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DOE OSTI2023

Biophotonic rogue waves in red blood cell suspensions

Rogue waves are ubiquitous in nature, appearing in a variety of physical systems ranging from acoustics, microwave cavities, optical fibers, and resonators to plasmas, superfluids, and Bose–Einstein condensates. Unlike nonlinear solitary waves, rogue waves are extreme events that can occur even without nonlinearity by, for example, spontaneous synchronization of waves with different spatial frequencies in a linear system. Here, we report the observation of rogue-wave-like events in human red blood cell (RBC) suspensions under weak light illumination, characterized by an abnormal L-shaped probability distribution. Such biophotonic extreme events arise mostly due to the constructive interference of Mie-scattered waves from the suspended RBCs, whose biconcave shape and mutable orientation give rise to a time-dependent random phase modulation to an incident laser beam. We numerically simulate the beam propagation through the colloidal suspensions with added disorder in both spatial and temporal domains to mimic random scattering due to Brownian motion. In addition, at high power levels, nonlinear beam self-focusing is also observed, leading to a dual-exponential probability distribution associated with the formation of multiple soliton-like spots. Such rogue wave events should also exist in environments with cells of other species such as swimming bacteria, and understanding of their underlying physics may lead to unexpected biophotonic applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods.

14 SOLAR ENERGY↗

DOE OSTI2021

Timing Intrusion Management Ensuring Resiliency (TIMER)

This document is created as the deliverable on the project titled Timing Intrusion Management Ensuring Resiliency (TIMER). Its purpose is to define Specification Requirements that guide the development of various timing intrusion (TI) detection modules, as well as describe their implementation, validation, and future commercialization.

42 ENGINEERING↗

DOE OSTI2023

Assessing Several Modeling Approaches in Depletion Studies of a TRISO-Fueled Microreactor

The impact of MCNP6 depletion resolution on core lifetime is examined in the context of the Snowflake microreactor with explicit TRISO fuel. The change in core lifetime and isotope mass as a result of different tracked isotopes, timesteps, and spatial regions is discussed. Calculation speed of a prototype MCNP delta tracking module is compared to a reactivity equivalent physical transformation (RPT). Using a single depletion material underpredicts core lifetime by 15%, and the resolution necessary to converge isotope mass greatly depends on the specific isotope, in addition to the size (and location) of the depletion region. The prototype delta tracking module decreases the CPU time of explicit TRISO criticality calculations by 30%, but does not always result in a speedup when used with depletion. Significant depletion speedup is obtained using RPT (50% faster), and all isotope masses agreed within three percent.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Exploring the Nature of Neutrinos with the Deep Underground Neutrino Experiment (DUNE)

The Deep Underground Neutrino Experiment (DUNE) is a next-generation experimental program designed to study the behaviour of neutrino oscillation. DUNE will utilize a neutrino beam originating at Fermilab, near Chicago, and will leverage a detector at Fermilab (Near Detector) and a detector 1300 km away in South Dakota (Far Detector), south of Saskatchewan. In the first phase of DUNE, its Far Detector will comprise of two 10,000 ton (fiducial) liquid argon (LAr) time-projection chamber (TPC) modules – powerful tracking calorimeter detectors – placed nearly a mile underground. With this large, sensitive, underground detector, DUNE aims to collect a high statistics and pure sample of neutrinos at the Far Detector. This setup also offers the potential to study non-beam physical processes via e.g. neutrinos produced in the atmosphere, supernova neutrino bursts, and/or solar neutrinos, etc. A second phase will aim to add more detector mass and expand the program. The Near Detector will consist of a LAr TPC module as well: critical to constraining systematic uncertainties in the oscillation analysis. However, this LAr TPC will have a novel design using a pixel-based readout instead of the traditional wire-based readout. This and the segmentation of the LAr TPC into multiple units are crucial in mitigating the high multiplicity of neutrino interactions expected in any readout window given its proximity to the beam. The Near Detector will feature additional components and capability beyond the LAr TPC, allowing one to deeply characterize the neutrino flux. Due to the complexity of this experimental program, several smaller-scale prototype detectors have been operating to test, validate, and improve both the technical designs and software for processing and analyzing events. By operating in charged particle test beams or neutrino beams, several of the prototypes are also capable of producing valuable results. Canadian institutions are involved in the realization of the DUNE through efforts with both the Near and Far Detectors and prototypes. DUNE is anticipated to begin operating near the end of this decade/the beginning of the next. This talk will focus on the overall DUNE program, for example its ultimate plans, status, and the efforts with prototypes.

