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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ChatGPT and Other Large Language Models for Cybersecurity of Smart Grid Applications

Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract a dataset of IEC 61850 communications.

ChatGPT↗
DOE OSTI2023

Reliable Devices Yield Stable Quantum Computations

Stable quantum computation requires noisy results to remain bounded even in the presence of noise fluctuations. Yet non-stationary noise processes lead to drift in the varying characteristics of a quantum device that can greatly influence the circuit outcomes. Here we address how temporal and spatial variations in noise relate device reliability to quantum computing stability. First, our approach quantifies the differences in statistical distributions of characterization metrics collected at different times and locations using Hellinger distance. We then validate an analytical bound that relates this distance directly to the stability of a computed expectation value. Our demonstration uses numerical simulations with models informed by the washington superconducting transmon device. We find that the stability metric is consistently bounded from above by the corresponding Hellinger distance, which can be cast as a specified tolerance level. These results underscore the significance of reliable quantum computing devices and the impact for stable quantum computation.

Dasgupta, Samudra↗
DOE OSTI2026

OpenSAMPL: An Open Source Library for Timing and Synchronization Measurements and Analytics

Today's power grid operators are implementing timing and synchronization solutions that provide resilience to Global Navigation Satellite System (GNSS) vulnerabilities. These vendor-specific solutions often come with additional software applications that are designed to monitor that vendor's synchronization performance data. However, resilient timing architectures often resulting in multi-vendor solutions, including approaches that blend terrestrial clocks with space-based subscription services. In such an environment, collecting, analyzing, and visualizing data from a variety of sources within a single platform was heretofore not possible. To address this need, the US Department of Energy's Center for Alternative Synchronization and Timing (CAST) developed OpenSAMPL, the Open Synchronized Analytics and Monitoring Platform, an open-source Python framework for processing, loading, and observing clock measurement data from distributed devices. OpenSAMPL enables the ingestion of diverse clock-probe sources into a scalable time-series database and applies robust analytics. OpenSAMPL currently supports two vendor data pipelines, and will be extended to more in the near future, enabling seamless monitoring of a variety of timing and synchronization devices in a common environment.

Grant, Josh [ORNL] (ORCID:0000000163475060)↗
DOE OSTI2021

Multilane Automated Driving With Optimal Control and Mixed-Integer Programming

Road vehicle lane changes often initiate traffic disturbances and can therefore impact road networks’ energy and time efficiency. Furthermore, unexpected changes in traffic conditions may also render lane changes counterproductive for the lane-changing vehicle. Vehicle-to-vehicle connectivity combined with anticipative control could address these challenges via improved lane change decisions by automated vehicles. In a move toward this objective, receding horizon control cast as a mixed-integer quadratic program is used to plan lane changing and acceleration in a coupled optimization. A long-term pacing module, based on Pontryagin’s minimum principle from optimal control theory, sets terminal and input references for receding horizon control to target a user’s expected travel time. To remove nonlinear vehicle dynamics from the receding horizon controller, lane change commands are passed to a pure pursuit steering module whose response is approximated by a second-order linear model. Here, comparison against a rule-based reactive algorithm in arterial and highway scenarios shows an 8.9%–13.7% reduction in energy consumption and a 5.2%–10.3% reduction in the travel time, along with navigational improvements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Robust Deep Gaussian Process-Based Probabilistic Electrical Load Forecasting Against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This article proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining the excellent performance of capturing the forecasting uncertainties.

anomalous events↗
DOE OSTI2025

Distributed Sapphire Fiber Bragg Gratings Based Thermal Profiling of Submerged Entry Nozzles

