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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Flux-Closure Domain Structures in Ferroelectric K 0.5 Na 0.5 NbO 3 Thin Films

Topological domain structures in ferroelectric materials have garnered increasing attention due to their intriguing physical properties and promising applications. While most existing topological structures in ferroelectric perovskite oxides originate from tetragonal or rhombohedral bulk phases, much less is understood about their counterparts in orthorhombic ferroelectrics. Here, in this work, we employ ferroelectric K 0.5 Na 0.5 NbO 3 (KNN) thin films as a model system and leverage phase-field simulations to theoretically predict the static structures and dynamic behaviors of three types of flux-closure domain configurations: in-plane (Type-I), out-of-plane (Type-II), and superdomain (Type-III) flux-closure structures. We systematically investigate the effects of finite size, misfit strains, and electrical boundary conditions on the formation and switching of these topological structures. For the Type-I structure, size reduction or small misfit strain facilitates a transition of the flux-closure pattern to polar vortices. Type-II structures emerge under open-circuit electrical boundary conditions of the film, forming at the junctions of specific domain walls with the film surface or the film–substrate interface. The formation mechanisms of these two flux-closure structures are rationalized from an energy perspective. We demonstrated switching capabilities of Type-II and Type-III structures by obtaining polarization–electric field hysteresis loops. Our simulations also reveal a reversible electric-field-induced transition between the orthorhombic and rhombohedral ferroelectric phases with a checkerboard domain pattern, during which the integrity of the flux-closure structure is preserved. These findings provide theoretical insights and practical guidance for identifying and manipulating topological structures in low-symmetry ferroelectrics, paving the way for developing energy-efficient microelectronic devices based on topological structures.

P-E loop↗
DOE OSTI2025

Lattice Anisotropy-Driven Reduction of Phonon Velocities in Black Phosphorus

Phonon dynamics and transport determine how heat is utilized and dissipated in materials. In 2D systems for optoelectronics and thermoelectrics, the impact of nanoscale material structure on phonon propagation is central to controlling thermal conduction. Here, we directly observe in-plane coherent acoustic phonon propagation in black phosphorus (BP) using ultrafast electron microscopy. We identify a significant reduction of the group velocities in directions intermediate to the armchair and zigzag lattice directions. Using a machine learning-based model with an >8000 atom supercell, we find that this slowing results from the mixing of in-plane transverse and longitudinal acoustic phonons and is independent of broken symmetries of edge reconstructions. In conclusion, this work demonstrates how coherent phonon transport is sensitive to propagation direction in the lattice plane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗
DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Effect of Solvents on Lignin–Surface Interactions via Molecular Dynamics Simulations

Lignin, an essential building block of lignocellulosic biomass, is a potential abundant source of aromatic monomers for the polymer and chemical industry. Reductive catalytic fractionation (RCF) is one promising process that can produce high yields of phenolic monomers and oligomers from lignin under different catalytic conditions. An important choice in optimizing RCF is the selection of solvent; however, detailed insights into solvent effects on lignin behaviors and interactions remain limited. Here, in this work, we perform all-atom molecular dynamics simulations to study the solvation of lignin, solvent-mediated conformational changes, and the interaction of solvated lignin oligomers with model surfaces. We focus on the behavior of an oligomeric lignin model compound in methanol, ethanol, a binary mixture of ethanol and water, and water at both the RCF reaction temperature (473 K) and room temperature. Analysis of structural features of lignin suggests that these three organic solvent systems favorably solvate lignin, resulting in a more extended conformation suitable for catalytic conversion to valuable chemicals. We further introduce model palladium (Pd) and carbon (C) surfaces to understand how solvent choice impacts adsorption onto a representative catalytic surface and support, and to quantify the competition among the reactant and solvent molecules for the surface. Unbiased simulations suggest strong adsorption of lignin on both Pd and C surfaces at 473 K, with notable solvent-mediated differences in adsorption energies. Additionally, our findings indicate that lignin adsorption is promoted by the entropy change resulting from the displacement of solvent molecules from the surface. This study provides a molecular perspective of adsorption of lignin onto varying surfaces, which is a step towards understanding and optimizing the catalytic conversion of lignin into valuable chemicals.

adsorption↗
DOE OSTI2021

No ordinary proteins: Adsorption and molecular orientation of monoclonal antibodies

