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NASA NTRS2022

Estimating Species-Specific Leaf Area Index and Basal Area Using Optical and SAR Remote Sensing Data in Acadian Mixed Spruce-Fir Forests, USA

This study combined Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral, and site variable datasets to model leaf area index (LAI) and basal area per ha (BAPH) of two economically important tree species in Northeast, USA; red spruce (Picea rubens Sarg.; RS), and balsam fir (Abies balsamea (L.) Mill.; BF). We used Random Forest (RF), and Multi-Layer Perceptron (MLP) algorithms for LAI and BAPH modeling. The results showed that RF outperformed MLP by reducing the normalized root mean square error (nRMSE) by 0.01 and 0.06 for LAI and BAPH, respectively. The final variables selected for modeling of both LAI and BAPH indicated the superiority of Sentinel-2 variables over the Sentinel-1 SAR with minor contributions of site variables (mainly elevation). The red-edge spectral vegetation indices played a significant role in both LAI and BAPH estimation. We attained the lowest nRMSEs of 0.12, and 0.16 for the final LAI model of RS, and BF, respectively using Sentinel-2 and site variables. The lowest nRMSE for both RS and BF BAPH models was 0.12. As RS and BF are the primary host species for a cyclically occurring and most destructive pest of the region, eastern spruce budworm (Choristoneura fumiferana; SBW), these estimations will be useful to evaluate SBW dynamics in the region.

Forest inventory↗

NASA NTRS2023

Remotely Sensed Soil Moisture Can Capture Dynamics Relevant to Plant Water Uptake

A frequently expressed viewpoint across the Earth science community is that global soil moisture estimates from satellite L-band (1.4 GHz) measurements represent moisture only in a shallow surface layer (0–5 cm) and consequently are of limited value for studying global terrestrial ecosystems because plants use water from deeper rootzones. Using this argumentation, many observation-based land surface studies avoid satellite-observed soil moisture. Here, based on peer-reviewed literature across several fields, we argue that such a viewpoint is overly limiting for two reasons. First, microwave soil emission depth considerations and statistical considerations of vertically correlated soil moisture information together indicate that L-band measurements carry information about soil moisture extending below the commonly referenced 5 cm in many conditions. However, spatial variations of effective depths of representation remain uncertain. Second, in reviewing isotopic tracer field studies of plant water uptake, we find a prevalence of vegetation that primarily draws moisture from these upper soil layers. This is especially true for grasslands and croplands covering more than a third of global vegetated surfaces. Even some deeper-rooted species (i.e., shrubs and trees) preferentially or seasonally draw water from the upper soil layers. Therefore, L-band satellite soil moisture estimates are more relevant to global vegetation water uptake than commonly appreciated (i.e., relevant beyond only shallow soil processes like soil evaporation). Our commentary encourages the application of satellite soil moisture across a broader range of terrestrial hydrosphere and biosphere studies while urging more rigorous estimates of its effective depth of representation.

Andrew F. Feldman↗

DOE OSTI2018

Elevated [CO2] changes soil organic matter composition and substrate diversity in an arid ecosystem

Little is known about how rising atmospheric [CO2] will impact long-term plant biomass or the dynamics of soil organic matter (SOM) in arid ecosystems. Evans et al. (1) reported higher soil organic carbon (SOC) and total nitrogen (N) concentrations following 10 years exposure to elevated atmospheric [CO2] at the Nevada Desert Free-Air-Carbon dioxide-Enrichment (FACE) Facility (NDFF). In this study, we investigated potential mechanisms that resulted in increased SOC and total N accumulation and SOM stabilization using high resolution mass spectrometry. Samples were collected from soil profiles to 1 m in depth with a 0.2 m increment under the dominant evergreen shrub Larrea tridentata. The differences in the molecular composition and diversity of SOM were more evident in surface soils and declined with depth, and were consistent with higher SOC and total N concentrations under elevated than ambient [CO2]. Our molecular analysis also suggested increased root exudation and/or microbial necromass from stabilization of labile C and N contributed to SOM and N stocks. Increased microbial activity and metabolism under elevated [CO2] compared to ambient treatments suggest that elevated [CO2] altered microbial carbon use patterns, reflecting changes in the quality and quantity of SOC inputs. We found that plant-derived compounds were primary substrates for microbial activity under elevated [CO2] and microbial products were the main constituents of stabilized SOM. Our results suggest that arid ecosystems are a potential large C sink under elevated [CO2], given the extensive coverage of the land surface, and that labile compounds are transformed to stable SOM via microbial processes. Arid systems are limited by water, and thus may have a different C storage potential under changing climates than other ecosystems that are limited by nitrogen or phosphorus.

