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At least 991 records · Page 55

Preliminary Evaluation of Cesium Distribution for Wet Sieving Process Planned for Soil Decontamination in Japan - 13104

For the purpose of decontaminating radioactive cesium from a huge amount of soil, which has been estimated to be 1.2x10{sup 8} m{sup 3} by excavating to a 5-cm depth from the surface of Fukushima Prefecture where a severe nuclear accident occurred at TEPCO's power generating site and has emitted a significant amount of radioactive materials, mainly radioactive cesium, a wet sieving process was selected as one of effective methods available in Japan. Some private companies have demonstrated this process for soil treatment in the Fukushima area by testing at their plants. The results were very promising, and a full-fledged application is expected to follow. In the present study, we spiked several aqueous samples containing soil collected from an industrial wet sieving plant located near our university for the recycling of construction wastes with non-radioactive cesium hydroxide. The present study provides scientific data concerning the effectiveness in volume reduction of the contaminated soil by a wet sieving process as well as the cesium distribution between the liquid phase and clay minerals for each sub-process of the full-scale one, but a simulating plant equipped with a process of coagulating sedimentation and operational safety fundamentals for the plant. Especially for the latter aspect, the study showed that clay minerals of submicron size strongly bind a high content of cesium, which was only slightly removed by coagulation with natural sedimentation (1 G) nor centrifugal sedimentation (3,700 G) and some of the cesium may be transferred to the effluent or recycled water. By applying ultracentrifugation (257,000 G), most of submicron clay minerals containing cesium was removed, and the cesium amount which might be transferred to the effluent or recycled water, could be reduced to less than 2.3 % of the original design by the addition of a cesium barrier consisting of ultracentrifugation or a hollow fiber membrane. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Monte Carlo Glauber wounded nucleon model with meson cloud

We study the effect of the nucleon meson cloud on predictions of the Monte Carlo Glauber wounded nucleon model for AA, pA, and pp collisions. From the analysis of the data on the charged multiplicity density in AA collisions we find that the meson–baryon Fock component reduces the required fraction of binary collisions by a factor of ~2 for Au + Au collisions at √s = 0.2 TeV and ~1.5 for Pb + Pb collisions at √s = 2.76 TeV. For central AA collisions, the meson cloud can increase the multiplicity density by ~16–18%. We give predictions for the midrapidity charged multiplicity density in Pb + Pb collisions at √s = 5.02 TeV for the future LHC run 2. We find that the meson cloud has a weak effect on the centrality dependence of the ellipticity ϵ{sub 2} in AA collisions. For collisions of the deformed uranium nuclei at √s = 0.2 TeV, we find that the meson cloud may improve somewhat agreement with the data on the dependence of the elliptic flow on the charged multiplicity for very small centralities defined via the ZDCs signals. We find that the meson cloud may lead to a noticeable reduction of ϵ{sub 2} and the size of the fireball in pA and pp collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Discordant Clinical and Microbiological Outcomes Are Associated With Late Clinical Relapse in Clinical Trials for Complicated Urinary Tract Infections

Abstract Background Current US Food and Drug Administration guidance recommends that the primary endpoint for complicated urinary tract infection clinical trials be a composite of the clinical and microbiological responses, assessed at a fixed point after therapy. Although some participants meet the criteria for clinical success, they do not meet the criteria for microbiological eradication and are classified as treatment failures. These discordant outcomes have raised questions about the utility of the microbiological endpoint. Methods We analyzed participant data from 13 phase 3 clinical trials submitted to the US Food and Drug Administration (N = 4842). Outcomes were determined at the test of cure (TOC) visit, recommended to occur at least 5 days after therapy and at the late follow-up visit, recommended to occur 21 to 28 days after randomization. Clinical and microbiological success were defined as the resolution of complicated urinary tract infection symptoms present at study entry, with no new symptoms (clinical cure), and a reduction in density of the original pathogen to <103 CFU/mL on urine culture (microbiological eradication). Results Among included participants, 70.7% were concordant successes at the TOC visit, 18.0% were discordant failures (clinical cure/microbiological persistence), and 6.7% were concordant failures (clinical failure/microbiological persistence). Discordant participants were at an increased risk for clinical failure at the late follow-up visit, and the risk of late clinical failure increased with time. Conclusions Discordant clinical and microbiological outcomes at the TOC visit were associated with an increased risk of late clinical failure. Microbiological outcomes appear to be an important component of the endpoint.

