Distributional analysis of radiation conditions for the $3+1$ wave equation
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Mathematics↗
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Plutonium Oxidation State Distribution under WIPP Relevant Conditions (Rev. 2)
The oxidation state of plutonium in the Waste Isolation Pilot Plant (WIPP) environment has been a topic of interest since the initial compliance certification application. Plutonium (Pu) was initially expected to be present primarily as Pu(IV), but since the presence of Pu(III) could not be ruled out, it was also included in performance assessment (PA) calculations. The redox of the other variant actinides, uranium (U) and neptunium (Np), are also coupled to the plutonium redox. This led to a position in performance assessment calculations that is commonly referred to as “50/50”. In which half of the PA realizations assume solubility is dominated by the low oxidation state [U(IV), Np(IV), Pu(III)] and the other half assume solubility is dominated by the higher oxidation state [U(VI), Np(V), Pu(IV)]. Recently, a joint group of WIPP project participants from Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), and the Department of Energy’s Carlsbad Field Office (DOE-CBFO) agreed on a new path forward for the oxidation state model in PA which will decouple the redox active actinides and will instead consider their redox as a function of E h . This will take the current binary approach and turn it into a system with four possible redox states.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Physical conditions, dynamics and mass distribution in the center of the galaxy
Investigations of the central 10 pc of the Galaxy, and conclusions on energetics, dynamics, and mass distribution derived from X and gamma ray measurements and from infrared and microwave studies, especially from spectroscopy, high resolution imaging, and interferometry are reviewed. Evidence for and against a massive black hole is analyzed.
Genzel, R.↗
Analyzing at-scale distribution grid response to extreme temperatures
Threats against power grids continue to increase, as extreme weather conditions and natural disasters (extreme events) become more frequent. Hence, there is a need for the simulation and modeling of power grids to reflect realistic conditions during extreme events conditions, especially distribution systems. Herein, this paper presents a modeling and simulation platform for electric distribution grids which can estimate overall power demand during extreme weather conditions. The presented platform's efficacy is shown by demonstrating estimation of electrical demand for 1) Electricity Reliability Council of Texas (ERCOT) during winter storm Uri in 2021, and 2) alternative hypothetical scenarios of integrating Distributed Energy Resources (DERs), weatherization, and load electrification. In comparing to the actual demand served by ERCOT during the winter storm Uri of 2021, the proposed platform estimates approximately 34 GW of peak capacity deficit. These numbers are consistent with state-of-the-art prediction results published in the literature. For the case of the future electrification of heating loads, peak capacity of 78 GW (124% increase) is estimated, which would be reduced to 47 GW (38% increase) with the adoption of efficient heating appliances and improved thermal insulation. Integrating distributed solar PV and storage into the grid causes improvement in the local energy utilization and hence reduces the potential unmet energy by 31% and 40%, respectively.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A study of the distribution of molecules under free molecular flow conditions after collisions with simple geometries
Molecular distribution under free molecular flow conditions within surfaces of simple geometries
SURFACE GEOMETRY↗
Cold Plasmaspheric Electrons Affected by ULF Waves in the Inner Magnetosphere: A Van Allen Probes Statistical Study
Six years of Van Allen Probes data are used to investigate cold plasmaspheric electrons affected by ultralow-frequency (ULF) waves in the inner magnetosphere (L<7) including spatial distributions, occurrence conditions, and resonant energy range. Events exhibit a global distribution within L= 4–7 but preferentially occur at L~5.5–7 in the dayside, while there is higher occurrence rate in the duskside than dawnside. They can occur under different geomagnetic activities and solar wind velocities (V S ), but the occurrence rates are increasing with larger AE, |SYMH|, and V S . These features are closely associated with the generation and propagation of ULF waves in Pc4 (45–150 s) and Pc5 (150–600 s) bands. Combined with electron observations from HOPE instrument, the resonant energies inferred from wave power indicate that cold electrons at ones to hundreds of electron volts can be affected by ULF waves. Finally, this study may shed new light on further investigations on the acceleration and transportation of cold plasmaspheric particles that would affect plasmaspheric material release to the Earth's magnetosphere and instabilities for exciting various waves.
79 ASTRONOMY AND ASTROPHYSICS↗
Strategy for distributed controller defence: Leveraging controller roles and control support groups to maintain or regain control in cyber-adversarial power systems
Distributed controllers play a prominent role in electric power grid operation. The coordinated failure or malfunction of these controllers is a serious threat, where the resulting mechanisms and consequences are not yet well-known and planned against. If certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the system to an unsafe state. The authors present a strategy for distributed controller defence (SDCD) for improved grid tolerance under conditions of distributed controller compromise. The work of the authors’ first formalises the roles that distributed controllers play and their control support groups using controllability analysis techniques. With these formally defined roles and groups, the authors then present defence strategies for maintaining or regaining system control during such an attack. A general control response framework is presented here for the compromise or failure of distributed controllers using the remaining, operational set. The SDCD approach is successfully demonstrated with a 7-bus system and the IEEE 118-bus system for single and coordinated distributed controller compromise; the results indicate that SDCD is able to significantly reduce system stress and mitigate compromise consequences.