The interaction of monoclonal antibodies (mAbs) with air/water interfaces plays a crucial role in their overall stability in solution. We aim to understand this behavior using pendant bubble measurements to track the dynamic tension reduction and x-ray reflectivity to obtain the electron density profiles (EDPs) at the surface. Native immunoglobulin G mAb is a rigid molecule with a flat, “Y” shape, and simulated EDPs are obtained by rotating a homology construct at the surface. Comparing simulations with experimental EDPs, we obtain surface orientation probability maps showing mAbs transition from flat-on Y-shape configurations to side-on or end-on configurations with increasing concentration. The modeling also shows the presence of β sheets at the surface. Overall, the experiments and the homology modeling elucidate the orientational phase space during different stages of adsorption of mAbs at the air/water interface. These finding will help define new strategies for the manufacture and storage of antibody-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Using Energy Storage-Based Grid Forming Inverters for Operational Reserve in Hybrid Diesel Microgrids

In remote arctic communities, where access to a bulk electrical grid interconnection is not available, the implementation of islanded microgrids has been the most viable way to produce and distribute electricity services to their inhabitants. Historically, these islanded grids have relied primarily on diesel generators or hydropower resources to supply the baseload. However, this practice can result in increased expense due to the high costs associated with fuel transportation and the significant amounts of on-site storage necessary when fuel transportation is unavailable during winter months. In order to mitigate this problem, arctic microgrids have started to transition to a hybrid-source operational mode by incorporating renewable energy sources that are inherently variable in nature, such as wind or solar. Due to their highly stochastic behavior, these hybrid-source islanded microgrids can pose potential issues related to power quality due to introduction of rapid net load fluctuations and inability of diesel generators to respond rapidly. In addition, non-firm stochastic sources can require significant idling diesel generator resources to serve as spinning reserves, which is inefficient and wasteful. This work studies the problems that may arise in the transient dynamics of a real-world hybrid diesel microgrid when subjected to a loss of wind generation. Moreover, this work proposes a transition from a diesel spinning reserve to a battery energy-storage system (BESS) operating reserve scheme. The study of the proposed transition is important in establishing the fundamental implication of transient dynamics and the potential benefits of integrating a BESS as a spinning reserve in terms of stability, frequency nadir, and transient voltage deviation. The methods to investigate and validate the transient dynamics relied on both electromagnetic simulation models of GFMIs and a commercially available GFMI in an experimental power hardware-in-the-loop setup. The simulation results showed that the proposed operating reserve scheme improves the power quality of the system in terms of voltage deviation and frequency nadir when the microgrid is subjected to a loss of wind generation scenario. Depending on the simulation cases, adding a GFMI reduced the frequency nadir between 65.3% and 86.7%. Moreover, the reductions in the voltage deviations improved between 3.6% and 23.0%. From these results it can be concluded that the integration of a GFMI can reduce the frequency nadir in a hybrid diesel microgrid, and in turn, reduce diesel consumption, which improves system reliability while reducing fuel expenses. Furthermore, the novelty of this work relies on the fact that the offline simulation results were validated using a power hardware-in-the-loop platform that incorporated a 100 kVA commercially available GFMI as the device under test.

Hernandez-Alvidrez, Javier↗
DOE OSTI2022

Effects of Particle Size Distribution with Efficient Packing on Powder Flowability and Selective Laser Melting Process

The powder bed-based additive manufacturing (AM) process contains uncertainties in the powder spreading process and powder bed quality, leading to problems in repeatability and quality of the additively manufactured parts. This work focuses on identifying the uncertainty induced by particle size distribution (PSD) on powder flowability and the laser melting process, using Ti6Al4V as a model material. The flowability test results show that the effect of PSDs on flowability is not linear, rather the PSDs near dense packing ratios cause significant reductions in flowability (indicated by the increase in the avalanche angle and break energy of the powders measured by a revolution powder analyzer). The effects of PSDs on the selective laser melting (SLM) process are identified by using in-situ high-speed X-ray imaging to observe the melt pool dynamics during the melting process. The results show that the powder beds made of powders with dense packing ratios exhibit larger build height during laser melting. The effects of PSD with efficient packing on powder flowability and selective laser melting process revealed in this work are important for understanding process uncertainties induced by feedstock powders and for designing mitigation approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

How initial conditions-, structural-, and parameter-based model uncertainty interact and influence predictions in permafrost ecosystems: Modeling Archive

This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Deep Reinforcement Learning for Residential HVAC Control with Consideration of Human Occupancy

The Artificial Intelligence (AI) development described herein uses model-free Deep Reinforcement Learning (DRL) to minimize energy cost during residential heating, ventilation, and air conditioning (HVAC) operation. Building cooling loads and HVAC operation are difficult to accurately model due to complexity, lack of measurements and data, and model specific performance, so online machine learning is used to allow for real-time readjustment in performance. Energy costs for the multi-zone cooling unit shown in this work are minimized by scheduling on/off commands around dynamic prices. By taking advantage of precooling events that take place when the price is low, the agent is able to reduce operational cost without violating user comfort. The DRL controller was tested in simulation where the learner achieved a 43.89% cost reduction when compared to traditional, fixed-setpoint operation. The system is now ready for the next phase of testing in a live, real-time home environment.