This research focuses on the application of sapphire fiber Bragg gratings (FBGs) for instrumentation in submerged entry nozzles (SEN) within the steelmaking industry. The SEN is pivotal for transferring molten steel from a tundish to a mold, while preventing the infiltration of oxygen and nitrogen from the surrounding environment. Maintaining optimal flow conditions in the mold is crucial for ensuring casting process stability and maintaining high quality steel. Sapphire FBG sensors have been instrumented in SENs to enable distributed thermal mapping for monitoring the health of the SEN. The optical sensor comprises three cascaded sapphire FBGs inscribed using femtosecond laser technology into a one-meter-long sapphire crystalline fiber. The sensor underwent characterization in a laboratory setting up to 1600°C and was tested for long-term stability over 40 hours under extreme environmental conditions. The coupling between silica and sapphire fibers was investigated and implemented during sensor packaging. Here, the sensor successfully captured the pre-heat sequence of the SEN in real-world steelmaking operations. Compared to conventional thermocouples, sapphire FBG sensors demonstrated exceptional efficiency and precision. They offer potential benefits such as increased productivity, reduced energy consumption, and minimized carbon footprint in the steel industry.

Sapphire Fiber Bragg Grating↗
DOE OSTI2020

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↗
DOE OSTI2021

Microstructure and Hard Magnetic Properties of Sm 1-x Zr x (Fe,Co) 11.3-y Ti 0.7 By Ingots and Thick Melt-Spun Ribbons

Permanent magnets made from Sm(Fe,Co) 12 -based compounds are being actively pursued through nanostructuring and powder metallurgy. This study was aimed at the development of hard magnetic properties in bulk as-cast alloys and in melt-spun alloys for very low wheel speeds. Slower solidification rates and alloying with Zr promote the tetragonal ThMn 12 -type crystal structure, whereas higher solidification rates and alloying with B replace the ThMn 12 structure type with the TbCu 7 structure type. When introduced simultaneously, Zr and B dramatically reduce the alloy solidification rates required for both the refinement of the 1:12 crystallites and their replacement with the 1:7 phase. In bulk arc-melted alloys, this allowed for a microstructure of separated 1:12 crystallites 1–3 μm in size, although, because of the ferromagnetic nature of a minority phase, the coercivity of these fine-grained alloys reached only 0.73 kOe. A moderately accelerated solidification further refined the 1:12 crystallites and increased the coercivity; a Sm 0.7 Zr 0.4 (Fe,Co) 10.8 Ti 0.7 B 0.5 alloy exhibited a coercivity of 1.5 kOe and a maximum energy product of 3.4 MGOe when it was melt-spun into a 0.26-mm-thick ribbon. A more rapid solidification suppressed the 1:12 phase and after annealing at 800–850 °C, the alloys modified with Zr and B developed reasonably high coercivity and maximum energy product even when melt-spun at a wheel speed of 6 m/s. For the above-mentioned alloy, these values were 4.1 kOe and 7.8 MGOe, respectively. Further, a similarly processed very-Sm-lean Sm 0.5 Zr 0.6 (Fe,Co) 10.6 Ti 0.7 B 0.7 alloy exhibited a remanence of 8.8 kG and an energy product of 7.4 MGOe.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improved Gamma-Ray Point Source Quantification in Three Dimensions by Modeling Attenuation in the Scene

We discuss using a series of detector measurements taken at different locations to localize a source of radiation as a well-studied problem. The source of radiation is sometimes constrained to a single point-like source, in which case the location of the point source can be found using techniques such as maximum likelihood. Recent advancements have shown the ability to locate point sources in 2D and even 3D, but few have studied the effect of intervening material on the problem. In this work we examine gamma-ray data taken from a freely moving system and develop voxelized 3-D models of the scene using data from the onboard LiDAR. Ray casting is used to compute the distance each gamma ray travels through the scene material, which is then used to calculate attenuation assuming a single attenuation coefficient for solids within the geometry. Parameter estimation using maximum likelihood is performed to simultaneously find the attenuation coefficient, source activity, and source position that best match the data. Using a simulation, we validate the ability of this method to reconstruct the true location and activity of a source, along with the true attenuation coefficient of the structure it is inside, and then we apply the method to measured data with sources and find good agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Secured Reserve Scheduling of Pumped-Storage Hydropower Plants in ISO Day-ahead Market