Tfaily, Malak M.↗

DOE OSTI2024

Minimizing the diffusivity difference between vacancies and interstitials in multi-principal element alloys

Interstitial atoms usually diffuse much faster than vacancies, which is often the root cause for the ineffective recombination of point defects in metals under irradiation. Here, via ab initio modeling of single-defect diffusion behavior in the equiatomic NiCoCrFe(Pd) alloy, we demonstrate an alloy design strategy that can reduce the diffusivity difference between the two types of point defects. The two diffusivities become almost equal after substituting the NiCoCrFe base alloy with Pd. The underlying mechanism is that Pd, with a much larger atomic size (hence larger compressibility) than the rest of the constituents, not only heightens the activation energy barrier ( E a ) for interstitial motion by narrowing the diffusion channels but simultaneously also reduces E a for vacancies due to less energy penalty required for bond length change between the initial and the saddle states. Our findings have a broad implication that the dynamics of point defects can be manipulated by taking advantage of the atomic size disparity, to facilitate point-defect annihilation that suppresses void formation and swelling, thereby improving radiation tolerance.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1988

Digital active control law synthesis for aeroservoelastic systems

This paper presents a formulation for synthesis of digital active control laws for aeroservoelastic systems, which are typically modeled by large order equations in order to accurately represent the rigid and flexible body modes, unsteady aerodynamic forces, actuator dynamics, and gust spectra. The control law is expected to satisfy multiple design requirements on the dynamic loads, responses, actuator deflection and rate limitations, as well as maintain certain stability margins, yet should be simple enough to be implemented by an onboard digital microprocessor. The synthesis procedure minimizes a linear quadratic Gaussian type cost function, by updating selected free parameters of the control law, while satisfying a set of inequality constraints on the design loads, responses and stability margins. A stable classical control law or an estimator based full or reduced order control law can be used as an initial design starting point. The gradients of the cost function and the constraints, with respect to the digital control law design variables are derived analytically, to facilitate rapid convergence. Selected design responses can be treated as constraints instead of lumping them into the cost function, in order to satisfy individual root-mean-square load and response limitations. Constraints are also imposed on the minimum singular value requirements for stability robustness improvement.

Mukhopadhyay, Vivekananda↗

DOE OSTI2015

Fluxons in a triangular set of coupled long Josephson junctions

We report results of an analysis of the dynamics of magnetic flux solitons in the system of three long Josephson junctions between three bulk superconductors that form a prism. The system is modeled by coupled sine-Gordon equations for the phases of the junctions. The Aharonov-Bohm constraint takes into account the axial magnetic flux enclosed by the prism and reduces the system from three independent phases to two. The equations of motion for the phases include dissipative terms, and a control parameter δ which accounts for the deviation of the enclosed flux from half a quantum. Analyzing the effective potential of the coupled equations, we identify different species of topological and non-topological phase solitons (fluxons) in this system. In particular, subkinks with fractional topological charges ±1/3 and ±2/3, confined inside integer-charge fluxons, may be mapped onto the root diagrams for mesons and baryons in the original quark model of hadrons. Solutions for straight-line kinks and for two types of non-topological solitons are obtained in an explicit analytical form. Numerical tests demonstrate that the former species is unstable against breakup into pairs of separating single-fluxon kinks. The non-topological kinks feature metastability, eventually breaking up into fluxon-antifluxon pairs. Free fractional-fluxon kinks, that connect different potential minima and are, accordingly, pulled by the potential difference, are also considered. Using the momentum-balance method, we predict the velocity at which these kinks should move in the presence of the dissipation. Numerical tests demonstrate that the analysis predicts the velocity quite closely. Higher-energy static solutions for all of the stable kink types mentioned above, as well as kinks connecting false vacua, are found by means of the shooting method. Inelastic collisions among the stable fractional and single-fluxon kinks are investigated numerically.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

