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At least 307 records · Page 17

Spatial patterns in occupancy and density of larval lampreys in freshwater habitats restored to a Stage 0 condition

Abstract We examined occupancy and density of larval lampreys ( Entosphenus tridentatus and Lampetra spp.) in two rivers in Oregon (USA) restored to a Stage 0 condition 1–5 years prior, using a multiscale occupancy model and a zero‐inflated Poisson mixture model. We sampled lampreys using backpack electrofishing in randomly distributed, paired, 1‐m 2 quadrats and recorded environmental data. Probabilities of occupancy and density were higher when water velocity was low, the substrate was noncompacted, and sediment was dominated by fines (<4 mm). At mean water depth (0.34 m) and velocity (0.09 m/s), estimated densities in occupied quadrats were 4.8 lampreys/m 2 (95%: 3.4–6.9) when the substrate was compacted, and fines were not dominant, and 21.1 lampreys/m 2 (95%: 17.7–25.3) when the substrate was noncompacted and fines were dominant. Probabilities of detecting occupancy in a 1‐m 2 quadrat sampled by backpack electrofishing were 0.76 (95%: 0.64–0.87) when captured after visual observation and 0.80 (95%: 0.71–0.88) with blind sweeps (i.e., constantly moving the net regardless of observation). The probability of capturing a single lamprey in a quadrat sampled by blind sweeps was 0.32 (95%: 0.27–0.37). Sampling in paired 1‐m 2 quadrats facilitated concurrent examination of patterns in occupancy and density while accounting for capture probability, which could aid temporal monitoring of restored habitats. To the best of our knowledge, this is the first study to document occupancy and estimate densities of larval lampreys in habitats that underwent valley floor restoration to Stage 0. We observed both lamprey genera within 5 years of restoration. Aquatic restoration that increases low‐velocity, noncompacted, fine sediment habitats could benefit lampreys.

Harris, Julianne E.↗

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗

Generative AI for Wind-Wave Inflows

Extreme wind-wave conditions can create dangerous or damaging environmental conditions for sea-based structures and watercrafts. However, the model of consistent, coupled wind-wave flow conditions is computational expensive, even for simple flow scenarios. This work examines the use of diffusion-based generative artificial intelligence tools to accelerate the generation of these two-phase flows and to characterize probabilities of various states to help with the generation of extreme patterns.

17 WIND ENERGY↗

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗

Interaction between the emerging components of online shopping and in-person activities: insights from a behavioral survey

The rise of technological advancements has led to the commonplace practice of online shopping for retail, grocery, and food. However, little research has been conducted on the interplay of these components in burdened communities (BCs) that face issues of marginalization and limited access to digital resources. Here, this study aims to provide a comprehensive understanding of travel behavior changes by analyzing the interconnectedness of the emerging components of online shopping (retail, grocery, and food) and in-person activities in both BCs and non-BCs. A unique household-level database is created by linking the 2021 Puget Sound Household Travel Survey and the US Department of Transportation’s burdened community databases, and a conditional mixed process model is estimated to account for unobserved endogeneity. The findings suggest households living in BCs are less likely to order online retail goods and groceries compared to non-BC households. Additionally, the probability of making more restaurant trips decreases for households living in BCs. The study highlights the digital divide that exists in BCs and the differences in online and in-person shopping activities across socioeconomic levels. Policymakers may address these disparities to promote better access to goods and services for all. Besides, planners may need to improve the travel demand models by accounting for the emerging components of online shopping and the trip frequencies by purpose in BCs.

