Continuous-Domain Real-Time Distributed ADMM Algorithm for Aggregator Scheduling and Voltage Stability in Distribution Network
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Automation & Control Systems↗
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Gluon distributions and their applications to Ioffe-time distributions
We investigate unpolarized and polarized gluon distributions and their applications to the Ioffe-time distributions, which are related to lattice QCD calculations of parton distribution functions. Guided by the counting rules based on the perturbative QCD at large momentum fraction x and the color coherence of gluon couplings at small x, we parametrize gluon distributions in the helicity basis. By fitting the unpolarized gluon distribution, the inferred polarized gluon distribution from our parametrization agrees with the one from global analysis. A simultaneous fit to both unpolarized and polarized gluon distributions is also performed to explore the model uncertainty. The agreement with the global analysis supports the (1 - x) power suppression of the helicity-antialigned distribution relative to the helicity-aligned distribution. The corresponding Ioffe-time distributions and their asymptotic expansions are calculated from the gluon distributions. Our results of the Ioffe-time distributions can provide guidance to the extrapolation of lattice QCD data to the region lacking precise gluonic matrix elements. Therefore, they can help regulate the ill-posed inverse problem associated with extracting the gluon distributions from discrete data from first-principle calculations, which are available in a limited range of the nucleon momentum and the spatial separation between the gluonic currents. Given various limitations in obtaining lattice QCD data at large Ioffe time, phenomenological approaches can provide important complementary information to extract the gluon distributions in the entire momentum fraction region, especially at small x. The possibility of investigating higher-twist effects and other systematic uncertainties in the contemporary first-principle calculations of parton distributions from phenomenologically well-determined Ioffe-time distributions in the large Ioffe-time region is also discussed.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Data and scripts associated with a manuscript on residence time distribution simulation in two 10-kilometer long river sections
This data package is associated with the publication “On the Transferability of Residence Time Distributions in Two 10-km Long River Sections with Similar Hydromorphic Units” submitted to the Journal of Hydrology (Bao et al. 2024).Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface, along with their residence time distributions (RTDs) in the subsurface, is crucial for managing water quality and ecosystem health in dynamic river corridors. However, directly simulating high-spatial resolution HEFs and RTDs can be a time-consuming process, particularly for watershed-scale modeling. Efficient surrogate models that link RTDs to hydromorphic units (HUs) may serve as alternatives for simulating RTDs in large-scale models. One common concern with these surrogate models, however, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this, we evaluated the HEFs and the resulting RTD-HU relationships for two 10-kilometer-long river corridors along the Columbia River, using a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework that we previously developed. Applying this framework to the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. This data package includes the model inputs files and the simulation results data. This data package contains 10 folders. The modeling simulation results data are in the folders 100H_pt_data and 300area_pt_data, for the study domain Hanford 100H and 300 area respectively. The remaining eight folders contain the scripts and data to generate the manuscript figures. The file-level metadata file (Bao_2024_Residence_Time_Distribution _flmd.csv) includes a list of all files contained in this data package and descriptions for each. The data dictionary file (Bao_2024_Residence_Time_Distribution _dd.csv) includes column header definitions and units of all tabular files.
54 ENVIRONMENTAL SCIENCES↗
River Dynamics Control Transit Time Distributions and Biogeochemical Reactions in a Dam-Regulated River Corridor
Residence Time Distributions (RTDs) exert an important control on biogeochemical translation in the hydrological systems. Previous tracer studies have revealed that RTDs often followed time-invariant exponential, lognormal, or heavy-tailed RTDs that have power-law behavior for long tails in headwater or low-order streams. However, there is a recognition that RTDs can be more complicated and time-variable in response to dynamic hydrological forcing. Here, we use particle tracking to estimate RTDs along the Hanford Reach of the Columbia River and to quantify the influences of river stage fluctuations. Particle tracking is conducted using the velocity field from high-resolution 3D groundwater flow simulations. The effects of hydrological forcing on the residence time distribution were evaluated by varying river flow boundary conditions and releasing particles in different time windows. Our results revealed that dynamic stage fluctuations created rapidly changing losing-gaining conditions in the river and led to highly transient RTDs, which contributes to multiple modes of RTDs. Dam-induced high-frequency (sub-daily) flow variation contributes to the short-time (sub-daily) component of the RTDs. Deviation of the reactant consumption under the single-mode assumption compared to the multimodal RTDs is relatively small (~5%) and appears when the Damköhler number was close to one.More specifically, high-frequency (daily) dam-induced stage variations have higher impacts on biogeochemical reactions with faster reaction rate, and can potentially increase the reactant consumption by 26.68%. Based on these findings, we suggest that current river basin models could be improved by including bank storage and more complex RTDs influenced by both short and long term river stage fluctuations.