97 MATHEMATICS AND COMPUTING↗
Distributed Small-Signal Stability Conditions for Inverter-Based Unbalanced Microgrids
The proliferation of inverter-based generation and advanced sensing, controls, and communication infrastructure have facilitated accelerated deployment of microgrids. A coordinated network of microgrids can maintain reliable power delivery to critical facilities during extreme events. Low-inertia offered by the power-electronics–interfaced energy resources, however, can present significant challenges to ensuring stable operation of the microgrids. In this work, distributed small-signal stability conditions for inverter-based microgrids are developed that involve the droop-controller parameters and the network parameters (e.g. line impedances, loads). The distributed closed-form parametric stability conditions derived in this paper can be verified in a computationally efficient manner, facilitating reliable design and operations of networks of microgrids. Dynamic phasor models have been used to capture the effects of electromagnetic transients. Furthermore, numerical results are presented, along with PSCAD simulations, to validate the analytical stability conditions. Effects of design choices, such as the conductor types, and inverter sizes, on the small-signal stability of inverter-based microgrids are investigated to derive useful engineering insights.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation
We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.
97 MATHEMATICS AND COMPUTING↗
A Transfer Learning Framework for Power System Event Identification
Not Available
24 POWER TRANSMISSION AND DISTRIBUTION↗
Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam
Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.
60 APPLIED LIFE SCIENCES↗
Vibration of thermally stressed plates with various boundary conditions.
By discarding Lurie's (1952) assumption of mode identity, it is shown that linear theory correctly predicts the frequency of all modes of a thermally stressed cantilever plate as well as the frequency and modes of plates with other boundary conditions. The thermal stress distribution is obtained for whatever temperature distribution and boundary conditions that may be specified. Experimental results are compared to calculated results for several different plates. Boundary conditions for the plates range from a plate with edges completely clamped to a plate with edges completely free with various other combinations of mixed and uniform edge conditions. Comparison of calculated data to experimental data shows that accurate, quantitative results can be obtained from linear theory for 'as cut' real plates for a significant range of heating when the assumption of mode identity is discarded.
Bailey, C. D.↗
Analysis of vector wind change with respect to time for Cape Kennedy, Florida: Wind aloft profile change vs. time, phase 1
Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.
Adelfang, S. I.↗
Diagnostics of dust content in spiral galaxies: Numerical simulations of radiative transfer
In order to find the best observable diagnostics for the amount of internal extinction within spiral galaxies, we have constructed realistic models for disk galaxies with immersed dust layers. The radiative transfer including both scattering and absorption has been computed for a range of model galaxies in various orientations. Standard galaxy surface photometry techniques were then applied to the numerical data to illustrate how different observables such as total magnitude, color and luminosity distribution behave under given conditions of dust distribution. This work reveals a set of superior diagnostics for the dust in the disk. These include not only the integrated parameters, but also the apparent disk structural parameters, the amplitude of the asymmetry between the near and far sides of the galaxy as divided by the apparent major axis and their dependence on the orientation of the galaxy with respect to the observer. Combining the above diagnostics with our impressions of real galaxies, we arrive at the qualitative conclusion that galaxy disks are generally optically thin. Quantitative conclusions will appear in subsequent work.
Byun, Y. I.↗
Resilience Assessment Framework For Electric Distribution Systems Performance Under Extreme Conditions
The devastating impact of extreme weather-related events is increasingly evident on power grids, especially on distribution grids. The severity of their potential impact calls for 1) developing a suitable resilience assessment framework to capture the system performance and 2) assessing relevant mitigative strategies to lessen the impact of such events. This paper proposes a framework to identify grid vulnerabilities using the energy-at-risk concept to select, disconnect and isolate grid portions due to a resilience event. The proposed framework mainly consists of two steps; i) processing the utility's available infrastructure, i.e., a network model, possible switching combinations, and outage information for those combinations, as a graph-based database, and ii) implementing a novel optimal switching algorithm leveraging database and grid simulated metrics. These switching actions are generated to implement load curtailment in a rolling manner during anticipated grid scarcity conditions. In this study, a test case is created using two taxonomy feeders and is simulated against an extreme temperature event, e.g., a long, relatively cold, and prolonged freeze peak, thereby creating stress on the grid. It is demonstrated that the proposed framework allows utilities to predict the energy-at-risk during such resilience events and design suitable outage management strategies.
Poudel, Shiva↗
Bayesian Integration of multiscale environmental data
The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.
CHEN, JINSONG↗
Bayesian Integration of multiscale environmental data
The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.
CHEN, JINSONG↗
Parameterizing hot electron energy distributions for tabular emissivities and opacities
Cold Kα and Kβ emission spectroscopy is a powerful diagnostic for plasma conditions and distributions of energetic electrons produced in short pulse laser experiments. SPECT3D post-processes hydrodynamics code output and simulates high-resolution spectra and images for plasmas containing arbitrary distributions of hot electrons, however these calculations can become prohibitively expensive for plasmas requiring complex atomic data and detailed computational grids. To significantly increase calculation speed, it is desirable to use pre-configured opacity tables that include information about hot electrons, rather than calculating emissivity and opacity for every grid point by solving collisional-radiative atomic kinetic rate equations. However, to tabulate such opacities, a general parameter-based description of hot electron energy distributions must be found. To be practical, hot electrons should be represented with an analytic function of just a few parameters which, in addition to temperature and density, can be used to define parameter space for opacity tables. In this paper, we present a method that allows for describing a set of arbitrary binned hot electron distributions with a simple analytic function, with only a modest impact on the accuracy of the simulations. Increased calculation speeds of 50–100x are demonstrated. In conclusion, we also discuss details of opacity calculations and present synthetic spectroscopy data based on post-processing of detailed particle-in-cell simulations relevant to the ongoing experimental campaign at the Omega EP laser facility.
74 ATOMIC AND MOLECULAR PHYSICS↗