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At least 361 records · Page 20

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

Simulations of carbon dioxide (CO 2 ) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO 2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. Here, we show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics and Clearance Analysis of NASA's Space Launch System Block-1 and Block 1B Solid Rocket Booster Separation Event

NASA’s Space Launch System (SLS) solid rocket booster separation event is an essential area of study requiring high fidelity modelling to capture the complexity of an intra-atmospheric stage separation event. The setup and analysis for this event leveraged the NASA-developed CLVTOPS multi-body dynamics toolchain to model aerodynamics at the separation event, booster thrust tailoff, and Core Stage engine throttling in addition to the separation system itself (booster separation motors (BSMs), pyrotechnic bolts and struts). The approach documented here will give a brief background on the CLVTOPS toolchain, how key input models are integrated and verified, and how results are quantified using an ordered-statistics approach. Specific areas discussed herein address the performance-to-orbit realized by adjusting the delay time between the separation cue and the actual separation event, and how the orientation of the aft BSMs was tuned to address small clearances between the aft diagonal attach struts and the Core Stage. Post-flight results from the inaugural Artemis I flight are also shown, and validation is performed between predicted vs. actual separation dynamics and clearances. Challenging night launch conditions necessitated comparisons that were more qualitative in nature, but still showed very good agreement to pre-flight predictions.

Carole J Addona↗

The Role of Seasonality and the ENSO Mode in Central and East Pacific ENSO Growth and Evolution

Abstract A cyclostationary linear inverse model (CSLIM) is used to investigate the seasonal growth of tropical Pacific Ocean El Niño–Southern Oscillation (ENSO) events with canonical, central Pacific (CP), or eastern Pacific (EP) sea surface temperature (SST) characteristics. Analysis shows that all types of ENSO events experience maximum growth toward final states occurring in November and December. ENSO events with EP characteristics also experience growth into May and June, but CP events do not. A single dominant “ENSO mode,” growing from an equatorial heat content anomaly into a characteristic ENSO-type SST pattern in about 9 months (consistent with the delayed/recharge oscillator model of ENSO), is essential for the predictable development of all ENSO events. Notably, its seasonality is responsible for the late-calendar-year maximum in ENSO amplification. However, this ENSO mode alone does not capture the observed growth and evolution of diverse ENSO events, which additionally involve the seasonal evolution of other nonorthogonal Floquet modes. EP event growth occurs when the ENSO mode is initially “covered up” in combination with other Floquet modes. The ENSO mode’s slow seasonal evolution allows it to emerge while the other modes rapidly evolve and/or decay, leading to strongly amplifying and more predictable EP events. CP events develop when the initial state has a substantial contribution from Floquet modes with meridional mode–like SST structures. Thus, while nearly all ENSO events involve the seasonally varying ENSO-mode dynamics, the diversity and predictability of ENSO events cannot be understood without identifying contributions from the remaining Floquet modes. Significance Statement The purpose of this study is to identify structures that lead to seasonal growth of diverse types of El Niño–Southern Oscillation (ENSO) events. An important contribution from this study is that it uses an observationally constrained, empirically derived seasonal model. We find that processes affecting the evolution of diverse ENSO events are strongly seasonally dependent. ENSO events with eastern equatorial Pacific sea surface temperature (SST) characteristics are closely related to a single “ENSO mode” that resembles theoretical models of ENSO variability. ENSO events that have central equatorial Pacific SST characteristics include contributions from additional “meridional mode” structures that evolve via different physical processes. These findings are an important step in evaluating the seasonal predictability of ENSO diversity.

Vimont, Daniel J.↗

Patterns of seismic activity preceding large earthquakes

A mechanical model of seismic faults is employed to investigate the seismic activities that occur prior to major events. The block-and-spring model dynamically generates a statistical distribution of smaller slipping events that precede large events, and the results satisfy the Gutenberg-Richter law. The scaling behavior during a loading cycle suggests small but systematic variations in space and time with maximum activity acceleration near the future epicenter. Activity patterns inferred from data on seismicity in California demonstrate a regional aspect; increased activity in certain areas are found to precede major earthquake events. One example is given regarding the Loma Prieta earthquake of 1989 which is located near a fault section associated with increased activity levels.