Digital Divide↗

Experimental validation of the mechanistic scale-up methodology of gas–solid spouted beds using radioactive particle tracking (RPT)

The very high-temperature reactors (VHTRs) are highly ranked among candidates of Generation IV of nuclear reactors due to their high efficiency, safety, the resistance to proliferation, and reliability. The VHTRs are preferentially fueled by Tristructural-isometric (TRISO) coated fuel particles which has fuel kernels of fissile material coated by four coating layers: a porous buffer pyrolysis carbon layer (buffer PyC), an inner dense pyrolysis carbon layer (IPyC), a silicon carbide layer (SiC) and an outer dense pyrolysis carbon layer (OPyC). The heart of the operation and safety of the VHTRs significantly depends on the reliability of the coating layers of TRISO particles to retain metallic and gaseous fission products within the particles. The technique used for coating TRISO particles are gas-solids spouted beds via chemical vapor deposition (CVD). Fabrication of high-quality low-defect TRISO fuel particles fuel at larger scale spouted beds is required to support the commercialization of the VHTRs. In this work, our new developed mechanistic scale-up methodology of gas-solids spouted beds based on matching the radial profile of gas-holdup has been demonstrated and validated using radioactive particle tracking (RPT). Two spouted beds of small and larger scales were used in the study. Three sets of conditions were carried out which include the conditions of the reference case in the large scale, conditions that provide similar gas holdup radial profile to that of the reference case and conditions that provided dissimilar gas holdup radial in the small-scale spouted beds. The results confirm the validation of the scale-up methodology in terms of the dimensionless values of the spout diameter, cumulative probability distribution of the solids particles penetration into the spout, fraction of cycle time in each region of the bed, the radial profiles of the dimensionless values of the root-mean-square particle velocities and solids eddy diffusivity. Finally, the results further advance the knowledge and understanding of the gas-solids spouted beds provide deeper insight into their solids dynamics and presenting important benchmarking data for validating computational fluid dynamics codes and models. At last, procedures are established for the implementation of the new scale-up methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Nucleon clustering at kinetic freezeout of heavy-ion collisions via path-integral Monte Carlo

Clustering of the four-nucleon system at kinetic freezeout conditions is studied using path-integral Monte Carlo techniques. This method seeks to improve upon previous calculations which relied on approximate semiclassical methods or few-body quantum mechanics. Estimates are given for the decay probabilities of the 4N system into various light nuclei decay channels and the strength of spatial correlations is characterized. Additionally, a simple model is presented to describe the impact of this clustering on nucleon multiplicity distributions. Additionally, the effects of a possible modification of the inter-nucleon interaction due to the close critical line (and hypothetical QCD critical point) on the clustering are also studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Directed Gas-Phase Formation of the 1-Cyanovinyl Radical (H 2 CCCN, X 2 A′) in the Interstellar Medium

The formation pathways to nitrogen-containing molecules and radicals are crucial to the understanding of the carbon–nitrogen chemistry in interstellar and atmospheric environments. While over 65 nitrogen-containing neutral species have been observed in deep space to date, their formation mechanisms─in particular, those of radical species─remain largely speculative. The crossed molecular beam technique in conjunction with electronic structure and statistical calculations was utilized to offer a detailed overview of the fundamental pathways in the gas-phase bimolecular reaction of ground-state atomic carbon (C, 3 P) with acetonitrile-d 3 (CD 3 CN, X 1 A 1 ) under single-collision conditions leading to the formation of the 1-cyanovinyl radical (D 2 CCCN, X 2 A′) coupled with deuterium atom loss. Here, the indirect reaction was initiated by barrierless carbon-atom addition, with the most probable route involving carbon addition across the carbon–nitrogen nitrile triple bond of acetonitrile, forming a three-membered ring intermediate followed by ring-opening and unimolecular decomposition via atomic deuterium loss from the C3 carbon atom. The reaction was overall exoergic, and intermediates and transition states lie lower in energy than the separated reactants, unlocking the reaction of carbon with acetonitrile in low-temperature environments such as cold molecular clouds, e.g., Taurus Molecular Cloud (TMC-1), and planetary atmospheres, e.g., Saturn’s moon Titan. In these environments, the 1-cyanovinyl radical may act as a building block for cyano-substituted polycyclic aromatic hydrocarbons and N-heterocycles, thus furthering our understanding of the complex carbon–nitrogen chemistry in deep space.

