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At least 721 records · Page 40

Developing a remediation framework

When harmful contaminants are detected in soil, sediment, or groundwater (or suspected due to industrial activities), remediation efforts may be required to protect human health and the environment. This chapter will introduce and discuss the steps in the general site remediation process that are key when approaching any remediation strategy, regardless of the site complexity. While these steps are described in a linear fashion, in most cases, the approach is more fluid and iterative depending on the desired outcomes and success of each progressive clean-up effort along the way. This chapter will additionally articulate some key considerations which may be important to the overall remediation strategy depending on the particular needs and desired outcomes. From these more general discussions, the chapter will branch into a case-study of the remediation approach, or process steps, previously/currently/in the future taking place at the Hanford Site, as one example of a complex waste sites in the United States. As indicated earlier, while a remediation strategy can be more simply described by a progression of general process steps, it is far more likely to observe fluidity and strategy evolution over time from the first conceived strategy as remediation progress occurs. The chapter concludes with a brief discussion of how the strategy at the Hanford Site has evolved to provide a singular example of what this evolution might look like for other complex waste sites.

Muller, Katherine A.↗

Constellation's best estimate alternate source term methodology overview

Safety analyses for a nuclear power plants need to consider postulated accidents that results in at risk of accidental release of radiation. The regulations require plant specific safety analysis reports to include an evaluation of the requirements of 10CFR50.67. Such a safety analysis report mandates limits such that calculated radiological consequences relative to certain dose locations do not exceed a total effective dose equivalent (TEDE) limits following a postulated release of radioactivity. Calculations are performed to estimate the radiological consequences, in terms of dose, to people and equipment to ensure the estimated doses are within the prescribed limits. Analysis should demonstrate, with reasonable assurance, that these prescribed limits are complied with. Conventional methodologies utilize conservative approaches to address lack of uncertainty quantification in the utilized approaches, methods, and/or inputs. These built-in excess conservatisms often result in compounding effects and hence overly conservative results in the estimated radiological consequences, which leads to inaccurate margin evaluation for operation and accident mitigation. Therefore, evaluating accurate dose consequences is needed for both operational and safety reasons. The research documented in this paper provides an overview of Constellation's Best Estimate Alternate Source Term (BEAST) Methodology. BEAST methodology relies upon the use of realistic yet bounding input distributions for key analysis parameters, which replaces use of conservative deterministic singular inputs that bound overall analysis domain. This approach enables evaluating a more accurate accident analysis response, while enabling a bounding licensing basis envelope via more accurate quantification of uncertainty in the application. Therefore, built-in margin for a given scenario is more accurately evaluated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗

Source noise suppression in attosecond transient absorption spectroscopy by edge-pixel referencing

Attosecond transient absorption spectroscopy (ATAS) is used to observe photoexcited dynamics with outstanding time resolution. The main experimental challenge of this technique is that high-harmonic generation sources show significant instabilities, resulting in sub-par sensitivity when compared to other techniques. This paper proposes edge-pixel referencing as a means to suppress this noise. Two approaches are introduced: the first is deterministic and uses a correlation analysis, while the second relies on singular value decomposition. Each method is demonstrated and quantified on a noisy measurement taken on WS 2 and results in a fivefold increase in sensitivity. The combination of the two methods ensures the fidelity of the procedure and can be implemented on live data collection but also on existing datasets. The results show that edge-referencing methods bring the sensitivity of ATAS near the detector noise floor. An implementation of the post-processing code is provided to the reader.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unidirectional amplification in the frozen mode regime enabled by a nonlinear defect