Shaw, Bruce E.↗

An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool

Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). This study proposes the PRocedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA) method, which is an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). In this study, how to model human actions using the software and evaluate the error probabilities is suggested. The applicability of this approach will be also investigated through an extended loss of AC power (ELAP) scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.

99 GENERAL AND MISCELLANEOUS↗

Radiative Reconnection-powered TeV Flares from the Black Hole Magnetosphere in M87

Abstract Active galactic nuclei in general, and the supermassive black hole in M87 in particular, show bright and rapid gamma-ray flares up to energies of 100 GeV and above. For M87, the flares show multiwavelength components, and the variability timescale is comparable to the dynamical time of the event horizon, suggesting that the emission may come from a compact region near the nucleus. However, the emission mechanism for these flares is not well understood. Recent high-resolution general-relativistic magnetohydrodynamic simulations show the occurrence of episodic magnetic reconnection events that can power flares near the black hole event horizon. In this work, we analyze the radiative properties of the reconnecting current layer under the extreme plasma conditions applicable to the black hole in M87 from first principles. We show that abundant pair production is expected in the vicinity of the reconnection layer, to the extent that the produced secondary pair plasma dominates the reconnection dynamics. Using analytic estimates backed by two-dimensional particle-in-cell simulations, we demonstrate that in the presence of strong synchrotron cooling, reconnection can produce a hard power-law distribution of pair plasma imprinted in the outgoing synchrotron (up to a few tens of MeV) and the inverse-Compton signal (up to TeV). We produce synthetic radiation spectra from our simulations, which can be directly compared with the results of future multiwavelength observations of M87* flares.

79 ASTRONOMY AND ASTROPHYSICS↗

Probing the Environment around GW170817 with DESI: Insights on Galaxy Group Peculiar Velocities for Standard Siren Measurements

We present a new measurement of the Hubble constant, H 0 , following the gravitational-wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance ∼40 Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy owing to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group’s properties and NGC 4993’s membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a fivefold increase in galaxies compared to previous observations, with many contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is a part with a halo mass of order ∼10 13 M ⊙ . Using peculiar velocity measurements from our fundamental plane galaxy observations, we find $H_0 = 70.9^{+6.4}_{-8.5}$ km s −1 Mpc −1 . In addition, using a peculiar velocity measurement for NGC 4993 from surface brightness fluctuations in Cosmicflows-4, we find $H_0 = 73.4^{+3.3}_{-3.9}$ km s −1 Mpc −1 . We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the H 0 measurement. Our results demonstrate the value of multiplexed spectroscopic observations for probing the local environments of gravitational-wave events used in standard siren measurements.

Amsellem, A. J. [Carnegie Mellon University, Pitts↗

Integrated Hardware and Software for No-Loss Computing

When an algorithm is distributed across multiple threads executing on many distinct processors, a loss of one of those threads or processors can potentially result in the total loss of all the incremental results up to that point. When implementation is massively hardware distributed, then the probability of a hardware failure during the course of a long execution is potentially high. Traditionally, this problem has been addressed by establishing checkpoints where the current state of some or part of the execution is saved. Then in the event of a failure, this state information can be used to recompute that point in the execution and resume the computation from that point. A serious problem arises when one distributes a problem across multiple threads and physical processors is that one increases the likelihood of the algorithm failing due to no fault of the scientist but as a result of hardware faults coupled with operating system problems. With good reason, scientists expect their computing tools to serve them and not the other way around. What is novel here is a unique combination of hardware and software that reformulates an application into monolithic structure that can be monitored in real-time and dynamically reconfigured in the event of a failure. This unique reformulation of hardware and software will provide advanced aeronautical technologies to meet the challenges of next-generation systems in aviation, for civilian and scientific purposes, in our atmosphere and in atmospheres of other worlds. In particular, with respect to NASA s manned flight to Mars, this technology addresses the critical requirements for improving safety and increasing reliability of manned spacecraft.