Immunology↗

Pressio

Reduced-order Models (ROMs). ROMs are "compressed" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M

Blonigan, Patrick↗

Pressio v.1.0

Reduced-order Models (ROMs). ROMs are "compressed" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M

Blonigan, Patrick↗

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Biochemistry & Molecular Biology↗

Area 2. Use Of Engineered Nanoparticle-Stabilized CO 2 Foams To Improve Volumetric Sweep Of CO 2 EOR Processes

The goal of this project was to develop a new CO 2 injection enhanced oil recovery (CO 2 -EOR) process using engineered nanoparticles with optimized surface coatings that has better volumetric sweep efficiency and a wider application range than conventional CO 2 -EOR processes. The main objectives of this project were to (1) identify the characteristics of the optimal nanoparticles that generate extremely stable CO 2 foams in situ in reservoir regions without oil; (2) develop a novel method of mobility control using “self-guiding” foams with smart nanoparticles; and (3) extend the applicability of the new method to reservoirs having a wide range of salinity, temperatures, and heterogeneity. Concurrent with our experimental effort to understand the foam generation and transport processes and foam-induced mobility reduction, we also developed mathematical models to explain the underlying processes and mechanisms that govern the fate of nanoparticle-stabilized CO 2 foams in porous media and applied these models to (1) simulate the results of foam generation and transport experiments conducted in beadpack and sandstone core systems, (2) analyze CO 2 injection data received from a field operator, and (3) aid with the design of a foam injection pilot test. Our simulator is applicable to near-injection well field-scale foam injection problems and accounts for the effects due to layered heterogeneity in permeability field, foam stabilizing agents effects, oil presence, and shear-thinning on the generation and transport of nanoparticle-stabilized C/W foams. This report presents the details of our experimental and numerical modeling work and outlines the highlights of our findings.

54 ENVIRONMENTAL SCIENCES↗

Blockchain for Fault-Tolerant Grid Operations Version 2.0

This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Implementation of spot scanning dose optimization and dose calculation for helium ions in Hyperion

Purpose: Helium ions ({sup 4}He) may supplement current particle beam therapy strategies as they possess advantages in physical dose distribution over protons. To assess potential clinical advantages, a dose calculation module accounting for relative biological effectiveness (RBE) was developed and integrated into the treatment planning system Hyperion. Methods: Current knowledge on RBE of {sup 4}He together with linear energy transfer considerations motivated an empirical depth-dependent “zonal” RBE model. In the plateau region, a RBE of 1.0 was assumed, followed by an increasing RBE up to 2.8 at the Bragg-peak region, which was then kept constant over the fragmentation tail. To account for a variable proton RBE, the same model concept was also applied to protons with a maximum RBE of 1.6. Both RBE models were added to a previously developed pencil beam algorithm for physical dose calculation and included into the treatment planning system Hyperion. The implementation was validated against Monte Carlo simulations within a water phantom using γ-index evaluation. The potential benefits of {sup 4}He based treatment plans were explored in a preliminary treatment planning comparison (against protons) for four treatment sites, i.e., a prostate, a base-of-skull, a pediatric, and a head-and-neck tumor case. Separate treatment plans taking into account physical dose calculation only or using biological modeling were created for protons and {sup 4}He. Results: Comparison of Monte Carlo and Hyperion calculated doses resulted in a γ{sub mean} of 0.3, with 3.4% of the values above 1 and γ{sub 1%} of 1.5 and better. Treatment plan evaluation showed comparable planning target volume coverage for both particles, with slightly increased coverage for {sup 4}He. Organ at risk (OAR) doses were generally reduced using {sup 4}He, some by more than to 30%. Improvements of {sup 4}He over protons were more pronounced for treatment plans taking biological effects into account. All OAR doses were within tolerances specified in the QUANTEC report. Conclusions: The biological {sup 4}He model proposed above is a first approach matching biological data published so far. The advantage of {sup 4}He seems to lie in the reduction of dose to surrounding tissue and to OARs. Nevertheless, additional biological experiments and treatment planning studies with larger patient numbers and more tumor indications are necessary to study the possible benefits of helium ion beam therapy in detail.