Howard, Bruce [York U., Canada; Fermilab]↗

DOE OSTI2020

LID and LeTID Impacts to PV Module Performance and System Economics: Draft Analysis

This webinar is a technical review of the measurements and causes of BO LID, UV LID and LeTID, as well as modeling their impacts to PV project financial metrics. We will first review how Boron-Oxygen complexes form and detail the range of impacts to PV module power ratings over time and across climates. Similarly, we will also discuss the measurements and extent of UV LID over time and across climates. Then, we will demonstrate a methodology for translating these effects to pro forma cash flow models and their impacts to PV project financial returns and levelized cost of electricity (LCOE). We will conclude with estimates of the value of solutions to these degradation mechanisms.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Recent Hydrodynamic Modeling Enhancements in OpenFAST: Preprint

To improve the hydrodynamic modeling capabilities of the offshore wind design and modeling tool OpenFAST, a restructuring of the HydroDyn hydrodynamics module was undertaken with several new features implemented. The generation of the wave field is now separated from HydroDyn into a new module called SeaState. Unlike previous versions of HydroDyn, which precomputed the wave kinematics at the undisplaced positions of the hydrodynamic nodes, the new SeaState module computes the complete time history of the wave field at the vertices of a user-defined wave grid. During the simulation, the wave kinematics at any point within the grid can be efficiently interpolated, allowing the strip-theory wave loads to be evaluated based on the wave kinematics at the displaced structure position. A phase correction was also implemented for the potential-flow wave-exciting loads to account for large structure displacements. Several wave-stretching methods were implemented for the strip-theory solution along with a wave-load redistribution method that ensures smooth variation of the nodal loads as the nodes of a discrete hydrodynamic mesh enter and exit the water. The load smoothing is included to avoid the excitation of unphysical high-frequency structural vibration during hydroelastic simulations. The MacCamy-Fuchs diffraction correction for the strip-theory solution and the capability to insert a constrained NewWave into extreme stochastic sea states with directional spreading were also added. The present article documents the formulations of the new improvements to HydroDyn with example applications and numerical results.

constrained wave↗

DOE OSTI2020

Activation Energy for Solder Bond Degradation: Thermal Cycling of Field-aged Modules at Multiple Upper Temperatures

The reliability of solder joints in the solar cell metallization-interconnect system influences the lifetime of photovoltaic modules. Two field-aged modules-one with Sn 62 Pb 36 Ag 2 solder at the solder joints (Solarex MSX 60), and the other with the standard Sn 60 Pb 40 solder (Siemens M55)-were subjected to a modified thermal cycling (TC) test of IEC 61215. Three sections in each module were maintained at 85 degrees C, 95 degrees C, and 105 degrees C during the 15-minute high temperature dwell time. Current equivalent to the module short-circuit current was injected through the module when the chamber temperature was above 25 degrees C to simulate regular field operation. This novel approach aims to induce thermomechanical fatigue (TMF) at the solder joints and intermetallic compound (IMC) formation at the metal/solder interfaces. The activation energy (E a ) for solder bond degradation was calculated based on the series resistance (R s ) increase in TC testing rather than power drop to avoid the effect of confounding variables. Module-level R s increase in MSX 60 module after TC800 cycles and in M55 module after TC400 cycles was 1.22% and 183.7%, respectively. The E a determined for the module with 2wt% Ag is 0.24 eV and for that with the standard solder is 0.27 eV. The solder bond degradation seems to have been driven by TMF rather than IMC formation for both modules.