54 ENVIRONMENTAL SCIENCES↗
An Investigation of Time Distributions for Task Primitives to Support the HUNTER Dynamic Human Reliability Analysis
As an effort to support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method. GOMS-HRA was developed to provide cognition-based time and human error probability information for dynamic HRA calculation in the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework. HUNTER is a framework to support the dynamic modelling of human error in conjunction with other modelling tools. In this paper, we investigate time distributions using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which suggests an HRA data collection framework to complement full-scope simulator research as well as collect input data for dynamic HRA using simplified simulators such as the Rancor Microworld Simulator. In this study, time required for GOMS-HRA task primitives to satisfy thirteen statistical distributions is investigated. Then, the time distributions from student operators and professional operators are compared and discussed. As a result, this study identified several time distributions on five GOMS-HRA task primitives at a statistically significant level. According to analyses to date, a greater number of significant time distributions was found in abnormal or emergency operating procedures rather than standard operating procedures. In the future, it is expected that the result of this study can provide objective reference on elapsed time data for task primitives as well as help to realistically simulate scenarios within dynamic HRA.
99 GENERAL AND MISCELLANEOUS↗
Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis
The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.
99 GENERAL AND MISCELLANEOUS↗
Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis
To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.
Dynamic Human Reliability Analysis↗
Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River
Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.
97 MATHEMATICS AND COMPUTING↗
On the transferability of residence time distributions in two 10-km long river sections with similar hydromorphic units
Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface and their residence time distributions (RTDs) in the subsurface are important for managing the water quality and ecosystem health in dynamic river corridors. However, direct simulating high-spatial resolution HEFs and RTDs can be time-consuming, especially for watershed-scale modeling. Efficient surrogate models linking RTDs to hydromorphic units (HUs) can be alternatives for simulating RTDs in large-scale models. A common concern of these surrogate models, though, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this issue, this work evaluates the HEFs and resulting RTD-HU relationships for two 10-km long river corridors along the Columbia River leveraging a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework we previously developed. Applying such a framework at the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. Finally, our comparison shows that the similarity and transferability of the RTD-HU relationship is very low for the two investigated river sections, which suggests that devising a general algorithm to estimate RTDs based solely on surface water hydrodynamics and short-distance river channel topography data, as well as HU classification, might be nearly impossible.
54 ENVIRONMENTAL SCIENCES↗
Timing Distribution Test for Mu2e Experiment
Various tests and reconfigurations have been made to improve the timing distribution for the TDAQ subsystem of the Mu2e experiment. Additionally, efforts have been made to allow remote access to various teams involved in the development and testing of the DIRAC board.
Dewey, Brianna↗
Resilient Design of Continuous-time Distributed Optimization Algorithm in the Presence of Cyber-attacks
This paper presents a continuous-time resilient distributed optimization algorithm based on competitive interaction design method on connected graphs in the presence of adversaries. Here, the competitive interaction method allows us to design a network that protects the multi-agent systems from adversaries without requiring high network connectivity. In addition, the proposed algorithm does not require the global information about the number of adversaries. First, we show that the proposed distributed algorithm solves the resilient distributed optimization problem with no attack on the communication links. Second, we show that the proposed continuous-time distributed optimization algorithm on connected graphs converges to the small neighborhood of the optimal solution in the presence of cyber-attacks onto the communication channel. Simulations are presented to illustrate our theoretical results.