A stationary inflection point (SIP) is a spectral singularity of the Bloch dispersion relation ω(k) of a periodic structure where the first and the second derivatives of ω with respect to k vanish. An SIP is associated with a third-order exceptional point degeneracy in the spectrum of the unit-cell transfer matrix, where there is a collapse of one propagating and two evanescent Bloch modes. At the SIP frequency, the incident wave can be efficiently converted into the frozen mode with greatly enhanced amplitude and vanishing group velocity. This can be very attractive for applications, including light amplification. Due to its non-resonant nature, the frozen mode regime (FMR) has fundamental advantages over common cavity resonances. Furthermore, we propose, a novel, to the best of our knowledge, scheme for FMR-based unidirectional amplifiers by leveraging a tailored amplification/attenuation mechanism and a single nonlinear defect. The defect breaks the directional symmetry of the periodic structure and enables nonlinearity-related unidirectional amplification/attenuation in the vicinity of the SIP frequency. We demonstrate the robustness of the amplification mechanism to local impurities and parasitic nonlinearity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High finesse buckled microcavities

Optical cavities are widely used in modern science and technology to enable a wide range of both quantum and classical applications. Recently, the growing demand for miniaturization and high performance has fueled the exploration of new fabrication methods beyond traditional polishing techniques and macroscopic mirrors. Visible and near-infrared (NIR) wavelengths are particularly important for quantum applications, where achieving low-loss resonators is also more challenging than in the telecom range, presenting unique challenges and opportunities for microscopic cavity systems. Here, we present a fabrication method for making NIR microcavities using buckled dielectric membrane mirrors, achieving a record finesse of 0.9 million at 780 nm for microcavities. We demonstrated flexible device geometries—including singular mirrors and mirror arrays, featuring radii of curvature ranging from 1 to 10 mm. The fabrication process offers high uniformity, high yield, and robust performance across a wide range of cavity lengths. Additionally, we can produce easy-to-assemble microcavity packages, with a total volume of ~2(4) mm 3 , featuring optical modes with a linewidth of 5.16 MHz (570 kHz) and a free spectral range (FSR) of 3.18 THz (150 GHz). Our results extend the frontier of microcavity fabrication for classical and quantum photonic technologies.

Ding, Sophie Weiyi [Harvard Univ., Cambridge, MA (↗

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗

System identity and transformation in petroleum jurisdictions: A multi-method approach for the North Slope Borough, Alaska

Capturing the multidimensionality of a bounded social-environmental system (SES) presents a range of challenges to interdisciplinary researchers due to the need to integrate divergent scientific paradigms, scalar data, and social theories. Contemporary Arctic circumpolar SESs studied under conditions of rapid and unprecedented climatic, ecological, economic, and sociopolitical change, defy any singular established methodological approach that aims to schematize and interpret the system for decision-making purposes. As a small interdisciplinary team working within a large Arctic SES modeling effort, we have found that developing systems models to support resilience in the Arctic requires an understanding of system dynamics that is attentive to holistic indicators of change, measured both quantitatively and qualitatively. Using the Alaska North Slope Borough as a case study, we apply three convergent frameworks to capture significant dimensions of the system for improved problem definition in confronting the challenges of Arctic climate change. We describe contemporary “oil and gas” social-ecological system components and dynamics, the historical processes and transformations that fundamentally altered the system, and the scientific projections for the most likely catalysts of future change. This analysis results in a typology for defining subnational Arctic hydrocarbon SESs. We conclude that the future of oil and gas development as a policy pathway in different locations experiencing rapid climate change can be evaluated when difficult-to-quantify variables are included.

Lovecraft, Amy Lauren↗

Charm meson and charm-meson molecule in an expanding hadron gas

We present our studies on the evolution of charm mesons after the kinetic freeze-out of the expanding hadron gas produced in a heavy-ion collision and the thermal correction to a loosely bound charm-meson molecule in a pion gas. The πD* → πD* reaction rates have t-channel singularities that give contributions inversely proportional to the thermal width of the D. The ratio of the D 0 and D + production rate can differ significantly from those predicted using the measured D* branching fractions. The thermal correction to a loosely bound charm-meson molecule in a pion gas comes primarily from the complex thermal energy shift of the charm-meson constituents.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring numerical blow-up phenomena for the Keller–Segel–Navier–Stokes equations

