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At least 73 records · Page 4

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗

Stellar coronae - What can be predicted with minimum flux models?

In order to determine the possible errors of various minimum flux corona (MFC) predictions, MFC models are compared with a grid of detailed coronal models covering a range of two orders of magnitude in coronal heating and damping length values. The MFC concept is totally unreliable in the prediction of mass loss and the relative importance of various kinds of energy losses, and MFC predictions for the mass loss rate and energy losses due to stellar wind can be wrong by many orders of magnitude. It is suggested that for future applications, the unreliable MFC formulas should be replaced by a grid of related models accounting for the coronal dependence on damping length, such as the models underlying the present study.

Hammer, R.↗

A hierarchical approach to reliability modeling of fault-tolerant systems

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

Gossman, W. E.↗

A high performance totally ordered multicast protocol

This paper presents the Reliable Multicast Protocol (RMP). RMP provides a totally ordered, reliable, atomic multicast service on top of an unreliable multicast datagram service such as IP Multicasting. RMP is fully and symmetrically distributed so that no site bears un undue portion of the communication load. RMP provides a wide range of guarantees, from unreliable delivery to totally ordered delivery, to K-resilient, majority resilient, and totally resilient atomic delivery. These QoS guarantees are selectable on a per packet basis. RMP provides many communication options, including virtual synchrony, a publisher/subscriber model of message delivery, an implicit naming service, mutually exclusive handlers for messages, and mutually exclusive locks. It has commonly been held that a large performance penalty must be paid in order to implement total ordering -- RMP discounts this. On SparcStation 10's on a 1250 KB/sec Ethernet, RMP provides totally ordered packet delivery to one destination at 842 KB/sec throughput and with 3.1 ms packet latency. The performance stays roughly constant independent of the number of destinations. For two or more destinations on a LAN, RMP provides higher throughput than any protocol that does not use multicast or broadcast.

Montgomery, Todd↗

Design, Implementation, and Verification of the Reliable Multicast Protocol

This document describes the Reliable Multicast Protocol (RMP) design, first implementation, and formal verification. RMP provides a totally ordered, reliable, atomic multicast service on top of an unreliable multicast datagram service. RMP is fully and symmetrically distributed so that no site bears an undue portion of the communications load. RMP provides a wide range of guarantees, from unreliable delivery to totally ordered delivery, to K-resilient, majority resilient, and totally resilient atomic delivery. These guarantees are selectable on a per message basis. RMP provides many communication options, including virtual synchrony, a publisher/subscriber model of message delivery, a client/server model of delivery, mutually exclusive handlers for messages, and mutually exclusive locks. It has been commonly believed that total ordering of messages can only be achieved at great performance expense. RMP discounts this. The first implementation of RMP has been shown to provide high throughput performance on Local Area Networks (LAN). For two or more destinations a single LAN, RMP provides higher throughput than any other protocol that does not use multicast or broadcast technology. The design, implementation, and verification activities of RMP have occurred concurrently. This has allowed the verification to maintain a high fidelity between design model, implementation model, and the verification model. The restrictions of implementation have influenced the design earlier than in normal sequential approaches. The protocol as a whole has matured smoother by the inclusion of several different perspectives into the product development.

Montgomery, Todd L.↗

Capillary-Driven Heat Transfer Experiment: Keeping It Cool in Space

Capillary-pumped loops (CPL's) are devices that are used to transport heat from one location to another--specifically to transfer heat away from something. In low-gravity applications, such as satellites (and possibly the International Space Station), CPL's are used to transfer heat from electrical devices to space radiators. This is accomplished by evaporating one liquid surface on the hot side of the CPL and condensing the vapor produced onto another liquid surface on the cold side. Capillary action, the phenomenon that causes paper towels to absorb spilled liquids, is used to "pump" the liquid back to the evaporating liquid surface (hot side) to complete the "loop." CPL's require no power to operate and can transfer heat over distances as large as 30 ft or more. Their reliance upon evaporation and condensation to transfer heat makes them much more economical in terms of weight than conventional heat transfer systems. Unfortunately, they have proven to be unreliable in space operations, and the explanation for this unreliability has been elusive. The Capillary-Driven Heat Transfer (CHT) experiment is investigating the fundamental fluid physics phenomena thought to be responsible for the failure of CPL's in low-gravity operations. If the failure mechanism can be identified, then appropriate design modifications can be developed to make capillary phase-change heat-transport devices a more viable option in space applications. CHT was conducted onboard the Space Shuttle Columbia during the first Microgravity Science Laboratory (MSL-1) mission, STS-94, which flew from July 1 to 17, 1997. The CHT glovebox investigation, which was conceived by Dr. Kevin Hallinan and Jeffrey Allen of the University of Dayton, focused on studying the dynamics associated with the heating and cooling at the evaporating meniscus within a capillary phase-change device in a low-gravity environment. The CHT experimental hardware was designed by a small team of engineers from Aerospace Design & Fabrication (ADF), the NASA Lewis Research Center, and the University of Dayton. The hardware consisted of two experiment modules that each contained an instrumented test loop (idealized capillary-pumped loop), a base unit for power conversion and backlighting, a display unit with 15 LED's (light-emitting diodes) to display temperatures, pressure, heater power, and time, a control unit to select heaters and heater settings, a cooling fan, and associated cables.

