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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 487 records · Page 27

Safe Reinforcement Learning for Emergency Load Shedding of Power Systems

The paradigm shift in the electric power grid necessitates a revisit of existing control methods to ensure the grid’s security and resilience. In particular, the increased uncertainties and rapidly changing operational conditions in power systems have revealed outstanding issues in terms of either speed, adaptiveness, or scalability of the existing control methods for power systems. On the other hand, the availability of massive real-time data can provide a clearer picture of what is happening in the grid. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach leveraging massive data for fast and adaptive grid control. However, like most existing machine learning (ML)- based control techniques, RL control usually cannot guarantee the safety of the power systems. In this paper, we introduce a novel method for safe RL-based load shedding of power systems that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Numerical simulation on the IEEE 39-bus testcase is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.

reinforcement learning, emergency control, power g↗

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Paying it Forward: How an Emerging Unconventional Play can Hit the Ground Running

While every tight oil play is unique, there are lessons that can be transferred from one play to another to improve the efficiency and pace of production operations and development. These improvements may not fit precisely in every basin or play but generally hold to themes that can be tested against and built upon. Themes such as the quantity of proppant, longer lateral length, or the number of stages can be directly tied to increased productivity. However, there are diminishing returns on these investment activities for which each operator, within a given play, will be required to identify and mitigate against. This is especially true as the industry steps in and begins developing new tight oil plays. In their nascent stages, these plays may have limited well penetrations and, as a result, limited geological and performance data from which to extrapolate. Pulling together an understanding of where the industry currently resides in terms of how to exploit these resources can provide a boost in terms of working towards greatly improved well completions. In 2019, the US EIA estimated that nearly 8 million barrels of oil per day were produced from tight oil reservoirs in the United States (US EIA, 2020). This represents over 60% of the domestic crude production, originating from multiple reservoirs in the Permian Basin (TX) as well as the Bakken (MT, ND), Eagle Ford (TX), Niobrara (CO, WY), and Anadarko Basin (OK) formations, among others. As such, there are 1,000s of wells across these numerous tight oil plays that can relate an informative story. To build this story, the interplay of geology, well spacing, lateral length, and stimulation, all critical to economic success, will be explored. This paper proposes to look back at these mature tight oil (and gas) basins and bring forth an understanding of what lessons can be applied to the emerging Powder River Basin tight oil reservoirs (Mowry and the Turner/Frontier). The authors will delve into the four broad topics of geology, well spacing, lateral length, and stimulation, highlighting case studies to demonstrate those lessons from established tight oil plays that will underpin planned activities at a Field Laboratory Test Site in the southern Powder River Basin.

02 PETROLEUM↗

System Study: Emergency Power System 1998–2018

This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from 1998 through 2018 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the EPS results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

1st Quarter Emergency Drill at SERF: Player's Briefing [Slides]

The purpose of this briefing is to provide drill information to players participating in the 1st Quarter Emergency Drill at SERF as follows: Communicate general drill information and conduct expectations; Outline roles and responsibilities; and Provide safely and securely guidance to ensure unsafe act or security violation does not occur during the drill.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

System Study: Emergency Power System 1998-2020

This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from 1998 through 2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in the industry-wide estimates of EPS system start-only mission as well as EPS system unreliability (8-hour mission).

99 GENERAL AND MISCELLANEOUS↗

Evaluation of the Radioactive Material Release in the Harborview Research and Training Building and Implications for Emergency Response

The objectives of this project were to assess the accidental release of 137 CsCl at the University of Washington Harborview Research and Training (HRT) Building for its implications related to emergency response methods. Ramifications of behavior and transport of 137 CsCl dispersal within the building were evaluated, as well the phenomenology of this event compared to past alkali halide dispersal events.

99 GENERAL AND MISCELLANEOUS↗

System Study: Emergency Power System 1998-2022

This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a highly statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 8-hour mission unreliability.

99 GENERAL AND MISCELLANEOUS↗

Improving Production in the Emerging Paradox Oil Play (Final Technical Report)

This report documents the results of the DOE-funded project Improving Production in the Emerging Paradox Oil Play, focused on integrating geological characterization, petrophysical analysis, reservoir simulation, and field development planning to improve hydrocarbon recovery from the Paradox Basin. Project activities included core and log analysis, assessment of reservoir heterogeneity and compartmentalization, evaluation of completion and stimulation strategies, and development of an uncertainty-aware field development framework. Findings highlight the importance of selective completions, geology-driven well placement, and targeted stimulation in vertically heterogeneous carbonate reservoirs.