The Keller–Segel–Navier–Stokes system governs chemotaxis in liquid environments. This system is to be solved for the organism and chemoattractant densities and for the fluid velocity and pressure. It is known that if the total initial organism density mass is below 2π there exist globally defined generalised solutions, but what is less understood is whether there are blow-up solutions beyond such a threshold and its optimality. Motivated by this issue, a numerical blow-up scenario is investigated. Approximate solutions computed via a stabilised finite element method founded on a shock capturing technique are such that they satisfy a priori bounds as well as lower and L 1 (Ω) bounds for the organism and chemoattractant densities. In particular, these latter properties are essential in detecting numerical blow-up configurations, since the non-satisfaction of these two requirements might trigger numerical oscillations leading to non-realistic finite-time collapses into persistent Dirac-type measures. Our findings show that the existence threshold value 2π encountered for the organism density mass may not be optimal and hence it is conjectured that the critical threshold value 4π may be inherited from the fluid-free Keller–Segel equations. Additionally it is observed that the formation of singular points can be neglected if the fluid flow is intensified.

97 MATHEMATICS AND COMPUTING↗

Zinc oxide (ZnO) hybrid metasurfaces exhibiting broadly tunable topological properties

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

36 MATERIALS SCIENCE↗

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗

Geometric Interpretation of the Cluster Location Problem Part II: Application to the Pahala, Hawaii, Earthquake Sequence

In the companion “Theory” article, we presented a new framing of the seismic location problem in terms of differential geometry (Harris et al., 2025). From that viewpoint, we developed a “project and correct” approach for estimating the relative locations of earthquakes. Here, in this study, we use project and correct to estimate high-precision relative locations of events from an earthquake sequence beneath the town of Pahala, Hawaii, using high-precision correlation-derived picks. The sequence was active from 2020 through 2022 and produced many highly correlated signals at Hawaii Volcano Observatory (HVO) stations on the island of Hawaii. The data we inverted consisted of 2882 events with observations at 5 HVO stations. For comparison with the travel-time image, we also produced conventional hypocenter solutions using both the Bayesloc program (Myers et al., 2007, 2009) and a purpose-built double-difference code. There were obvious structural elements in the resulting image, the resolution of which we used to test the performance of the project and the correct algorithm. For the projection step, we first produced a 3D local basis using an singular value decomposition (SVD) of the 2882 groups of times. Projection of the travel-time vectors into this basis resulted in an image with structures similar to those produced by our conventional locators, but with distortion as predicted by theory. Removing the distortion requires an inverse operator generated from the metric tensor at the geometric centroid of the events. We compared two approaches to obtaining such an inverse operator. The first uses an estimate of the geographic centroid of the event cloud from the centroid of the travel-time data. The second approach uses the centroid of the conventionally produced locations. The first approach produces a corrected image very similar to the conventional results, but with a rotation. The corrected image produced using the conventionally derived centroid is a near-exact match to the conventional locations.

Dodge, Douglas A. [Lawrence Livermore National Lab↗

IDAES-PSE 2.3.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. New Features and Models • New diagnostics toolboxes and examples o Tutorial for using the DiagnosticsToolbox o Methods to identify potential evaluation errors in models o SVDToolbox for performing singular value decomposition analysis on models to identify possible degeneracies and poor scaling o DegeneracyHunter for identifying irreducible degenerate sets in models • Model for solid-liquid separation which takes two inputs (solid and liquid streams) and produces three outlets (solids, liquid entrained with solids and pure liquid) • Example of temperature swing adsorption in models_extra Deprecation Warnings • With the update to Pyomo 6.7.0, the plate heat exchanger model has begun failing tests on some CI platforms. If this is not addressed by the February release, this model may be removed due to failing tests. See #1294. Offers to help identify the cause and fix this issue are welcome. Improvements and bug fixes • Fixed oversight which precluded using Mixer and Separator models when inherent reactions were present in property package • Added reporting methods to the MSContactor model • Minor corrections in some examples where values were being fixed outside of declared variable bounds