Lekan, Jack F.↗

Shuttle Payload Ground Command and Control: An Experiment Implementation Combustion Module-2 Software Development, STS-107

This presentation covers the design of a command and control architecture developed by the author for the Combustion Module-2 microgravity experiment, which flew aboard the STS-107 Shuttle mission, The design was implemented to satisfy a hybrid network that utilized TCP/IP for both the onboard segment and ground segment, with an intermediary unreliable transport for the space to ground segment. With the infusion of Internet networking technologies into Space Shuttle, Space Station, and spacecraft avionics systems, comes the need for robust methodologies for ground command and control. Considerations of high bit error links, and unreliable transport over intermittent links must be considered in such systems. Internet protocols applied to these systems, coupled with the appropriate application layer protections, can provide adequate communication architectures for command and control. However, there are inherent limitations and additional complexities added by the use of Internet protocols that must be considered during the design. This presentation will discuss the rationale for the: framework and protocol algorithms developed by the author. A summary of design considerations, implantation issues, and learned lessons will be will be presented. A summary of mission results using this communications architecture will be presented. Additionally, areas of further needed investigation will be identified.

Carek, David Andrew↗

A Black-Scholes Approach to Satisfying the Demand in a Failure-Prone Manufacturing System

The goal of this paper is to use a financial model and a hedging strategy in a systems application. In particular, the classical Black-Scholes model, which was developed in 1973 to find the fair price of a financial contract, is adapted to satisfy an uncertain demand in a manufacturing system when one of two production machines is unreliable. This financial model together with a hedging strategy are used to develop a closed formula for the production strategies of each machine. The strategy guarantees that the uncertain demand will be met in probability at the final time of the production process. It is assumed that the production efficiency of the unreliable machine can be modeled as a continuous-time stochastic process. Two simple examples illustrate the result.

Chavez-Fuentes, Jorge R.↗

Optimizing Air Transportation Service to Metroplex Airports: Analysis of Historical Data - Part 1

The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation (+4% annual growth), resulting in unreliable service and systemic delays. Estimates of the impact of delays and unreliable air transportation service on the economy range from $32B to $41B per year. This report describes the results of an analysis of airline strategic decision-making with regards to: (1) geographic access, (2) economic access, and (3) airline finances. This analysis evaluated markets-served, scheduled flights, aircraft size, airfares, and profit from 2005-2009. During this period, airlines experienced changes in costs of operation (due to fluctuations in hedged fuel prices), changes in travel demand (due to changes in the economy), and changes in infrastructure capacity (due to the capacity limits at EWR, JFK, and LGA). This analysis captures the impact of the implementation of capacity limits at airports, as well as the effect of increased costs of operation (i.e. hedged fuel prices). The increases in costs of operation serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed.

Donohue, George↗

High Temperature Wireless Communication And Electronics For Harsh Environment Applications