Chemical reactions↗

Direct numerical simulation of supercritical oxy-methane mixing layers with CO 2 substituted counterparts

Direct numerical simulations (DNS) of temporally developing, three dimensional, CH 4 /CO 2 , CH 4 /O 2 and CO 2 /O 2 mixing layers, are conducted at a supercritical pressure of 300 atm. To effectively model the supercritical regime, the employed formulation includes the compressible form of the governing equations, the cubic Peng-Robinson equation of state and a generalized formulation for heat and mass flux vectors derived from non-equilibrium thermodynamics and fluctuation theory. A linear inviscid stability analysis is also performed for each case, to determine its most unstable wavelength. Flow visualizations reveal the presence of high density gradient magnitude regions for all three mixing layers, with conditional averages indicating increased presence of heavier fluid species within these regions. No significant departures are observed from perfect gas behavior, with compressibility factors very close to unity for all three mixing cases. Applicability of presumed probability density function methods (PDF) is examined for the three supercritical mixing layers. An a priori analysis is also conducted to investigate various simplifying assumptions employed in modeling various subgrid scale (SGS) flux models. Two additional terms are identified in the large eddy simulations (LES) equations, the gradient of SGS contribution of pressure in the momentum equation and the gradient of SGS contribution of heat flux in energy equation, whose magnitudes are similar and comparable with their respective resolved terms. The performance of the scale similarity model to represent these additional terms is investigated. Lastly, the performance of Smagorinsky, gradient and scale similarity models are also investigated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Uniform Mechanical Loading Can Test for Nonuniform Loading Durability

In this work, we present a method to evaluate the equivalency between any module mechanical loading conditions. The method is developed to address the specific failure mode of glass fracture and is based on Weibull analysis and weakest link theory. It considers the varying stress profile across the module to calculate the probability of glass fracture, which is used as the metric of equivalency. An idealized nonuniform loading scheme is employed to demonstrate the method and introduce the concept of the equivalent uniform load factor: a factor applied to the maximum pressure of the nonuniform load to obtain the equivalent uniform load value. It is demonstrated that this factor is less than unity for all nonuniform load cases considered, including snow and various characters of wind loading. These significant results suggest that uniform loading may be reliably, and practically, employed to evaluate photovoltaic module glass for nonuniform loading durability.

14 SOLAR ENERGY↗

Generalized Wigner theorem for noninvertible symmetries

In this article, we establish the conditions under which a conservation law associated with a non-invertible operator may be realized as a symmetry in quantum physics. As established by Wigner, all quantum symmetries must be represented by either unitary or antiunitary transformations. Relinquishing an implicit assumption of invertibility, we demonstrate that the fundamental invariance of quantum transition probabilities under the application of symmetries mandates that all non-invertible symmetries may only correspond to projective unitary or antiunitary transformations, i.e., partial isometries. This extends the notion of physical states beyond conventional rays in Hilbert space to equivalence classes in an extended, gauged Hilbert space, thereby broadening the traditional understanding of symmetry transformations in quantum theory. Our generalized theorem applies irrespective of the origin of the (non)invertible symmetry, holds in arbitrary spatial dimensions, and is independent of the Hamiltonian or action. We explore its physical consequences and, using simple model systems, illustrate how the distinction between invertible and non-invertible symmetries can sometimes be tied to the choice of boundary conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Modeling the Cosmological Lyman-𝛼 Forest at the Field Level

The distribution of absorption lines in the spectra of distant quasars, called the Lyman-𝛼 (Ly-𝛼) forest, is a unique probe of cosmology and the intergalactic medium at high redshifts and small scales. The statistical power of ongoing redshift surveys demands precise theoretical tools to model the Ly-𝛼 forest. We address this challenge by developing an analytic, perturbative forward model to predict the Ly-𝛼 forest at the field level for a given set of cosmological initial conditions. Our model shows a remarkable performance when compared with the Sherwood hydrodynamic simulations: it reproduces the Ly-𝛼 forest flux power spectrum, its cross-correlation with dark matter halos, and the one-point probability distribution function of both fields at the percent level down to scales of a few Mpc. Our work provides crucial tools that bridge analytic modeling on large scales with simulations on small scales, enabling field-level inference from Ly-𝛼 forest data and simulation-based priors for cosmological analyses. Furthermore, this is especially timely for realizing the full scientific potential of the Ly-𝛼 forest measurements by the dark energy spectroscopic instrument.