James, Mark↗

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

METHODOLOGY AND APPLICATION OF PHYSICAL SECURITY EFFECTIVENESS BASED ON DYNAMIC FORCE-ON-FORCE MODELING

This paper describes ongoing work within the Light Water Reactor Sustainability (LWRS) Program at Idaho National Laboratory (INL) to optimize security and cost of nuclear power plants (NPPs). It reviews the conservatisms in conventional physical security posture and regulations. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The dynamic assessment methodology leverages EMRALD to process results of force-on-force (FOF) simulations and crediting safety mitigation actions from probabilistic risk assessment (PRA) models as well as diverse and flexible coping strategies (FLEX) mitigation strategies. Timing information from these simulations are compared against the available time to perform mitigations obtained from Reactor Excursion and Leak Analysis Program (RELAP5) simulations. To illustrate the methodology, a station blackout (SBO) attack scenario was modeled in commercially available FOF simulation tools. The simulation results provide valuable insights into possible attack outcomes and as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures were modeled in EMRALD, and were dependent on the attack outcomes by considering human operator uncertainties. RELAP5 simulations incorporating human and hardware uncertainties were performed to estimate the distribution of time-to-core damage. The results demonstrate that, even in the extreme case of a successful adversarial attack, plant mitigation strategies provide significantly high-likelihood of preventing radiological release. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the NPPs to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Pan-Continental Droughts in North America over the Last Millennium

Regional droughts are common in North America, but pan-continental droughts extending across multiple regions, including the 2012 event, are rare relative to single-region events. Here, the tree-ring-derived North American Drought Atlas is used to investigate drought variability in four regions over the last millennium, focusing on pan-continental droughts. During the Medieval Climate Anomaly (MCA), the central plains (CP), Southwest (SW), and Southeast (SE) regions experienced drier conditions and increased occurrence of droughts and the Northwest (NW) experienced several extended pluvials. Enhanced MCA aridity in the SW and CP manifested as multidecadal megadroughts. Notably, megadroughts in these regions differed in their timing and persistence, suggesting that they represent regional events influenced by local dynamics rather than a unified, continental-scale phenomena. There is no trend in pan-continental drought occurrence, defined as synchronous droughts in three or more regions. SW, CP, and SE (SW+CP+SE) droughts are the most common, occurring in 12 percent of all years and peaking in prevalence during the twelfth and thirteenth centuries; patterns involving three other regions occur in about 8 percent of years. Positive values of the Southern Oscillation index (La Nina conditions) are linked to SW, CP, and SE (SW+CP+SE) droughts and SW, CP, and NW (SW+CP+NW) droughts, whereas CP, NW, and SE (CP+NW+SE) droughts are associated with positive values of the Pacific decadal oscillation and Atlantic multidecadal oscillation. While relatively rare, pan-continental droughts are present in the paleo record and are linked to defined modes of climate variability, implying the potential for seasonal predictability. Assuming stable drought teleconnections, these events will remain an important feature of future North American hydroclimate, possibly increasing in their severity in step with other expected hydroclimate responses to increased greenhouse gas forcing.

