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At least 145 records · Page 8

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DOE OSTI2024

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗

DOE OSTI2020

Learning reference governor for cycle-to-cycle combustion control with misfire avoidance in spark-ignition engines at high exhaust gas recirculation–diluted conditions

Cycle-to-cycle feedback control is employed to achieve optimal combustion phasing while maintaining high levels of exhaust gas recirculation by adjusting the spark advance and the exhaust gas recirculation valve position. The control development is based on a control-oriented model that captures the effects of throttle position, exhaust gas recirculation valve position, and spark timing on the combustion phasing. Under the assumption that in-cylinder pressure information is available, an adaptive extended Kalman filter approach is used to estimate the exhaust gas recirculation rate into the intake manifold based on combustion phasing measurements. The estimation algorithm is adaptive since the cycle-to-cycle combustion variability (output covariance) is not known a priori and changes with operating conditions. A linear quadratic regulator controller is designed to maintain optimal combustion phasing while maximizing exhaust gas recirculation levels during load transients coming from throttle tip-in and tip-out commands from the driver. During throttle tip-outs, however, a combination of a high exhaust gas recirculation rate and an overly advanced spark, product of the dynamic response of the system, generates a sequence of misfire events. In this work, an explicit reference governor is used as an add-on scheme to the closed-loop system in order to avoid the violation of the misfire limit. The reference governor is enhanced with model-free learning which enables it to avoid misfires after a learning phase. Experimental results are reported which illustrate the potential of the proposed control strategy for achieving an optimal combustion process during highly diluted conditions for improving fuel efficiency.

42 ENGINEERING↗

DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, 2023

This dataset includes raw and corrected specific conductivity, temperature, and calculated salinity measurements collected at 10 cm depth in a Typha angustifolia-dominated tidal brackish wetland at the upper estuary of Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site. Measurements were taken to evaluate temporal variation in porewater salinity (a proxy for porewater sulfate concentration) in high frequency to assess soil and plant responses to changes in salinity. Measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger deployed in a well. Specific conductivity was corrected using non-linear temperature compensation, and salinity was calculated using the Practical Salinity Scale 1978 via Onset's HOBOware software. Reference conductivity measurements to correct for sensor drift were taken at the start and end of each deployment using a HACH HQ14D Portable Conductivity Meter. Data were then filtered in MATLAB to remove values logged while the sensor was out of the well or during post-deployment equilibration. Detailed metadata, including variable descriptions, sampling methods, QA/QC procedures, and site information, are provided in the files: Typha_ctd_salinity_dd.csv and Typha_MI_ctd_salinity_2023_flmd.csv.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, May-December 2022

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Plastic work constrained elastoplastic topology optimization

An elastoplastic topology optimization framework for limiting plastic work generation while maximizing stiffness is presented. The kinematics and constitutive model are based on finite strain linear isotropic hardening plasticity, and the balance laws are solved using a total Lagrangian finite element formulation. Aggregation of the specific plastic work combined with an adaptive normalization scheme efficiently constrains the maximum specific plastic work. The optimization problem is regularized using an augmented partial differential equation filter, and is solved by the method of moving asymptotes where path-dependent sensitivities are derived using the adjoint method. The numerical examples show a clear dependence on the optimized maximum stiffness structures for different levels of constrained specific plastic work. It is also shown that due to the history dependency of the plasticity, the load path significantly influences the structural performance and optimized topology.

42 ENGINEERING↗

DOE OSTI2025

Compact Coaxial HOM Damper for SRF Cavities

SRF technology enable particle accelerators operate with greater average beam currents and higher duty cycles. In these regimes parasitic excitation of the cavity HOM spectrum become the limiting factor due to extra RF losses and instabilities appearing in the beam. We discuss the limitations of HOMs for large accelerator projects as the Fermilab MI upgrade and the proposed future circular and linear colliders EIC and ILC. A new compact HOM damper concept is suggested providing required HOM suppression. The idea is based on an oversized coaxial line with radial sections, which is directly connected to the axial region of the SRF cavity. Such radially sectioned coaxial works as a filter for the operating mode, while being transparent for the HOMs. Implementations of this design for the accelerator and crab cavities developed for the MI and EIC machines, respectively, are discussed.