02 PETROLEUM↗

System Study: Emergency Power System 1998-2024

This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 24-hour mission unreliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Discovering novel therapeutic V H Hs for emerging viruses: perspectives from VEEV selection strategies

Introduction: Evolution or emergence of a new viral variant is a significant public health concern. Alphaviruses, such as Venezuelan equine encephalitis virus (VEEV), are mosquito-borne viruses which are becoming more prevalent due to expansion of vector habitats. Despite this, there are currently no antiviral therapies or FDA-approved vaccines available to treat or prevent VEEV infection. The increased prevalence of such viruses provides opportunities for novel variants to evolve. Key therapeutic molecules that could be developed against viral pathogens are recombinant antibodies or antibody fragments, such as the variable heavy domain of heavy chain antibodies (V H Hs). Methods: In vitro selections offer a promising pathway for identification of therapeutic antibodies, here we explored isolation of V H Hs using phage and yeast display methodology with three antigen formats 1) recombinant E2, 2) linear peptides of E2, selected based on molecular dynamics analysis, and 3) UV inactivated virus. Results: Here we report four novel “human” V H Hs which bind to the VEEV E2 protein selected using different strategies that include both computational and biochemical design of suitable antigens and whole virus selections. These V H Hs have distinct complementarity-determining regions (CDRs). Multiple VHHs bind to the VEEV viral particles in ELISAs, and we report the peptide epitope recognized by these V H Hs. Discussion: Though non-neutralizing, these V H Hs bind to and sequester VEEV viral particles preventing infection, demonstrating the potential of these V H Hs to perform viral “sponging” which represents a novel therapeutic approach. The selection strategies we report may have applications to further antibody developments against other viruses.

59 BASIC BIOLOGICAL SCIENCES↗

A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics

A general agreement in psycholinguistics claims that syntax and meaning are unified precisely and very quickly during online sentence processing. Although several theories have advanced arguments regarding the neurocomputational bases of this phenomenon, we argue that these theories could potentially benefit by including neurophysiological data concerning cortical dynamics constraints in brain tissue. In addition, some theories promote the integration of complex optimization methods in neural tissue. In this paper we attempt to fill these gaps introducing a computational model inspired in the dynamics of cortical tissue. In our modeling approach, proximal afferent dendrites produce stochastic cellular activations, while distal dendritic branches–on the other hand–contribute independently to somatic depolarization by means of dendritic spikes, and finally, prediction failures produce massive firing events preventing formation of sparse distributed representations. The model presented in this paper combines semantic and coarse-grained syntactic constraints for each word in a sentence context until grammatically related word function discrimination emerges spontaneously by the sole correlation of lexical information from different sources without applying complex optimization methods. By means of support vector machine techniques, we show that the sparse activation features returned by our approach are well suited—bootstrapping from the features returned by Word Embedding mechanisms—to accomplish grammatical function classification of individual words in a sentence. In this way we develop a biologically guided computational explanation for linguistically relevant unification processes in cortex which connects psycholinguistics to neurobiological accounts of language. We also claim that the computational hypotheses established in this research could foster future work on biologically-inspired learning algorithms for natural language processing applications.

59 BASIC BIOLOGICAL SCIENCES↗

Electroexcitation of Nucleon Resonances and Emergence of Hadron Mass

Developing an understanding of phenomena driven by the emergence of hadron mass (EHM) is one of the most challenging problems in the Standard Model. This discussion focuses on the impact of results on nucleon resonance (𝑁 ∗ ) electroexcitation amplitudes (or 𝛾 𝑣 𝑝𝑁 ∗ electrocouplings) obtained from experiments during the 6 GeV era in Hall B at Jefferson Lab on understanding EHM. Analyzed using continuum Schwinger function methods (CSMs), these results have revealed new pathways for the elucidation of EHM. A good description of the Δ(1232)3/2 + , 𝑁(1440)1/2 + , and Δ(1600)3/2 + electrocouplings, achieved by CSM analyses that express a realistic dressed quark mass function, sheds light on the strong interaction dynamics underlying EHM. Extensions to 𝑁 ∗ studies for higher-mass states are outlined, as well as experimental results anticipated in the 12 GeV era at Jefferson Lab and those that would be enabled by a further increase in the beam energy to 22 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Human factors and safety in emergency medicine

A model based on an input process and outcome conceptualisation is suggested to address safety-relevant factors in emergency medicine. As shown in other dynamic and demanding environments, human factors play a decisive role in attaining high quality service. Attitudes held by health-care providers, organisational shells and work-cultural parameters determine communication, conflict resolution and workload distribution within and between teams. These factors should be taken into account to improve outcomes such as operational integrity, job satisfaction and morale.

Non-NASA Center↗

Design and Demonstration of Emergency Control Modes for Enhanced Engine Performance

A design concept is presented for developing control modes that enhance aircraft engine performance during emergency flight scenarios. The benefits of increased engine performance to overall vehicle survivability during these situations may outweigh the accompanied elevated risk of engine failure. The objective involves building control logic that can consistently increase engine performance beyond designed maximum levels based on an allowable heightened probability of failure. This concept is applied to two previously developed control modes: an overthrust mode that increases maximum engine thrust output and a faster response mode that improves thrust response to dynamic throttle commands. This paper describes the redesign of these control modes and presents simulation results demonstrating both enhanced engine performance and robust maintenance of the desired elevated risk level.

aircraft engine simulation↗