DiagnosticsToolbox,IDAES,PSE,Process Systems Engin↗

Beam correction for multi-pass arcs in FFA@CEBAF: status update

This work examines the multi-pass steering of six electron beams in an FFA arc ranging from approximately 10.5 GeV to 22 GeV. Shown here is an algorithm based on singular value decomposition (SVD) to successfully steer all six beams through the arc given precise knowledge of all beam positions at each of one hundred and one diagnostic locations with one hundred individual corrector magnets: that is successive application of SVD to different 100 × 101 response matrices—one for each beam energy. Further, a machine learning scheme is developed which only requires knowledge of the energy-averaged beam position at each location to provide equivalent steering. Extension of this scheme to other beam optics quantities as well as transverse and longitudinal coupling is explored.

Accelerator Physics↗

ORBIT CORRECTION STUDIES ON THE ELECTRON TRANSPORT LINE FROM RCS TO ESR

A dedicated electron transfer line from Rapid Cycling Synchrotron (RCS) to Electron Storage Ring (ESR), referred to as the RTE line has been designed for the Electron-Ion Collider (EIC). The beamline follows a straight-line geometry, with a length of 133 m, and is consists with two matching sections and a FODO section for beam diagnostics. Imperfections with magnet alignments introduce orbit distortions, making orbit correction scheme a critical component in the design. To facilitate orbit correction, each quadrupole magnet is equipped with a pair of beam position monitors (BPMs) and kickers. The Singular Value Decomposition (SVD) algorithm is used for orbit correction and tolerance studies. This paper presents the ongoing progress in the optics design and error correction scheme of the RTE line.

Neththikumara, I. [Thomas Jefferson National Accel↗

Fast tensor disentangling algorithm

Many recent tensor network algorithms apply unitary operators to parts of a tensor network in order to reduce entanglement. However, many of the previously used iterative algorithms to minimize entanglement can be slow. We introduce an approximate, fast, and simple algorithm to optimize disentangling unitary tensors. Our algorithm is asymptotically faster than previous iterative algorithms and often results in a residual entanglement entropy that is within 10 to 40% of the minimum. For certain input tensors, our algorithm returns an optimal solution. When disentangling order-4 tensors with equal bond dimensions, our algorithm achieves an entanglement spectrum where nearly half of the singular values are zero. We further validate our algorithm by showing that it can efficiently disentangle random 1D states of qubits.

Slagle, Kevin↗

String correlators on $\text{AdS}_3$: Analytic structure and dual CFT

We continue our study of string correlators on Euclidean \text{AdS}_3 AdS 3 with pure NS-NS flux. The worldsheet and spacetime correlators have a rich analytic structure, which we analyse completely for genus 0 four-point functions. We show that correlators exhibit a simple behaviour near their singularities. The spacetime correlators are meromorphic functions in the \mathrm{SL}(2,\mathbb{R}) S L ( 2 , ℝ ) -spins, whose pole structure is shown to agree with the prediction of a recent proposal for the dual \text{CFT}_2 CFT 2 . Moreover, we also compute the residues of the spacetime correlators for some of the poles exactly and find again a perfect match with the proposal for the dual \text{CFT}_2 CFT 2 , thereby checking the duality for some non-trivial four-point functions exactly. Our computations simplify drastically in the tensionless limit of \mathrm{AdS}_3 \times \mathrm{S}^3 \times \mathbb{T}^4 A d S 3 × S 3 × 𝕋 4 where the behaviour near the poles gives in fact the exact answer. This paper is the third in a series with several installments.

74 ATOMIC AND MOLECULAR PHYSICS↗