Lunin, A. [Fermilab]↗

DOE OSTI2022

Pseudodiagonalization Method for Accelerating Nonlinear Subspace Diagonalization in Density Functional Theory

In density functional theory, each self-consistent field (SCF) nonlinear step updates the discretized Kohn-Sham orbitals by solving a linear eigenvalue problem. The concept of pseudodiagonalization is to solve this linear eigenvalue problem approximately, and specifically utilizing a method involving a small number of Jacobi rotations that takes advantage of the good initial guess to the solution given by the approximation to the orbitals from the previous SCF iteration. The approximate solution to the linear eigenvalue problem can be very rapid, particularly for those steps near SCF convergence. Here, we adapt pseudodiagonalization to finite-temperature and metallic systems, where partially-occupied orbitals must be individually resolved with some accuracy. We apply pseudodiagonalization to the subspace eigenvalue problem that arises in Chebyshev-filtered subspace iteration. In tests on metallic and other systems for a range of temperatures, we show that pseudodiagonalization achieves similar rates of SCF convergence to exact diagonalization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Differential holography

Differential Holography technology measures the amplitude and/or phase of, e.g., an incident linearly polarized spatially coherent quasi-monochromatic optical field by optically computing the first derivative of the field and linearly mapping it to an irradiance signal detectable by an image sensor. This information recorded on the image sensor is then recovered by a simple algorithm. In some embodiments, an input field is split into two or more beams to independently compute the horizontal and vertical derivatives (using amplitude gradient filters in orthogonal orientations) for detection on one image sensor in separate regions of interest (ROIs) or on multiple image sensors. A third unfiltered beam recorded in a third ROI directly measures amplitude variations in the input field to numerically remove its contribution as noise before recovering the original wavefront using a numerical in algorithm. When combined, the measured amplitude and phase constitute a holographic recording of the incident optical field.

Ravizza, Frank↗

DOE OSTI2026

Toward scalable quantum computations of atomic nuclei

We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitary coupled cluster theory to parametrize the ground states of the deuteron and 3 He, compute their corresponding energies, and analyze the scaling of the required computational resources. Our quantum simulations reproduce exact benchmarks for 2 H and 3 He within 100 keV, requiring at most 30 layers in the ansatz and thus resulting in modest circuit depths. Additionally, we find the number of shots required to reach a given precision scales linearly in the lattice size and more mildly in the system size. Furthermore, based on the agreement with exact benchmarks and mild scaling, we conclude that this can be an efficient, scalable approach for quantum computations of nuclear ground states, particularly to prepare initial states for quantum phase estimation or other filtering algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Evaluation of Time-Series Gap-Filling Methods for Solar Irradiance Applications

A complete solar resource data set is essential for any stage of a solar energy project - from feasibility studies to daily operations. But measured or modeled solar resource data are prone to data gaps and data quality issues. To mitigate these issues, a data imputation process should be implemented to obtain a complete and reliable temporal and spatial data series. This study focused on imputing temporal scales by applying random and artificial data gaps and then implementing eight imputation methods, including the Kalman filtering and smoothing and stine interpolations. These methods were implemented on 1-minute to half hourly irradiance data for 1 year using a few locations from the National Solar Radiation Database (NSRDB) and ground measurement data set. The results demonstrated that some of the simpler methods, such as the stine and linear interpolation methods, were the relatively best models based on the statistical metrics for imputing NSRDB and ground measurement data, respectively.