14 SOLAR ENERGY↗

DOE OSTI2022

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders

The anomalies in the high voltage converter modulator (HVCM) remain a major down time for the spallation neutron source facility, that delivers the most intense neutron beam in the world for scientific materials research. In this work, we propose neural network architectures based on Recurrent AutoEncoders (RAE) to detect anomalies ahead of time in the power signals coming from the HVCM. Bi-directional gated recurrent unit, bi-directional long-short term memory (LSTM), and convolutional LSTM (ConvLSTM) are developed, trained, and tested using real experimental signals from the HVCM module. The results show a good performance of the proposed RAE models, achieving precision up to 91%, recall up to 88%, false omission rate as low as 20% (i.e. 80% of the anomalies were detected), and area under the ROC curve up to 0.9. The three RAE models provide very comparable performance, with LSTM showing slightly better performance than GRU and ConvLSTM. The RAE models are benchmarked against other anomaly detection methods, including isolation forest, support vector machine, local outlier factor, feedforward and convolutional autoencoders, and others; showing a better performance. Here, the results of this study demonstrate the promising potential of RAE in anomaly detection for real-world power systems, and for increasing the reliability of the HVCM modules in the spallation neutron source.

42 ENGINEERING↗

DOE OSTI2020

Spectral Variability of VHS J1256–1257b from 1 to 5 μm

Multiwavelength time-resolved observations of rotationally modulated variability from brown dwarfs and giant exoplanets are the most effective method for constraining their heterogeneous atmospheric structures. In a companion paper, we reported the discovery of strong near-infrared variability in HST/WFC3/G141 light curves of the very red L-dwarf companion VHS J1256–1257b. In this paper, we present a follow-up 36 hr Spitzer/IRAC Channel 2 light curve together with an in-depth analysis of the Hubble space telescope (HST) and the Spitzer data. The combined data set provides time-resolved light curves of VHS1256b sampling 1.1 to 4.5 μm. The Spitzer light curve is best fit with a single sine wave with a period of 22.04 ± 0.05 hr and a peak-to-peak amplitude of 5.76 ± 0.04%. Combining the period with a previously measured projected rotational velocity (v sin i), we find that VHS1256b is most consistent with equatorial viewing geometry. The HST/G141+Spitzer spectral energy distribution favors a model with a T{sub eff} of 1000 K and low surface gravity with disequilibrium chemistry. The spectral variability of VHS1256b is consistent with predictions from partly cloudy models, suggesting that heterogeneous clouds are the dominant source of the observed modulations. We find evidence at the 3.3σ level for amplitude variations within the 1.67 μm CH{sub 4} band, which is the first such detection for a variable L-dwarf. We compare the HST/G141 time-resolved spectra of three red L-dwarfs with high-amplitude near-infrared rotational modulations and find that although their time-averaged spectra are similar, their spectroscopic variabilities exhibit notable differences. This diversity reinforces the advantage of time-resolved spectroscopic observations for understanding the atmospheres of brown dwarfs and directly imaged exoplanets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Viscoelastic Material Characterization and Modeling of Photovoltaic Module Packaging Materials for Direct Finite-Element Method Input

Numerical tools, such as the finite-element method, are increasingly used to design and evaluate the photovoltaic (PV) modules, providing for the reduction of development time and improved performance and reliability. However, high-fidelity material models are necessary to accurately model the complex structural behavior of the involved packaging materials. A common simplification used in recent years is to model the polymer materials (i.e., encapsulant and backsheet) as linear elastic, which will lead to inaccurate results. Therefore, in this work, we present a thorough characterization of the time- and temperature-dependent mechanical response of predominant PV module encapsulant and backsheet materials. Based on this material characterization, we developed and experimentally validated generalized Maxwell models to describe each material's viscoelastic response. In addition, we included measurements of the coefficient of thermal expansion and presented all material models in such a fashion for direct input into commercial finite-element method modeling software.