In order for future aerospace propulsion systems to meet the increasing requirements for decreased maintenance, improved capability, and increased safety, the inclusion of intelligence into the propulsion system design and operation becomes necessary. These propulsion systems will have to incorporate technology that will monitor propulsion component conditions, analyze the incoming data, and modify operating parameters to optimize propulsion system operations. This implies the development of sensors, actuators, and electronics, with associated packaging, that will be able to operate under the harsh environments present in an engine. However, given the harsh environments inherent in propulsion systems, the development of engine-compatible electronics and sensors is not straightforward. The ability of a sensor system to operate in a given environment often depends as much on the technologies supporting the sensor element as the element itself. If the supporting technology cannot handle the application, then no matter how good the sensor is itself, the sensor system will fail. An example is high temperature environments where supporting technologies are often not capable of operation in engine conditions. Further, for every sensor going into an engine environment, i.e., for every new piece of hardware that improves the in-situ intelligence of the components, communication wires almost always must follow. The communication wires may be within or between parts, or from the engine to the controller. As more hardware is added, more wires, weight, complexity, and potential for unreliability is also introduced. Thus, wireless communication combined with in-situ processing of data would significantly improve the ability to include sensors into high temperature systems and thus lead toward more intelligent engine systems. NASA Glenn Research Center (GRC) is presently leading the development of electronics, communication systems, and sensors capable of prolonged stable operation in harsh 500C environments. This has included world record operation of SiC-based transistor technology (including packaging) that has demonstrated continuous electrical operation at 500C for over 2000 hours. Based on SiC electronics, development of high temperature wireless communication has been on-going. This work has concentrated on maturing the SiC electronic devices for communication purposes as well as the passive components such as resistors and capacitors needed to enable a high temperature wireless system. The objective is to eliminate wires associated with high temperature sensors which add weight to a vehicle and can be a cause of sensor unreliability. This paper discusses the development of SiC based electronics and wireless communications technology for harsh environment applications such as propulsion health management systems and in Venus missions. A brief overview of the future directions in sensor technology is given including maturing of near-room temperature "Lick and Stick" leak sensor technology for possible implementation in the Crew Launch Vehicle program. Then an overview of high temperature electronics and the development of high temperature communication systems is presented. The maturity of related technologies such as sensor and packaging will also be discussed. It is concluded that a significant component of efforts to improve the intelligence of harsh environment operating systems is the development and implementation of high temperature wireless technology

Hunter, G. W.↗

Validation of Pronghorn for Natural-Circulation Molten Salt Loops

This paper presents the development and validation of a high-fidelity thermal-hydraulic model of a molten salt natural circulation flow loop, designed for integration within a digital twin framework. The study evaluates the performance of Idaho National Laboratory’s Pronghorn against experimental data from Texas A&M University Molten Salt Flow Loop (MSFL) four Hitec-salt test benchmark data. Natural circulation of high-Prandtl-number fluids exhibits complex, counter-intuitive flow patterns that make pointwise thermocouple readings unreliable. Experimental work at TAMU’s MSFL provides benchmark data, including flow visualization at a test-section and centerline steady-state temperature measurements along the loop. Validation includes four single-phase natural circulation test cases with Hitec salt. Key metrics include flow profile agreement and steady-state temperature accuracy. Pronghorn results for two-dimensional single-phase agree qualitatively with the experimental flow profile. This paper illustrates the importance of Computational Fluid Dynamics (CFD) in elucidating the behavior of high-Prandtl-number thermal-hydraulics, along with how misleading centerline temperature measurements can be. Pronghorn reproduces the axial and radial stratification that makes single thermocouple readings unreliable. Future research will focus on reduced-order modeling techniques to enable rapid simulation suitable for real-time digital twin applications. The validated cases provide a basis for developing reduced-order surrogates aimed at real-time digital-twin applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Industry-Average Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants: 2020 Update

This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

99 GENERAL AND MISCELLANEOUS↗

Isoreticular Tolerance and Phase Selection in the Synthesis of Multi‐Module Metal–Organic Frameworks for Gas Separation and Electrocatalytic OER

Abstract Although metal–organic frameworks are coordination‐driven assemblies, the structural prediction and design using metal‐ligand interactions can be unreliable due to other competing interactions. Leveraging non‐coordination interactions to develop porous assemblies could enable new materials and applications. Here, we use a multi‐module MOF system to explore important and pervasive impact of ligand‐ligand interactions on metal‐ligand as well as ligand‐ligand co‐assembly process. It is found that ligand‐ligand interactions play critical roles on the scope or breakdown of isoreticular chemistry. With cooperative di‐ and tri‐topic ligands, a family of Ni‐MOFs has been synthesized in various structure types including partitioned MIL‐88‐acs ( pacs ), interrupted pacs (i‐ pacs ), and UMCM‐1‐muo. A new type of isoreticular chemistry on the muo platform is established between two drastically different chemical systems. The gas sorption and electrocatalytic studies were performed that reveal excellent performance such as high C 2 H 2 /CO 2 selectivity of 21.8 and high C 2 H 2 uptake capacity of 114.5 cm 3 /g at 298 K and 1 bar.