14 SOLAR ENERGY↗

DOE OSTI2023

Semi-Implicit Computation of Fast Modes in a Scheme Integrating Slow Modes by a Leapfrog Method Based on a Selective Implicit Time Filter

Abstract A scheme for integration of atmospheric equations containing terms with differing time scales is developed. The method employs a filtered leapfrog scheme utilizing a fourth-order implicit time filter with one function evaluation per time step to compute slow-propagating phenomena such as advection and rotation. The terms involving fast-propagating modes are handled implicitly with an unconditionally stable method that permits application of larger time steps and faster computations compared to fully explicit treatment. Implementation using explicit and recurrent formulation is provided. Stability analysis demonstrates that the method is conditionally stable for any combination of frequencies involved in the slow and fast terms as they approach the origin. The implicit filter used in the method damps the computational modes without noticeably sacrificing the accuracy of the physical mode. TheO[(Δt 4 )] accuracy for amplitude errors achieved by the implicitly filtered leapfrog is preserved in applications where terms responsible for fast propagation are integrated with a semi-implicit method. Detailed formulation of the method for soundproof nonhydrostatic anelastic equations is provided. Procedures for implementation in global spectral shallow-water models are also given. Examples comparing numerical and analytical solutions for linear gravity waves demonstrate the accuracy of the scheme. The performance is also shown in more practical nonlinear applications, where numerical solutions accomplished by the method are evaluated against those computed from a scheme where the slow terms are handled by the third-order Runge–Kutta scheme. It demonstrates that the method is able to accurately resolve fine-scale dynamics of Kelvin–Helmholtz shear instabilities, the evolution of density current, and nonlinear drifts of twin tropical cyclones.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Homotopy Solver

This software implements parallel versions of an interior-point solver, based on the publicly available ipopt solver. Here we have full control over the linear solver and our algorithm is fully parallel thus enabling scalability to large-scale optimization problems. This package also has a parallel implementation of a homotopy solver developed under the scalable methods for contact LDRD project 23-ERD-017. This solver is an mfem-based implementation of algorithm described in ``A filter trust-region Newton continuation method for nonlinear complementarity problems''. Cosmin G. Petra, Nai-Yuan Chiang, Jingyi Wang, Tucker Hartland, and Michael Puso (submitted), LLNL-JRNL-869761.

Hartland, Tucker [Lawrence Livermore National Labo↗

DOE OSTI2022

To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects

Abstract Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects. This diffractive camera consists of transmissive surfaces structured using deep learning to perform selective imaging of target classes of objects positioned at its input field-of-view. After their fabrication, the thin diffractive layers collectively perform optical mode filtering to accurately form images of the objects that belong to a target data class or group of classes, while instantaneously erasing objects of the other data classes at the output field-of-view. Using the same framework, we also demonstrate the design of class-specific permutation and class-specific linear transformation cameras, where the objects of a target data class are pixel-wise permuted or linearly transformed following an arbitrarily selected transformation matrix for all-optical class-specific encryption, while the other classes of objects are irreversibly erased from the output image. The success of class-specific diffractive cameras was experimentally demonstrated using terahertz (THz) waves and 3D-printed diffractive layers that selectively imaged only one class of the MNIST handwritten digit dataset, all-optically erasing the other handwritten digits. This diffractive camera design can be scaled to different parts of the electromagnetic spectrum, including, e.g., the visible and infrared wavelengths, to provide transformative opportunities for privacy-preserving digital cameras and task-specific data-efficient imaging.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Multi-User Capacity for Cyclic Prefix Direct Sequence Spread Spectrum with Linear Detection and Precoding

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a promising solution for futuristic 6G ultra-reliable low latency communications (URLLC) and massive machine type communication (mMTC) applications, where the CP-DSSS waveform would operate as a secondary network at the same frequencies as the primary network but at much lower SNR. In this paper, we show per-user capacity for multi-user scenarios, where simple matched filtering (MF) is performed on the uplink (UL) and time-reversal (TR) precoding is used on the downlink (DL). When operating in the low SNR regime, CP-DSSS achieves per-user capacity near the optimum single-user capacity by using a MF detector at the receiver for the UL. TR precoding converges to the optimal capacity as the number of antennas at the hub/gateway increases. Given the near-optimal performance of MF detection and TR precoding for each of the users, CP-DSSS can be implemented with simple device transceiver structures, reducing per-unit cost for massively deployed 6G networks.