60 APPLIED LIFE SCIENCES↗

Bridging confined phase behavior of CH 4 -CO 2 binary systems across scales

Phase behavior of confined fluids may deviate significantly from that of the bulk fluid due to the fluid-wall interactions being a significant portion of all intermolecular interactions under confinement. Despite recent advancements in understanding confined phase behavior of pure fluids, confined phase behavior of mixtures remains an understudied topic. In this work, we examine the confined phase behavior of a CH 4 -CO 2 binary system by combining Monte Carlo (MC) simulations, a cubic equation of state (EoS), and the lattice Boltzmann method (LBM). First, the effects of confinement on density and phase distribution in nano-size pores are established using Gibbs Ensemble MC calculations, which produce precise results of liquid and vapor confined pressures and account for the modification of the phase change location. By comparing the phase envelopes of bulk and confined mixtures at a fixed temperature, here it is observed that the phase envelopes shrink with reductions in pore size. Based on this observation, we extend a modified Peng-Robinson EoS, which was originally developed for pure fluids under confinement, to mixtures via van-der-Waals-type mixing rules and by accounting for shifts in the critical properties of confined CH 4 -CO 2 . The resulting phase envelopes are in good agreement with the MC data. In addition, a local density model is used in combination with the confined EoS to calculate adsorption isotherms of CH 4 -CO 2 mixtures and to characterize the behavior of confined matter in nanopores. Finally, we incorporate this EoS in a multicomponent multiphase LBM that uses a pseudopotential model to represent intermolecular forces. This workflow utilizes multiscale simulation techniques to bridge the behavior of multicomponent systems across scales and to shed light on the confined phase behavior of CH 4 -CO 2 binary systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers

High–dimensional datasets are becoming ubiquitous in many applications and therefore unsupervised tensor methods to interrogate them are needed. Here, we report a new unsupervised machine learning (ML) approach (NTFk) based on nonnegative tensor factorization integrated with a custom k–means clustering. We demonstrate the ability of NTFk to extracting temporal and spatial features of phase separation of copolymers as they are modeled by self–consistent field theory. Microphase separation of block copolymers has been extensively studied both experimentally and theoretically. However, the interpretation of computer simulations and/or experimental data, representing temporal and spatial changes of molecular species concentration is still a challenging task. Thus, extracting the phase diagram from simulations or experimental data as well as the interpretation of data requires discernment of the model/experimental parameters (such as, temperature, concentrations, the number of molecular species and the interaction between species) impact on the microphase separation process. An attractive and unique aspect of the introduced ML method is that it ensures the nonnegativity of the extracted latent features. Nonnegativity is an essential constraint needed to obtain interpretable and sparse latent features that are parts–based representation of the data. The custom clustering in NTFk serves to estimate the number of latent features in the data.

97 MATHEMATICS AND COMPUTING↗

A Comparative Evaluation of Normal Tissue Doses for Patients Receiving Radiation Therapy for Hodgkin Lymphoma on the Childhood Cancer Survivor Study and Recent Children's Oncology Group Trials

