with multiple destinations is developed. The proposed policy is based on a multi-commodity formulation of the store-and-forward model and assumes all vehicles are able to exchange information with the infrastructure. Vehicles share information about their current location and final destination. Based on this information, the strategy determines both optimized signal timings at every intersection and vehicle-specific routing information at every link of the network. The control actions, i.e., signal times and routing information, are updated at every cycle and delivered by a finite horizon optimal control problem cast into a rolling horizon framework. The underlying optimization problem is convex, and thus the method is suitable for real-time operation in large networks. The method is validated via a micro-simulation study in networks with up to twenty intersections and, in all simulations, outperforms a real-time traffic-responsive signal control strategy that is based on a single-commodity store-and-forward model. The scalable computation effort for increasing network sizes and prediction horizon confirms the computational efficiency of the method.

42 ENGINEERING↗