FEM↗

DOE OSTI2023

Scintillation light detection performance for the DUNE ND-LAr 2 × 2 modules

The Deep Underground Neutrino Experiment (DUNE) will be using a liquid argon time projection chamber (LAr TPC) with optically separated modules in the Near Detector (ND) complex. A prototype experiment, DUNE ND-LAr 2 × 2, is composed of four test modules. They detect ionization charge through a pixel-based readout and scintillation light through fibers in light collection modules and light traps called ArCLights. The light detection performance for two modules of DUNE ND-LAr 2 × 2 that took cosmic ray data at the University of Bern is shown. We present further the role of the 2 × 2 prototype in DUNE and how it is used to demonstrate the reconstruction capabilities of its light detectors in terms of energy thresholds and timing resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Scintillation light detection performance for the DUNE ND-LAr 2 × 2 modules

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Constraining the Charge-Sign and Rigidity-Dependence of Solar Modulation

Our ability to identify the sources of cosmic rays and understand how these particles propagate through the interstellar medium is hindered by the combined effects of the solar wind and its embedded magnetic field, collectively known as solar modulation. In this paper, we build upon our previous work to model and constrain the effects of solar modulation on the cosmic-ray spectrum, using data from AMS-02 and BESS Polar II collected between 2007 and 2012, during which the heliospheric magnetic field was in a state of negative polarity. Our model uses measurements of the heliospheric magnetic field and the tilt angle of the heliospheric current sheet to accurately predict the effects of solar modulation as a function of time, charge, and rigidity. By incorporating data from a period of negative polarity, we have been able to robustly observe and constrain the charge-dependent effects of solar modulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Spherical time-encoded radiation imaging simulations

Radiation source localization is important for nuclear nonproliferation and can be obtained using time-encoded imaging systems with unsegmented detectors. A scintillation crystal can be used with a moving coded-aperture mask to vary the detected count rate produced from radiation sources in the far field. The modulation of observed counts over time can be used to reconstruct an image with the known coded-aperture mask pattern. Current time-encoded imaging systems incorporate cylindrical coded-aperture masks and have limits to their fully coded imaging field-of-view. This work focuses on expanding the field-of-view to 4π by using a novel spherical coded-aperture mask. A regular icosahedron is used to approximate a spherical mask. This icosahedron consists of 20 equilateral triangles; the faces of which are each subdivided into four equilateral triangle-shaped voxels which are then projected onto a spherical surface, creating an 80-voxel coded-aperture mask. Furthermore, these polygonal voxels can be made from high-Z materials for gamma-ray modulation and/or low-Z materials for neutron modulation. In this work, we present Monte Carlo N-Particle (MCNP) simulations and simple models programmed in Mathematica to explore image reconstruction capabilities of this 80-voxel coded-aperture mask.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

DOE OSTI2025

Entanglement swapping systems toward a quantum internet

We demonstrate conditional entanglement swapping, i.e. teleportation of entanglement, between time-bin qubits at the telecommunication wavelength of 1536.4 nm with high fidelity of 87%. Our system is deployable, utilizing modular, off-the-shelf, fiber-coupled, and electrically controlled components such as electro-optic modulators. It leverages the precise timing resolution of superconducting nanowire detectors, which are controlled and read out via a custom developed graphical user interface. The swapping process is described, interpreted, and guided using characteristic function-based analytical modeling that accounts for realistic imperfections. Our system supports quantum networking protocols, including source-independent quantum key distribution, with an estimated secret key rate of approximately 0.5 bits per sifted bit.

Davis, Samantha I. [Caltech] (ORCID:00000001999481↗

DOE OSTI2025

QCD moat regime and its real-time properties

Dense quantum chromodynamics (QCD) matter may exhibit crystalline phases. Their existence is reflected in a moat regime, where mesonic correlations feature spatial modulations. We study the real-time properties of pions at finite temperature and density in QCD in order to elucidate the nature of this regime. We show that the moat regime arises from particle-hole-like fluctuations near the Fermi surface. This gives rise to a characteristic peak in the spectral function of the pion at nonzero spacelike momentum. This peak can be interpreted as a new quasi particle, the moaton. In addition, our framework also allows us to directly test the stability of the homogeneous chiral phase against the formation of an inhomogeneous condensate in QCD. We find that an inhomogeneous instability is highly unlikely for baryon chemical potentials μ B ≤ 630 MeV . Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