BONCAT-Live for isolation and cultivation of active environmental bacteria

In diverse environments, microbes drive a myriad of processes, from geochemical and nutrient cycling to interspecies interactions, including associations with plants and animals. Their physiological state is dynamic and impacted by abiotic and biotic conditions, responding to environmental fluctuations by changes in cellular metabolism, according to their genetic potential. Molecular, cellular, and genomic approaches can identify and measure microbial responses and adaptation to environmental changes in native communities. However, isolating individual microbial cells that respond to specific changes for cultivation has been difficult. To address this, we implemented a novel bacterial isolation approach (BONCAT-Live) by integrating bio-orthogonal non-canonical amino acid tagging (BONCAT) in diverse native communities, with isolation and cultivation of cells responding to specific stimuli, at different time scales. In frozen Arctic permafrost samples, we identified and isolated dormant bacteria that become active after thawing under native or nutrient-enriched conditions. From the Populus tree rhizosphere, we isolated strains that thrive under high concentrations of root exudates that act as defense compounds and nutrients. In the human microbiome, we identified and isolated bacteria that rapidly proliferated when exposed to metabolites provided by the host or other co-occurring microbes. Further characterization of isolated bacterial strains will provide opportunities for in-depth determination of how these microbes adapt to changes in their environments, individually and as part of model communities.

Analytical Methods↗

NASA NTRS1994

Variability in equatorial Pacific sea surface topography during the verification phase of the TOPEX/POSEIDON mission

As part of the verification phase of the TOPEX/POSEIDON mission, 10-day gridded fields of altimeter data derived from TOPEX geophysical data records are compared with 10-day gridded fields of dynamic height derived from more than 60 moorings of the Tropical Ocean and Global Atmosphere-Tropical Atmosphere Ocean (TOGA-TAO) array in the equatorial Pacific Ocean. Access to TAO data in real time permits the first 500 days of the TOPEX/POSEIDON mission to be placed in the context of complementary, in-situ measurements of surface winds, sea surface temperatures, and upper ocean thermal structure, as well as the time history of these variables prior to launch. Analysis of the space-time structure in the TOPEX and TAO surface topography data increases sea level variability primarily due to equatorial Kelvin wave activity generated by intense wind bursts west of the date line in association with the 1991-1993 El Nino. Cross correlations between the two data sets are generally greater than 0.7, with root mean square (RMS) differences less than 4 cm. However, for reasons not fully understood, correlations drop to less than 0.5 in certain regions off the equator in the eastern Pacific and RMS differences can be greater than 5 cm north of the equator in the central and eastern Pacific.

Busalacchi, Antonio J.↗

DOE OSTI2023

Combustion of 10–100 μm aluminum droplets in detonation products gases

Here we describe a two-phase model of combustion effects in aluminized high explosive (HE) charges. It is based on: (i) a Gas Dynamic Model of the expansion of the detonation product gases and their turbulent combustion with air; and (ii) a Heterogeneous Continuum Model of aluminum (Al) droplets and their combustion with the detonation product gases. Initial conditions are based on an analytical similarity solution for a cylindrical Chapman-Jouguet (CJ) detonation propagating at the CJ detonation velocity. The CJ jump conditions are computed at the thermodynamic equilibrium state by the Cheetah code, assuming the Al droplets are inert. We assume that the Al is 10 % of the charge mass and occurs as droplets at the CJ state. Different initial droplet diameters, ranging from 10 to 100 microns, are studied. A hydrodynamic combustion model based on large Damköhler numbers is employed in this study, -3σ(1 + 0.276 $\sqrt{Re}$)/($Kd^2_w$). It has a square-root dependence on the Reynolds number (Re) and inversed-squared dependence on the droplet diameter (d w ). The burnout time (t B ) of the Al droplets has a three-halves dependence on the droplet diameter, t B ~ ($d^0_w$) 3/2 . After burnout, the detonation products act as detonation products of the HE charge with active Al. They turbulently mix with air and form a combustion layer on the outer edge of the fireball. Details of the two-phase model, initial conditions and evolution of the flow field will be described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Information theory and machine learning illuminate large‐scale metabolomic responses of Brachypodium distachyon to environmental change

SUMMARY Plant responses to environmental change are mediated via changes in cellular metabolomes. However, <5% of signals obtained from liquid chromatography tandem mass spectrometry (LC‐MS/MS) can be identified, limiting our understanding of how metabolomes change under biotic/abiotic stress. To address this challenge, we performed untargeted LC‐MS/MS of leaves, roots, and other organs of Brachypodium distachyon (Poaceae) under 17 organ–condition combinations, including copper deficiency, heat stress, low phosphate, and arbuscular mycorrhizal symbiosis. We found that both leaf and root metabolomes were significantly affected by the growth medium. Leaf metabolomes were more diverse than root metabolomes, but the latter were more specialized and more responsive to environmental change. We found that 1 week of copper deficiency shielded the root, but not the leaf metabolome, from perturbation due to heat stress. Machine learning (ML)‐based analysis annotated approximately 81% of the fragmented peaks versus approximately 6% using spectral matches alone. We performed one of the most extensive validations of ML‐based peak annotations in plants using thousands of authentic standards, and analyzed approximately 37% of the annotated peaks based on these assessments. Analyzing responsiveness of each predicted metabolite class to environmental change revealed significant perturbations of glycerophospholipids, sphingolipids, and flavonoids. Co‐accumulation analysis further identified condition‐specific biomarkers. To make these results accessible, we developed a visualization platform on the Bio‐Analytic Resource for Plant Biology website ( https://bar.utoronto.ca/efp_brachypodium_metabolites/cgi‐bin/efpWeb.cgi ), where perturbed metabolite classes can be readily visualized. Overall, our study illustrates how emerging chemoinformatic methods can be applied to reveal novel insights into the dynamic plant metabolome and stress adaptation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2004