Purpose: Survivors of pediatric Hodgkin lymphoma (HL) are recognized to have an increased risk of delayed adverse health outcomes related to radiation therapy (RT). However, the necessary latency required to observe these late effects means that the estimated risks apply to outdated treatments. We sought to compare the normal tissue dose received by children treated for HL and enrolled in the Childhood Cancer Survivor Study (CCSS) (diagnosed 1970-1986) with that of patients treated in recent Children's Oncology Group (COG) trials (enrolled 2002-2012). Methods and Materials: RT planning data were obtained for 50 HL survivors randomly sampled from the CCSS cohort and applied to computed tomography planning data sets to reconstruct the normal tissue dosimetry. For comparison, the normal tissue dosimetry data were obtained for all 191 patients with full computed tomography–based volumetric RT planning on COG protocols AHOD0031 and AHOD0831. Results: For early-stage patients, the mean female breast dose in the COG patients was on average 83.5% lower than that for CCSS patients, with an absolute reduction of 15.5 Gy. For advanced-stage patients, the mean breast dose was decreased on average by 70% (11.6 Gy average absolute dose reduction). The mean heart dose decreased on average by 22.9 Gy (68.6%) and 17.6 Gy (56.8%) for early- and advanced-stage patients, respectively. All dose comparisons for breast, heart, lung, and thyroid were significantly lower for patients in the COG trials than for the CCSS participants. Reductions in the prescribed dose were a major contributor to these dose reductions. Conclusions: These are the first data quantifying the significant reduction in the normal tissue dose using actual, rather than hypothetical, treatment plans for children with HL. These findings provide useful information when counseling families regarding the risks of contemporary RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Building intermixed donor–acceptor architectures for water-processable organic photovoltaics

A modified synthesis method for aqueous nanoparticle printing inks, based upon vacuum-assisted solvent removal, is reported. Poly(3-hexylthiophene):phenyl C 61 butyric acid methyl ester nanoparticle inks were prepared via this modified miniemulsion method, leading to both an improvement in photoactive layer morphology and a substantial reduction in the ink fabrication time. A combination of UV-visible spectroscopy, photoluminescence spectroscopy and scanning transmission X-ray microscopy measurements revealed a nanoparticle morphology comprising highly intermixed donor–acceptor domains. Consistent with these measurements, dynamic mechanical thermal analysis of the nanoparticles showed a glass transition temperature (T g ) of 104 °C, rather than a pure polymer phase or pure fullerene phase T g . Together the spectroscopy, microscopy and thermomechanical data indicate that rapid solvent removal generates a more blended nanoparticle morphology. As such, this study highlights a new experimental lever for optimising nanostructure in the photoactive layer of nanoparticulate organic photovoltaic devices by enabling highly intermixed donor–acceptor architectures to be built from customised nanoparticulate inks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emission line predictions for mock galaxy catalogues: a new differentiable and empirical mapping from DESI

ABSTRACT We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii], and [O iii]) from a galaxy’s rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman’s rank correlation coefficient ρs > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo-z’s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

ISRM Suggested Method: Determining Deformation and Failure Characteristics of Rocks Subjected to True Triaxial Compression

The purpose of this ISRM Suggested Method is to introduce a guideline on determining deformation and failure characteristics of rocks subjected to true triaxial compression on different stress path. Here, the true triaxial testing apparatus was reviewed by means of the function and engineering application. Some key techniques, such as stress and strain measurements, and reduction of end effect between specimen and metal platens, preventing metal platens interference, were stated and suggested in detail. Methodology of specimen processing, specimen shape, and testing procedure are characterized. There is an explanation of the experimental data processing on stress–strain curves, strength, and fracture mode.

42 ENGINEERING↗

Parameterizing the Variability and Uncertainty of Wind and Solar in CEMs

We present current and improved methods for estimating the capacity value and curtailment impacts from variable generation (VG) in capacity expansion models (CEMs). The ideal calculation of these variability metrics is through an explicit co-optimized investment-dispatch model using multiple years of VG and load data. Because of data and computational limitations, existing CEMs typically approximate these metrics using a subset of all hours from a single year and/or using statistical methods, which often do not capture the tail-event impacts or the broader set of interactions between VG, storage, and conventional generators. In our proposed new methods, we use hourly generation and load values across all hours of the year to characterize the (1) contribution of VG to system capacity during high load hours, (2) the curtailment level of VG, and (3) the reduction in VG curtailment due to storage and shutdown of select thermal generators. Using CEM model outputs from a preceding model solve period, we apply these methods to exogenously calculate capacity value and curtailment metrics for the subsequent model solve period. Preliminary results suggest that these hourly methods offer improved capacity value and curtailment representations of VG in the CEM from existing approximation methods without additional computational burdens.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