Due to the fast response ability and high ramping rates, pumped-storage hydropower (PSH) plants are playing an increasingly critical role in mitigating power generation fluctuations induced by the growing proliferation of renewable energy resources. However, because they are energy-limited resources, actual reserve deployment from PSHs would cause the deviation of state-of-charge (SOC) from the scheduled value, which, once accumulated over time, could induce potential violations on SOC limits and cause non-dispatchability of PSHs. In recognizing this potential issue, it can become important to securing the reserve schedule of PSHs and other energy limited resources preventively in the day-ahead market clearing. To ensure reserve dispatchability of PSHs despite SOC deviations, this paper proposes the reserve secure constraints, which are cast as a distributionally robust chance-constrained formulation by judiciously introducing random parameters to describe deployment ratios of scheduled regulation reserve from PSHs. Furthermore, these constraints are converted into tractable second-order cone constraints, and further approximated as linear constraints to be compatible with the current ISO day-ahead market clearing model. A modified IEEE 118-bus system with multiple PSHs is adopted to verify the proposed approach.

13 HYDRO ENERGY↗
DOE OSTI2020

Bus Clustering for Distribution Grid Topology Identification

Recovering the distribution grid topology is essential to perform several distribution system operator functions. Many algorithms that address the topology recovery problem have already been proposed in the literature. Most are based on a priori information regarding which buses are fed by which substation; however, this information might not be available because frequent grid reconfigurations change the distribution grid portion connected to each substation. This paper addresses the problem of assigning every substation the set of buses that it is feeding, given field data. First, the aforementioned task is cast as a nonconvex optimization problem. Second, a relaxed version of the optimization problem is solved via the alternating direction method of multipliers. Finally, the performance of our approach is validated through numerical simulations of realistic scenarios using a standard IEEE benchmark feeder.

bus clustering↗
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Ant handling changes myrmecochore seed coat microbiomes and alters diversity of seed-borne plant pathogenic fungi

1. The putative benefits to seeds in myrmecochory (ant- mediated seed dispersal) are often cast in a reward context. However, microbes have been mostly overlooked as seed mortality agents in myrmecochory, as have potential treatments provided by ant-handling. 2. We investigated the effects of ant handling on the diversity of seed coat fungal communities of three myrmecochorous plant species. 3. Ant-handling altered measures of both alpha and beta diversity of fungal communities. Ant-handled seeds harboured different overall fungal communities and plant pathogen communities than non-ant-handled seeds. The myrmecochore pathogenic fungal community showed high dissimilarity (high pairwise community turnover) between ant-handled and control seeds, while beta diversity measures for ant- handled seeds and seeds with manually removed elaiosomes were less dissimilar. 4. Ant handling may offer an additional benefit to myrmecochorous seeds via the reduction in the seed coat pathogenic community, which may be driven by elaiosome removal or as a by-product of ant cleaning behaviours and chemical secretions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Organic preservation of vase‐shaped microfossils from the late Tonian Chuar Group, Grand Canyon, Arizona, USA

Abstract Vase‐shaped microfossils (VSMs) are found globally in middle Neoproterozoic (800–730 Ma) marine strata and represent the earliest evidence for testate (shell‐forming) amoebozoans. VSM tests are hypothesized to have been originally organic in life but are most commonly preserved as secondary mineralized casts and molds. A few reports, however, suggest possible organic preservation. Here, we test the hypothesis that VSMs from shales of the lower Walcott Member of the Chuar Group, Grand Canyon, Arizona, contain original organic material, as reported by B. Bloeser in her pioneering studies of Chuar VSMs. We identified VSMs from two thin section samples of Walcott Member black shales in transmitted light microscopy and used scanning electron microscopy to image VSMs. Carbonaceous material is found within the internal cavity of all VSM tests from both samples and is interpreted as bitumen mobilized from Walcott shales likely during the Cretaceous. Energy dispersive X‐ray spectroscopy (EDS) and wavelength dispersive X‐ray spectroscopy (WDS) reveal that VSM test walls contain mostly carbon, iron, and sulfur, while silica is present only in the surrounding matrix. Raman spectroscopy was used to compare the thermal maturity of carbonaceous material within the samples and indicated the presence of pyrite and jarosite within fossil material. X‐ray absorption spectroscopy revealed the presence of reduced organic sulfur species within the carbonaceous test walls, the carbonaceous material found within test cavities, and in the sedimentary matrix, suggesting that organic matter sulfurization occurred within the Walcott shales. Our suite of spectroscopic analyses reveals that Walcott VSM test walls are organic and sometimes secondarily pyritized (with the pyrite variably oxidized to jarosite). Both preservation modes can occur at a millimeter spatial scale within sample material, and at times even within a single specimen. We propose that sulfurization within the Walcott Shales promoted organic preservation, and furthermore, the ratio of iron to labile VSM organic material controlled the extent of pyrite replacement. Based on our evidence, we conclude that the VSMs are preserved with original organic test material, and speculate that organic VSMs may often go unrecognized, given their light‐colored, translucent appearance in transmitted light.