anomalies↗

Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures

Digital Instrumentation and Control (I&C) systems have a key role in nuclear power plants in the upgrade of aging analog systems. Digital systems improve plant safety and reliability through features such as increased hardware reliability and stability and improved failure detection capability. There is no consensus on which of the current probabilistic risk assessment methods are most suitable for use in the reliability analysis of digital I&C systems. While the traditional event-tree/fault-tree (ET/FT) approach is still used for their reliability modeling, there are concerns regarding this approach in properly accounting for dynamic interactions among system components since potentially significant dependencies among failure events may not be identified and/or their likelihood may not be properly quantified. Dynamic methodologies are expected to provide a much more accurate representation of probabilistic evolution of the I&C systems in time due to their capability to more properly account for complex interactions than the static approach. The applicability of dynamic PRA methodologies for digital I&C system is investigated using the criteria presented in the NUREG/CR-6901, and the comparisons made in NUREG/CR-6901 are updated in light of the latest studies. The Dynamic Event Tree (DET) approach has been identified as one of the top dynamic methods when evaluated against the requirements for the reliability modeling of digital I&C systems. The DET method is a strong candidate for integration into existing PRA studies, as it bears many similarities to the traditional ET approach. In this study, the DET approach has been applied to the Plant Protection System of the APR1400 design, and the results are compared to results from its available traditional ET/FT analysis. Possible approaches to evaluate and quantify the effects of common cause failures on system safety using dynamic methods are also examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using Dynamically Downscaled Climate Model Outputs to Inform Projections of Extreme Precipitation Events

Many of the storms that generate damaging floods are caused by locally intense, sub-daily precipitation, yet the spatial and temporal resolution of the most widely available climate model outputs are both too coarse to simulate these events. Thus there is often a disconnect between the nature of the events that cause damaging floods and the models used to project how climate change might influence their magnitude. This could be a particular problem when developing scenarios to inform future storm water management options under future climate scenarios. In this study we sought to close this gap, using sub-daily outputs from the Weather Research and Forecasting model (WRF) from each of the nine climate regions in the United States. Specifically, we asked 1) whether WRF outputs projected consistent patterns of change for sub-daily and daily precipitation extremes; and 2) whether this dynamically downscaled model projected different magnitudes of change for 3-hourly vs 24-hourly extreme events. We extracted annual maximum values for 3-hour through 24-hour precipitation totals from an 11-year time series of hindcast (1995-2005) and mid-century (2045-2055) climate, and calculated the direction and magnitude of change for 3-hour and 24-hour extreme events over this timeframe. The model results project that the magnitude of both 3-hour and 24-hour events will increase over most regions of the United States, but there was no clear or consistent difference in the relative magnitudes of change for sub-daily vs daily events.

Climate models↗

A Model-Free Voltage Control Approach to Mitigate Motor Stalling and FIDVR for Smart Grids

Electric power networks are large and highly nonlinear dynamical systems that present unique challenges to control design. Though there is a large number of dynamic models for power system stability and control, many models are only useful with right assumptions and wrong for other tasks. Moreover, the dynamic behavior of the grid is increasingly complex under the banner of smart grids. These lead to the difficulty of developing appropriate dynamic modeling, and thus an efficient control strategy. To avoid such modeling challenges, here we present a novel dynamic voltage control strategy based on a model-free control (MFC) approach, requiring no modeling procedure. In particular, it focuses on fault-induced delayed voltage recovery (FIDVR) events, which require complex and accurate dynamic load models to replicate such events. This work utilizes MFC as an online controller to achieve the desired voltage stability under the FIDVR event. The proposed MFC strategy allows simple implementation and low computational cost for efficient mitigation of FIDVR. For benchmarking, a reasonably accurate dynamic performance model is explored. Simulation results with the IEEE 57 bus test network demonstrate the enhanced dynamic voltage profile for load buses having induction motors with the support of reactive power resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A case and statistical study of transient magnetic field events at geosynchronous orbit and their solar wind origin