Mckee, Evan↗
DOE OSTI2022

A Variable Pressure Multi-Pressure Rail System Design for Agricultural Applications

This paper presents a solution for reducing energy loss in the hydraulic control system of agricultural tractors and their implements. The solution is referred to as a multi-pressure rail (MPR) and provides power to the hydraulic functions following a pressure control logic, as opposed to the traditional flow control logic typical of hydraulic systems used in off-road vehicles. The proposed hydraulic control system allows for elimination of redundant flow control valves in the state-of-the-art system, which cause excessive throttling losses leading to poor overall energy efficiency. Related work on MPR technology targets construction vehicles, where the MPR solution can allow energy recovery during overrunning loads and better engine management. This paper alternatively addresses the case of agricultural applications where functions mostly operate under resistive load conditions with slow dynamics, which offers an opportunity to target throttle losses. For this purpose, the paper introduces a variable pressure control strategy to handle the instantaneous pressure at each rail. To develop both the controller and the hydraulic system architecture, a stationary test rig is conceived and used to validate a numerical simulation model of the MPR system and its control strategy. Particular focus is given to the dynamic behavior of the system during the switches of a function between different pressure rails, which needs to ensure reduced oscillations of the flow provided to each hydraulic function. Once validated, the simulation model is used to predict the energy savings of the MPR solution in an actual application: a 435 hp hydraulic tractor powering a 16-row planter, for which operating features during typical drive cycles were available to the authors. The results show up to 59% total power reduction at the pump shaft, corresponding to 89.8% system efficiency gain.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interplay between disorder, local relaxation, and collective behavior for an ensemble of emitters outside versus inside a cavity

The interplay between collective optical response and molecular static and dynamic disorder is studied using simple effective Hamiltonians for an ensemble of two-level emitters inside and outside a single-mode cavity. We model environmental disorder by randomly modulating the molecular transition frequencies and the coupling between the emitters and the electromagnetic field. We also consider the effects of intermolecular interactions and orientational disorder. We investigate how these effects lead to new features in the steady-state absorption (outside the cavity), transmission spectra (inside the cavity), and the yield of local molecular processes such as a unimolecular reaction. Outside the cavity, the collective behavior is manifested in the linewidth of the steady-state absorption, the emission spectrum, and the local chemical yield. Inside the cavity, however, the collective behavior primarily determines the Rabi splitting. The effects of intermolecular interactions under orientational disorder are also studied. For the most part, for all types of disorder, if we increase disorder, we find a reduction in the collective nature of the molecular response (smaller effective N) and therefore the Rabi splitting contraction occurs with orientational disorder. Furthermore, we find that static disorder is more destructive to collective behavior than dynamic disorder.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Reductive Dynamic and Static Excited State Quenching of a Homoleptic Ruthenium Complex Bearing Aldehyde Groups

A new homoleptic Ru polypyridyl complex bearing two aldehyde groups on each bipyridine ligand, [Ru(dab) 3 ](PF 6 ) 2 , where dab is 4,4′-dicarbaldehyde-2,2′-bipyridine, was synthesized, characterized, and utilized for iodide photo-oxidation studies. In acetonitrile (CH 3 CN) solution, the complex displayed an intense metal-to-ligand charge transfer (MLCT) absorbance maximum at 475 nm (ε = 22,000 M –1 cm –1 ) and an infrared (IR) band at 1712 cm –1 assigned to the pendent aldehyde groups. Visible light excitation in air-saturated solution resulted in room temperature photoluminescence (PL) with a maximum at 675 nm, a quantum yield, ϕ PL = 0.048, and an excited state lifetime, τ ο = 440 ns, from which radiative and nonradiative relaxation rate constants were extracted, k r = 9.1 × 10 4 s –1 and knr = 1.8 × 10 6 s –1 . Pulsed visible light excitation yielded transient UV–vis and IR absorption spectra consistent with an MLCT excited state; relaxation occurred with the maintenance of two isosbestic points in the visible region, and a lifetime that agreed with that measured by time-resolved PL. Cyclic voltammetry studies in a CH 3 CN solution with 0.1 M TBAPF 6 electrolyte revealed a quasi-reversible oxidation, E°(Ru III/II ) = +1.25 V vs. Fc +/0 , and three sequential one-electron reductions at −1.10, −1.25, and −1.54 V vs. Fc +/0 . Here, an excited state reduction potential of E°(Ru *2+/+ ) = +0.89 V vs. Fc +/0 was estimated with the Rehm–Weller expression. Titration of tetrabutylammonium iodide, TBAI, into a CD 3 CN solution of [Ru(dab) 3 ](PF 6 ) 2 resulted in significant shifts in the aldehyde H atom and 3,3′-biypridyl resonances that were analyzed with a 1:1 equilibrium model, from which K eq = 460 M –1 was extracted, increasing to 5800 M –1 when the solvent was changed to acetone-d 6 . Iodide titrations resulted in a significant quenching of the [Ru(dab) 3 ] *2+ lifetime and quantum yield in both CH 3 CN and acetone solvents. In CH 3 CN, the quenching was mainly dynamic and well described by the Stern–Volmer model, from which a quenching rate constant, k q , of 4.5 × 10 10 M –1 s –1 and an equilibrium constant, K eq , of 8.3 × 10 3 M –1 were obtained. In acetone, the static quenching pathway by iodide was greatly enhanced, with a K eq of 1.2 × 10 4 M –1 and a higher k q of 9.2 × 10 10 M –1 s –1 .