58 GEOSCIENCES↗
DOE OSTI2023

The evolution of grain boundary energy in textured and untextured Ca–doped alumina during grain growth

The role of anisotropic grain boundary energy in grain growth is investigated using textured microstructures that contain a high proportion of special grain boundaries. Textured and untextured Ca–doped alumina was prepared by slip casting inside and outside a high magnetic field, respectively. At 1600°C, the textured microstructure exhibits faster growth than the untextured microstructure and its population of low–angle boundaries increases. Atomic force microscopy (AFM) is employed to measure the geometry of thermal grooves to assess the relative grain boundary energy of these systems before and after growth. In the textured microstructure, the grain boundary energy distribution narrows and shifts to a lower average energy. Conversely, the energy distribution broadens for the untextured microstructure as it grows and exhibits abnormal grain growth. Further analysis of the boundary networks neighboring abnormal grains reveals an energy incentive that facilitates their growth. These results suggest that coarsening is not the only dominant grain growth mechanism and that the system can lower its energy effectively by replacing high energy boundaries with those of low energy. The faster growth of lower energy boundaries suggests that isotropic simulations do not adequately account for anisotropic grain growth mechanisms or anisotropic mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Melting point of group IV and V transition metal diborides

The environmental conical nozzle levitator system enables cooling trace experiments above 4000 K. These cooling trace experiments were used to determine the melting points through observation of thermal arrest of group IV and V transition metal diborides (TiB 2 , T m = 3313 ± 33 K; ZrB 2 , T m = 3404 ± 38 K; HfB 2 , T m = 3529 ± 33 K; and TaB 2 , T m = 3284 ± 10 K; note: mean ± 2 standard error). Temperature measurements were conducted utilizing dual single-color pyrometers at wavelengths of 0.9 and 0.65 µm. This system utilizes aerodynamic levitation and dual laser heating to achieve temperatures approaching 4000 K. The samples were synthesized from commercial powders using ceramic gel-casting to produce high-density spherical components. The measurements obtained were compared to previously reported melting temperature values and were generally found to be in agreement with most of the published values.

Materials science↗
DOE OSTI2023

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Mechanism-Based Energy Regularization in Computational Modeling of Quasibrittle Fracture

Abstract Quasibrittle materials are featured by a strain-softening constitutive behavior under many loading scenarios, which could eventually lead to localization instability. It has long been known that strain localization would result in spurious mesh sensitivity in finite element (FE) simulations. Previous studies have shown that, for the case of fully localized damage, the mesh sensitivity can be mitigated through energy regularization of the material constitutive law. However, depending on the loading configuration and structural geometry, quasibrittle structures could exhibit a complex damage process, which involves both localized and diffused damage patterns at different stages of loading. This study presents a generalized energy regularization method that considers the spatial and temporal evolution of damage pattern. The method introduces a localization parameter, which describes the local damage pattern. The localization parameter governs the energy regularization of the constitutive model, which captures the transition from diffused to localized damage during the failure process. The method is cast into an isotropic damage model, and is further extended to rate-dependent behavior. The energy regularization scheme is directly incorporated into the kinetics of damage growth. The model is applied to simulate static and dynamic failures of ceramic specimens. It is shown that the present model is able to effectively mitigate the spurious mesh sensitivity in FE simulations of both types of failure. The present analysis demonstrates the essential role of mechanism-based energy regularization of constitutive relation in FE simulations of quasibrittle fracture.

Mechanics↗