97 MATHEMATICS AND COMPUTING↗
Assessment of the impact of reactor residence time distribution on non-equilibrium product selectivity of polypropylene pyrolysis using reactive molecular dynamics simulations
Mass residence time distribution (RTD) is considered to be an important factor controlling the product selectivity in the pyrolysis of biomass and plastic wastes along with the pyrolysis chemistry. However, due to the complex pyrolysis chemistry of biomass and plastic waste, the coupling between the reaction chemistry, RTD, and product selectivity is challenging to understand. Here, we introduce a reaction molecular dynamics-based method to examine pyrolysis chemistry and species timescales to assess the impact of RTD on product selectivity and yield. To validate this method, reactive molecular dynamics simulations were conducted for polypropylene pyrolysis and its non-equilibrium product selectivity using 6 different RTDs. We find that the RTD and the reaction chemistry control the peak non-equilibrium product concentrations. The peak monomer (C 3 H 6 ) concentration during pyrolysis can be increased by up to 25 % by using a narrow RTD in the case of polypropylene pyrolysis. We also find that product selectivity is strongly affected by the average residence time and RTD. This coupling between the reaction chemistry, RTD, and product selectivity highlights the need to understand detailed reaction chemistry to control RTD and optimize non-equilibrium product selectivity during polymer and biomass pyrolysis. The present method provides a new way to design RTD for reactors to reach maximized product selectivity of plastic waste and biomass.
33 ADVANCED PROPULSION SYSTEMS↗
Real-Time Distributed Control of Smart Inverters for Network-level Optimization
The limitations of centralized optimization methods in managing electric power distribution systems operations have led to the distributed paradigm of computing and decision-making. Unfortunately, the existing distributed optimization algorithms are limited in their applicability to managing fast varying phenomena such as those resulting from highly variable Distributed Energy Resource (DER) generation patterns. They require a large number of communication rounds (in the order of 10 2 to 10 3 ) among the computing agents to solve one instance of the optimization problem. Related real-time distributed control methods are equally limited in their applications to power distribution systems with fast-changing DER generation; they require hundreds of rounds of communication and thus are slow in tracking the network-level optimal solutions. In this paper, we propose a novel distributed voltage controller that provides a fast-tracking of rapidly varying DER generation profiles while simultaneously converging to network-level optimal solutions within a few communication rounds. The proposed control algorithm leverages the radial topology of the system, which reduces the required communication rounds to reach the network-level optimum solution by order of magnitude. The novelty lies in carefully reducing the electrical network model from the perspective of each distributed controller and enabling appropriate data sharing among upstream and downstream nodes to achieve fast convergence. The simulation results demonstrate the effectiveness of the proposed approach in minimizing the feeder losses while maintaining the node voltage within the pre-specified limits.
voltage control, optimization, reactive power, inv↗
Electrochemical Residence Time Distribution as a Diagnostic Tool for Redox Flow Batteries
The fluid dynamic and electrochemical performance of redox flow batteries (RFBs) stems from the relationship between the flow field and the porous electrode, whose interplay determines how active species move and react during device operation. While characterization techniques, such as residence time distribution, offer insights into species mobility within a reactive volume for a traditional chemical reactor, electrochemical reactors also enable simultaneous measurement of the redox reactions, unlocking another dimension of analysis. Herein, we demonstrate how potentiodynamic measurements, using injections of electrolyte examined through moment analysis, can provide electrode-specific performance scaling relationships across a matrix of carbon paper and cloth electrodes with flow through and interdigitated flow fields. We further combine experimental campaigns with multiphysics simulations to demonstrate how electrode surface area can be estimated with this technique, which we then validate with activated and unactivated commercial carbon cloth electrodes. These studies reveal the multiscale observations that potentiodynamic measurements afford, augmenting existing electrochemical techniques for holistic electrochemical reactor diagnostics.
Electrochemistry↗
Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows
The need for real-time processing to enable automated decision making and experimental steering has driven a shift from high-performance computing workflows on a centralized system to a distributed approach that integrates remote data sources, edge devices, and diverse compute facilities. Under this paradigm, data can be processed close to the source where it is generated, thus reducing latency and bandwidth usage. System resilience is thus a key challenge, requiring distributed workflows to survive component failures and to meet stringent quality-of-service requirements, which results in the need to mitigate anomalies such as congestion and low availability of resources. To address these challenges, we propose Diaspora, a unified resilience framework that is inspired by event-driven communication patterns used in public clouds. Specifically, we propose an event fabric that extends across sites, facilities, and computations to provide timely, reliable, and accurate information about data, application, and resource status. On top of the event fabric, we build resilience-enabling services that combine QoS-aware data streaming, resilient data views, resilient compute and data resources, and anomaly detection and prediction, all of which collectively enhance workflow resilience for these scientific cases.