Aldehydes↗
DOE OSTI2020

Neural Network Molecular Dynamics at Scale

Neural network molecular dynamics (NNMD) simulations could revolutionize atomistic modeling of materials with quantum-mechanical accuracy at a fraction of computational cost. However, popular NNMD frameworks are generally implemented for a single computing node, and conventional energy-based NN models still suffer from large time-to-solution (T2S), prohibiting the application of NNMD to challenging materials simulations encompassing large spatiotemporal scales. Consequently, no leadership-scale NNMD simulation has thus far been reported. Here, we present a scalable parallel NNMD software (RXMD-NN) based on our scalable reactive molecular dynamics simulation engine named RXMD. RXMD-NN has achieved high scalability up to 786,432 IBM BlueGene/Q cores involving 1.7 billion atoms. Furthermore, we have achieved 4.6-fold reduction of T2S by using a novel network that directly predicts atomic forces from feature vectors. Reduced T2S has for the first time allowed the study of large-scale off-stoichiometry effect in a widely used phase change material, Ge 2 Se 2 Te 5 , thereby resolving its "firstsharp diffraction peak mystery".

fist sharp diffraction peak↗
DOE OSTI2021

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗
DOE OSTI2024

Reducing beta functions in the NSLS-II long straight section for NEXT-III beamlines

The NSLS-II Experimental Tools III (NEXT-III) Project with the goal of building 8-12 new beamlines is ongoing. We were requested to explore the possibility of modifying the long straight section in Cell 26 to accommodate two new undulators for Advanced Nanoscale Imaging (ANI) Beamline and Tender X-ray Nanoprobe (TXN) Beamline. The scope of work includes: linear lattice matching; confirmation of the minimum ID gaps consistent with beam stay-clear limitations; calculation of the X-ray brightness; optimization of the dynamic aperture and momentum acceptance; multi-particle tracking to confirm the injection efficiency does not deteriorate significantly. The beam simulations have to be done using the most recent NSLS-II lattice model with all present insertion devices and realistic magnet errors, misalignments, and apertures. Originally two lattice options were considered for the assessment:1) with single -minimum beta functions and 2) NSLS-II with double-minimum beta functions. However, since the beamlines are not interested in the reduction of the horizontal beta function, just the vertical one, we decided to stop considering the single-minimum option because the current vertical beta is already low (3.3m) and further reducing it at the straight section center can increase it too much at the edge of a long ID, and limit the beam stay-clear. So, this report is focused on the double mini-beta scheme only.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Wastewater reuse benefits for municipal complete retention lagoons: Life cycle assessment and dynamic modeling

Complete retention lagoons with wastewater reuse for agricultural purposes may offer sustainability advantages over alternative systems for small communities in semiarid regions. This study quantifies the environmental life cycle impact of adopting agriculture water reuse systems using case study data to estimate operating and building infrastructure impacts and spatial–temporal modeling to quantify resource trade-offs. Water reuse system benefits are highly dependent on supply–storage–demand dynamics. The relative size of irrigated agricultural land to the lagoon size was the most significant factor influencing site water application rates. The benefits are sensitive to changes in air emissions occurring from the agricultural land and further emphasize the importance of proper fertilizer management when adopting water reuse systems. Wastewater reuse from complete retention lagoons reduce life cycle GHG emissions, primarily through excavation reductions, offset fertilizer use, and especially from increased crop yields from wastewater reuse at previously rainfed sites.

54 ENVIRONMENTAL SCIENCES↗