Cosmological parameters↗

Demonstration of CFD to support the coupled analysis of a reactor pressure vessel subjected to pressurized thermal shock

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended duration or under accident condition. As one of the most significant components of a reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Aging degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The prediction of the temperature field is achieved by using computational fluid dynamics (CFD) simulation. In this report, a demonstration CFD standalone simulation is performed to support coupled analysis for Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS). The study use a simplified computational domain to represents a real RPV. The purpose of the study is to demonstrate the transient temperature response of RPV to ECC injection. The CFD model is built in a robust and efficient way for further coupled calculation. The next steps of this work, including the coupled thermal and tensor mechanics capabilities using Cardinal are expected to be complete by the end of FY21 for the demo problem. After this, into FY22, the capability will be demonstrated for a realistic RPV.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multi physics simulation on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) by using Cardinal

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Microscopic Derivation of Transition-state Theory for Complex Quantum Systems

The decay of quantum complex systems through a potential barrier is often described with transition-state theory, also known as RRKM theory in chemistry. Here we derive the basic formula for transition-state theory based on a generic Hamiltonian as might be constructed in a configuration-interaction basis. Two reservoirs of random Hamiltonians from Gaussian orthogonal ensembles are coupled to intermediate states representing the transition states at a barrier. Under the condition that the decay of the reservoirs to open channels is large, an analytic formula for reaction rates is derived. Here, the transition states act as independent Breit–Wigner resonances which contribute additively to the total transition probability, as is well known for electronic conductance through resonant tunneling states. It is also found that the transition probability is independent of the decay properties of the states in the second reservoir over a wide range of decay widths.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Physics-coupled data-driven design of high-temperature alloys

We present a materials design loop, which streamlines physics-coupled machine learning (ML) surrogate models to discover new alloy chemistries with improved properties. The efficacy is demonstrated by discovering a high-temperature alumina-forming austenitic (AFA) stainless steel with enhanced creep, followed by experimental validation. The ML models have been trained using a well-curated, highly consistent experimental dataset augmented with synthetic microstructural features from a computational thermodynamic approach. We have populated a large number of hypothetical AFA alloys to explore the high-dimensional composition space and have predicted their creep properties by providing the same synthetic input features obtained from the trained ML models. Uncertainties from the ML training were taken as thresholds for truncating predicted results to identify alloys with improved or deteriorated creep. Individual elemental compositions have been determined via probability density distribution analysis from the group of alloys at the top and bottom of the predicted creep values for further virtual and experimental validations. In conclusion, we anticipate that this workflow can be applied to screen desired conditions, such as chemistry and processing parameters, in high-dimensional space through physics-guided data analytics.

Alloy design↗

Evaluation of sustainable waste management: An analysis of techno-economic and life cycle assessments of municipal solid waste sorting and decontamination

This study evaluates the economic and environmental feasibility of Municipal Solid Waste (MSW) sorting and decontamination technologies across urban, suburban, and rural areas. Using Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA), the research assesses cost-effectiveness and environmental impacts, with a focus on cost variability analyzed through Monte Carlo simulations. Findings indicate significant cost differences based on population density: rural areas incur high costs up to $$764/ton due to low waste volumes and limited infrastructure, whereas suburban and urban areas have more feasible costs ranging from $36.3 to $142.5/ton. Environmental impacts also vary, with greenhouse gas emissions at 171 kg CO 2 eq/ton for copy paper and 118.6 kg CO 2 eq/ton for plastics. PM2.5 levels are 9.1 g/ton for copy paper and 6.3 g/ton for plastics, with sorting lines being the main contributors. Monte Carlo simulations reveal a 50% probability of costs being below $$102.26/ton for copy paper and $115.8/ton for plastics in suburban settings. Further, the study underscores the importance of customized waste management strategies to improve economic viability and sustainability based on local conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