U.S. Offshore Wind Energy Noise Reduction Associated with Installation of Fixed-Bottom Foundations: Workshop Report

As offshore wind energy development grows in the United States, solutions are needed to reduce the underwater noise and substrate vibration generated during fixed-bottom turbine installation to help protect marine life. Monopiles are currently the main turbine foundation type installed globally and impact pile driving, the primary installation method, can be a major source of noise and vibration generation during wind farm construction. Opportunities exist to reduce the amount of noise and vibration produced during future offshore wind farm development. The use of alternative foundation types and installation methods, as well as innovative noise abatement technologies, would help reduce the potential detrimental effects on sensitive marine species. To explore these opportunities, the Department of Energy’s Wind Energy Technologies Office, in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, funded the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory to organize, host, and facilitate a virtual workshop in December 2022. The goal of the workshop was to gather input from the offshore wind energy community on noise reduction strategies for the installation of fixed-bottom offshore wind turbines in U.S. waters across multiple regions, including the U.S. Atlantic Coast, Gulf of Mexico, and Great Lakes to inform recommendations on future research. The joint lab team convened industry representatives, subject matter experts, and regulators to discuss potential pathways to reduce noise and vibration associated with fixed-bottom turbine installation, including the practicality of using alternative foundations and installation methods, the effectiveness of noise abatement technologies, as well as research and monitoring needs. In preparation for the workshop, the team invited experts to be part of a steering committee and worked with its members to help focus activities to meet the workshop goals. Additional pre-workshop activities included developing the invitee list and workshop agenda, reviewing existing Construction and Operations Plans (COP) for proposed offshore wind projects, distributing a brief questionnaire to industry representatives, and drafting the workshop discussion questions and Mural boards. In total, 128 workshop participants provided over 600 comments in response to the 17 group discussion questions used over two workshop sessions. Overarching recommendations highlighted across themes included future investments to provide data sharing, consistency, transparency, and opportunities for sharing best available science, knowledge, and expertise. The joint lab team synthesized the comments and identified four key research and development themes that could help advance the successful implementation of noise and vibration reduction strategies (see report). This report provides an overview of the workshop goals and scope, reviews the pre-workshop activities, presents brief summaries of participant feedback, and concludes with detailed research themes and recommendations for future investments. Appendix A includes the group discussion questions, Appendix B includes the results of the COP review, and Appendix C includes the results of the industry questionnaire. Overall, there was a high level of interest and engagement in the workshop. The sessions provided an opportunity for significant exchange of information between workshop participants from across sectors. Participants identified a variety of opportunities for next steps towards the noise reduction of offshore wind turbine installation in U.S. waters, including recommendations for future investments to provide certainty in the use of new technologies associated with alternative foundation types, noise abatement systems, and efficacy monitoring.

17 WIND ENERGY↗

Conservative projection-based data-driven model order reduction of a fluid-kinetic spectral solver

Kinetic simulations are computationally intensive due to six-dimensional phase space discretization. Many kinetic spectral solvers use the asymmetrically weighted Hermite expansion due to its conservation and fluid-kinetic coupling properties, i.e., the lower-order Hermite moments capture and describe the macroscopic fluid dynamics, and higher-order Hermite moments describe the microscopic kinetic dynamics. We leverage this structure by developing a parametric data-driven reduced-order model based on the proper orthogonal decomposition, which projects the higher-order kinetic moments while retaining the fluid moments intact. We demonstrate analytically and numerically that the method ensures local and global mass, momentum, and energy conservation. The numerical results show that the proposed method effectively replicates the high-dimensional spectral simulations at a fraction of the computational cost and memory, as validated on the weak Landau damping and two-stream instability benchmark problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