Xiao, Yuchen [Department of Chemistry University o↗

Isoreticular Tolerance and Phase Selection in the Synthesis of Multi‐Module Metal–Organic Frameworks for Gas Separation and Electrocatalytic OER

Abstract Although metal–organic frameworks are coordination‐driven assemblies, the structural prediction and design using metal‐ligand interactions can be unreliable due to other competing interactions. Leveraging non‐coordination interactions to develop porous assemblies could enable new materials and applications. Here, we use a multi‐module MOF system to explore important and pervasive impact of ligand‐ligand interactions on metal‐ligand as well as ligand‐ligand co‐assembly process. It is found that ligand‐ligand interactions play critical roles on the scope or breakdown of isoreticular chemistry. With cooperative di‐ and tri‐topic ligands, a family of Ni‐MOFs has been synthesized in various structure types including partitioned MIL‐88‐acs ( pacs ), interrupted pacs (i‐ pacs ), and UMCM‐1‐muo. A new type of isoreticular chemistry on the muo platform is established between two drastically different chemical systems. The gas sorption and electrocatalytic studies were performed that reveal excellent performance such as high C 2 H 2 /CO 2 selectivity of 21.8 and high C 2 H 2 uptake capacity of 114.5 cm 3 /g at 298 K and 1 bar.

Xiao, Yuchen [Department of Chemistry University o↗

Toward real-time optimization through model reduction and model discrepancy sensitivities

Optimization problems arise in a range of scenarios, from optimal control to model parameter estimation. In many applications, such as the development of digital twins, it is essential to solve these optimization problems within wall-clock-time limitations. However, this is often unattainable for complex systems, such as those modeled by nonlinear partial differential equations. One strategy for mitigating this issue is to construct a reduced-order model (ROM) that enables more rapid optimization. In particular, the use of nonintrusive ROMs—those that do not require access to the full-order model at evaluation time—is popular because they facilitate the computation of optimization solutions within the wall-clock time requirements. However, the optimization solution will be unreliable if the iterates move outside the ROM training data. This article proposes the use of hyper-differential sensitivity analysis with respect to model discrepancy (HDSA-MD) as a computationally efficient tool to augment ROM-constrained optimization and improve its reliability. The proposed approach consists of two phases: (i) an offline phase where several full-order model evaluations are computed to train the ROM, and (ii) an online phase where a ROM-constrained optimization problem is solved, a limited number of full-order model evaluations are computed, and HDSA-MD is used to enhance the optimization solution. Numerical results are demonstrated for two examples, atmospheric contaminant control and wildfire ignition location estimation, in which a ROM is trained offline using inaccurate atmospheric data. In conclusion, the HDSA-MD update yields a significant improvement in the ROM-constrained optimization solution using only one full-order model evaluation online with corrected atmospheric data.

PDE-constrained optimization↗

Methodology to determine printability criteria of highly concentrated pastes through rheological characterization

Material extrusion is an additive manufacturing technique that enables the creation of reproducible and complex hardware by depositing a viscous, shear-thinning ink onto a substrate in a custom-pattern via extrusion through a syringe. Here, the ability of an ink to be extruded onto a substrate in many layers, and maintain the desired shape is what defines the printability. Printability is often investigated by formulating, printing, and postmortem analysis of final parts in an iterative manner. Investigations of printability through rheological characterization have often been concerned with inks that straddle the line between printable and too thin, leaving out an entire class of inks that are highly-filled pastes, where extrudability is the limiting factor. Highly-filled pastes continue to pose issues for researchers as the effect of filler morphology, size, loading, and packing fraction on the ink rheology and corresponding printability is not understood. While traditional rheological characterizations may be useful for some inks, we show that protocols utilizing steady-shear, or large-amplitude oscillatory shear are difficult and unreliable for highly-filled pastes. Through transient rheology paired with real-time images we show that each traditional protocol produces inhomogeneous deformations that violate the assumptions that underly common rheological definitions. Instead, we demonstrate metrics measured with small-amplitude oscillatory shear that are correlated to the printability of various ink formulations ranging in loading. The rheological measures that accurately predict the printability of the inks are the axial stress measured at small amplitudes, and the critical stress amplitude above which rheological characterizations become impossible. In addition, we estimate the maximum packing fraction for each filler, based on the exponent common to hard sphere models, and show that the printability of each ink can be predicted by the ratio of the packing fraction to the theoretical maximum. We show how small-amplitude oscillatory shear allows users to develop printability criteria for any ink to enhance the workflow in the development of new inks, increase the performance of material extrusion printing, and improve the stability of printed parts, with less wasted time and materials.

36 MATERIALS SCIENCE↗