Rao, Nageswara↗
Insights Into Seismicity Associated With Flexibly Operating Enhanced Geothermal System From Real‐Time Distributed Acoustic Sensing
Enhanced Geothermal Systems (EGS) have the capacity to broaden the accessible resource pool for geothermal power generation. Traditionally viewed as a “baseload” resource, their flexible operation might also enable dispatchable load‐following generation and long‐term energy storage, aligning them with the evolving landscape of decarbonized electricity systems. However, increasing permeability and extracting energy during EGS operations can induce microseismic events; for many prior EGS efforts, some associated seismicity has been observed. While energetically beneficial, the flexibility of EGS operations prompts our inquiry into whether new types of operations will yield previously unseen seismicity patterns. We demonstrate the use of distributed acoustic sensing (DAS) with real‐time edge computing to monitor seismicity during a pilot test of a cyclically operated EGS facility at the Blue Mountain geothermal field. Our focus lies in uncovering seismicity insights from the real‐time microseismic catalog, particularly during load‐following dispatchability tests simulating flexible EGS operation. Here, we find that variations in pore pressure consistently correlate with seismicity, and that controlling pressure cycles during flexible operations appears to constrain microseismic activity during subsequent cycles. The spatio‐temporal evolution of microseismic clouds recorded during cyclic injection cycles fits diffusive models over our available observation period. Additionally, seismicity elevation lags behind pore pressure increases, likely due to pressure diffusion to the fracture system boundary. Through real‐time monitoring, we offer novel insights into seismicity associated with flexibly operating EGS. Our findings suggest that leveraging DAS and edge computing can inform EGS operations and help mitigate induced seismicity.
Chamarczuk, Michal [Rice Univ., Houston, TX (Unite↗
Gluon helicity from global analysis of experimental data and lattice QCD Ioffe time distributions
We perform a new global analysis of spin-dependent parton distribution functions with the inclusion of Ioffe time pseudodistributions computed in lattice QCD (LQCD), which are directly sensitive to the gluon helicity distribution, Δ g . These lattice data have an analogous relationship to parton distributions as do experimental cross sections, and can be readily included in global analyses. We focus in particular on the constraining capability of current LQCD data on the sign of Δ g at intermediate parton momentum fractions x , which was recently brought into question by analysis of data in the absence of parton positivity constraints. We find that present LQCD data cannot discriminate between positive and negative Δ g solutions, although significant changes in the solutions for both the gluon and quark sectors are observed. Published by the American Physical Society 2024
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A real-time distributed solid oxide electrolysis cell (SOEC) model for cyber-physical simulation
System integration and dynamic operability between SOEC and balance-of-plant (BoP) components are major technical challenges before realizing rapid load following of SOEC systems. Cyber-physical simulation (CPS) is a leading-edge digital engineering approach and is regarded as the next step beyond Digital Twins. CPS approach can be used to research SOEC system integration and develop dynamic controls prior to actual pilot testing without using a real SOEC. To seamlessly couple with BoP hardware and access non-observable operational parameters (e.g., local temperature gradient) during transients, a distributed one-dimensional (1D) real-time SOEC model was developed. Its real-time execution was demonstrated for 20 to 640 nodes at the fixed time step of 5 ms. A higher excess air ratio enabled smaller local temperature gradients on SOEC solid materials and faster transients upon current density step change from 0.15 to 0.55 A cm -2 . During the transients, the magnitude of the peak temperature gradient nearly doubled in 10 s from -3.5 to -5.9 °C cm -1 . This represents a significant operating risk that can impact the dynamic operability of SOEC systems. In addition, the local temperature gradient was found to change directions on all nodes in SOEC solid materials, with the greatest impact on the upstream nodes. The SOEC model was also tested at the thermal neutral voltage using actual process air flow parameters as variable model inputs. Variable process air temperatures were found to induce alternating local temperature gradients on SOEC solid materials. These are new operational mechanisms for SOEC degradation relevant for load following operational modes yet distinct from previous reports. To mitigate these unfavorable features, the SOEC can be operated at voltages that are slightly (±20 mV) deviated from the thermal neutral voltage. Here, the corresponding net thermal energy change was less than 1.6% of the electric power consumption. This 1D real-time SOEC model established the basis of cyber-physical simulation of SOEC hybrid systems.
24 POWER TRANSMISSION AND DISTRIBUTION↗