5G and Beyond Communications↗

DOE OSTI2024

Machine learning based unfolding of x-ray spectra from filter stack spectrometer data

We demonstrate the application of neural networks to perform x-ray spectra unfolding from data collected by filter stack spectrometers. A filter stack spectrometer consists of a series of filter-detector pairs, where the detectors behind each filter measure the energy deposition through each layer as photo-stimulated luminescence (PSL). The network is trained on synthetic data, assuming x-rays of energies < 1 MeV and of two different distribution functions (Maxwellian and Gaussian) and the corresponding measured PSL values obtained from five different filter stack spectrometer designs. Predicted unfolds of single distributions are near identical reproductions of the ground truth spectra, with differences in the values lower than 20% at the higher energy end in some cases. The neural network has also demonstrated robustness to experimental measurement errors of < 5% and some capability of performing unfolds for linear combinations of the two distributions without previous training. The network can perform unfolds at rates > 1 Hz, ideal for application to some high-repetition-rate systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Analysis of Needlet Internal Linear Combination performance on B -mode data from sub-orbital experiments

The observation of primordial B modes in cosmic microwave background (CMB) polarisation data represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky, pointing to the need for effective component separation methods. Aims. Among all the techniques, the blind Needlet Internal Linear Combination (NILC) is of great relevance given our current limited knowledge of the B-mode foregrounds. In this work, we explore the possibility of employing NILC for the analysis of B modes reconstructed from partial-sky data, specifically addressing the complications that such an application yields such as E–B leakage, needlet filtering, and beam convolution. We consider two complementary simulated datasets of future experiments: the balloon-borne Short Wavelength Instrument for the Polarisation Explorer (SWIPE) of the Large Scale Polarisation Explorer, which targets the observation of both reionisation and recombination peaks of the primordial CMB B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which, instead, is designed to observe only the recombination bump at ℓ ~ 80. We assessed the performance of the following two alternative techniques to correct for the CMB E–B leakage: the recycling technique and the Zhao-Baskaran method. We find that both techniques reduce the E–B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE footprint at ℓ < 20. Thus, we implemented two extensions of the pipeline, the iterative B decomposition and the diffusive inpainting, which enabled us to recover the input CMB B-mode power for ℓ ≥ 5. For the considered experiments, we demonstrate that needlet filtering and beam convolution do not affect the CMB B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows one to achieve sensitivities on the tensor-to-scalar ratio in agreement with the targets of the considered CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

The FRIB Decay Station: New Horizons with Rare Isotopes

In May 2022, the Facility for Rare Isotope Beams (FRIB), located on the campus of Michigan State University (MSU), began delivering exotic isotopes to an international community of scientists. New discoveries are now being reported from radioactive decay of neutron-rich nuclei near N = 20 and N = 28.FRIB is expected to produce roughly 80% of the unstable or radioactive isotopes predicted to exist up to uranium (Z = 92). The new user facility is supported by the U.S. Department of Energy, and it is operated by MSU. A high-power superconducting linear accelerator, shaped like a paper-clip, drives the production of these rare isotopes by colliding stable nuclei moving at half the speed of light with a rotating, water-cooled graphite tar-get. These collisions cause the primary stable beam to fragment into a wide variety of unstable nuclei, which can be subsequently filtered through a multistage magnetic separator, the Advanced Rare Isotope Separator, and transported to one of several experimental stations. The FRIB Decay Station initiator (FDSi) (see Figure 1) was developed to enable comprehensive radio-active decay studies of the exotic nuclei produced by FRIB and it was used in the first two experiments in 2022. Further, the FDSi is a highly reconfigurable multidetector system with two focal planes (FP1 for discrete spectroscopy and FP2 for total absorption spectroscopy) that can be optimized for the specific science goals of each experiment. It is designed, built, and operated by a community of users with the sup-port of U.S. funding agencies, including the Department of Energy and National Science Foundation.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2021

Estimating and Forecasting Time-Varying Groundwater Recharge in Fractured Rock: A State-Space Formulation with Preferential and Diffuse Flow to the Water Table

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

groundwater, Recharge, infiltration, recursive est↗