We present a statisical survey of Prognoz 10 solar wind observations at the times of transient (step function and impulsive) variations in the dayside magnetospheric magnetic field strength measured by the GOES 5 and 6 geosynchronous satellites. The results indicate that 51% of the magnetospheric events can be associated with corresponding variations in the solar wind dynamic pressure. A further 17% of the events can be associated with fluctuations in the interplanetary magnetic field orientation in the sense previously associated with foreshock pressure pulses. We find no tendency for impulsive events at dayside geosynchronous orbit to be associated with north/south fluctuations in the interplanetary magnetic field (IMF) orientation, nor for the events to occur primarily during intervals of southward IMF. The success rate for associating transient events at dayside geosynchronous orbit with solar wind features decreases as Prognoz 10 moves farther from the Earth-Sun line. The observations indicate that variations in the solar wind dynamic pressure and foreshock pressure pulses associated with variations in the IMF cone angle are the predominant causes of large-amplitude transient events observed at dayside geosynchronous orbit.

Borodkova, N. L.↗

Trigger of Standard and Blowout Solar Jets: I. Parametric Studies of the Magnetic Field Geometry

Context. Jets are dynamic, impulsive, well collimated plasma events developing at many different scales and in differentlayers of the solar atmosphere.Aims. Jets are believed to be induced by magnetic reconnection a process central to many astrophysical phenomena.Studying their dynamics can help us to better understand the processes acting in larger eruptive events (e.g. flares andcoronal mass ejection) as well as mass, magnetic helicity and energy transfer at all scale in the solar atmosphere. Therelative simplicity of their magnetic geometry and topology, compared with larger solar active events, makes jets idealcandidate for studying the fundamental role of reconnection in energetic events. Methods. In this study, using our state-of-the-art numerical solver ARMS, we present several parametric studies of anumerical three-dimensional magneto-hydrodynamic model of solar jet-like events. We study the impact of the magneticfield inclination and photospheric field distribution on the generation and properties of two types of observed solar jets:the so-called standard and blowout jets.Results. The present parametric studies validate our model of jets for different geometric properties of the magneticconfiguration. On one hand, a blowout jets is eventually always trigger for the range of parameters that we tested. The3D magnetic null-point configuration is a very robust structure for the energy storage and impulsive release characteristicof blowout jets. On the other hand, the existence of the standard jet depends on the magnetic geometry. We show thatthe reconnection occurring during the standard jet phase influences the properties of the trigger of the blowout jet.Conclusions. Our results allow us to better understand the energization, triggering and driving processes of standardand blowout jets. Our model allows us to predict the impulsiveness and energetics of jets in terms of the surroundingmagnetic field configuration. Finally we discuss the interpretation of standard jets and blowout jets and the physicalfactors that determine which type of jets will occur.

Pariat, E.↗

A Swing of the Pendulum: The Chemodynamics of the Local Stellar Halo Indicate Contributions from Several Radial Merger Events

We find that the chemical abundances and dynamics of APOGEE and GALAH stars in the local stellar halo are inconsistent with a scenario in which the inner halo is primarily composed of debris from a single massive, ancient merger event, as has been proposed to explain the Gaia-Enceladus/Gaia Sausage (GSE) structure. The data contain trends of chemical composition with energy that are opposite to expectations for a single massive, ancient merger event, and multiple chemical evolution paths with distinct dynamics are present. We use a Bayesian Gaussian mixture model regression algorithm to characterize the local stellar halo, and find that the data are fit best by a model with four components. We interpret these components as the Virgo Radial Merger (VRM), Cronus, Nereus, and Thamnos; however, Nereus and Thamnos likely represent more than one accretion event because the chemical abundance distributions of their member stars contain many peaks. Although the Cronus and Thamnos components have different dynamics, their chemical abundances suggest they may be related. We show that the distinct low- and high-α halo populations from Nissen & Schuster are explained by VRM and Cronus stars, as well as some in situ stars. Because the local stellar halo contains multiple substructures, different popular methods of selecting GSE stars will actually select different mixtures of these substructures, which may change the apparent chemodynamic properties of the selected stars. We also find that the Splash stars in the Solar region are shifted to higher v $\phi$ and slightly lower [Fe/H] than previously reported.

79 ASTRONOMY AND ASTROPHYSICS↗