Response of graywater recycling systems based on hydroponic plant growth to three classes of surfactants

Anionic (sodium laureth sulfate, SLES), amphoteric (cocamidopropyl betaine, CAPB) and nonionic (alcohol polyethoxylate, AE) surfactants were added to separate nutrient film technique (NFT) hydroponic systems containing dwarf wheat (Triticum aestivum cv. USU Apogee) in a series of 21 day trials. Surfactant was added either in a (1). temporally dynamic mode (1-3 g surfactant m(-2) growing area d(-1)) as effected by automatic addition of a 300 ppm surfactant solution to meet plant water demand, or (2). continuous mode (2 g surfactant m(-2) growing area d(-1)) as effected by slow addition (10 mLh(-1)) of a 2000 ppm surfactant solution beginning at 4d after planting. SLES showed rapid primary degradation in both experiments, with no accumulation 24 h after initial addition. CAPB and AE were degraded less rapidly, with 30-50% remaining 24 h after initial addition, but CAPB and AE levels were below detection limit for the remainder of the study. No reductions in vegetative growth of wheat were observed in response to SLES, but biomass was reduced 20-25% with CAPB and AE. Microbial communities associated with both the plant roots and wetted hardware surfaces actively degraded the surfactants, as determined by monitoring surfactant levels following pulse additions at day 20 (with plants) and day 21 (after plant removal). In order to test whether the biofilm communities could ameliorate phytotoxicity by providing a microbial community acclimated for CAPB and AE decay, the continuous exposure systems were planted with wheat seeds after crop removal at day 21. Acclimation resulted in faster primary degradation (>90% within 24h) and reduced phytotoxicity. Overall, the studies indicate that relatively small areas (3-5m(2)) of hydroponic plant systems can process per capita production of mixed surfactants (5-10 g x person(-1)d(-1)) with minimal effects on plant growth.

Hydroponics↗

DOE OSTI2024

Dynamic nitrogen fixation in an aerobic endophyte of Populus

Biological nitrogen fixation by microbial diazotrophs can contribute significantly to nitrogen availability in non-nodulating plant species. In this study of molecular mechanisms and gene expression relating to biological nitrogen fixation, the aerobic nitrogen-fixing endophyte Burkholderia vietnamiensis, strain WPB, isolated from Populus trichocarpa served as a model for endophyte–poplar interactions. Nitrogen-fixing activity was observed to be dynamic on nitrogen-free medium with a subset of colonies growing to form robust, raised globular like structures. Secondary ion mass spectrometry (NanoSIMS) confirmed that N-fixation was uneven within the population. A fluorescent transcriptional reporter (GFP) revealed that the nitrogenase subunit nifH is not uniformly expressed across genetically identical colonies of WPB and that only ~11% of the population was actively expressing the nifH gene. Higher nifH gene expression was observed in clustered cells through monitoring individual bacterial cells using single-molecule fluorescence in situ hybridization. Through 15 N 2 enrichment, we identified key nitrogenous metabolites and proteins synthesized by WPB and employed targeted metabolomics in active and inactive populations. We cocultivated WPB Pnif-GFP with poplar within a RhizoChip, a synthetic soil habitat, which enabled direct imaging of microbial nifH expression within root epidermal cells. We observed that nifH expression is localized to the root elongation zone where the strain forms a unique physical interaction with the root cells. This work employed comprehensive experimentation to identify novel mechanisms regulating both biological nitrogen fixation and beneficial plant–endophyte interactions.

15 N-tracking metabolomics↗

DOE OSTI2017

Plant Available Nutrients, Utqiagvik (Barrow), Alaska, Ver. 1

This dataset reports measurements of plant available nutrients made using Plant Root Simulator (PRS) probes (Western Ag Innovations Inc.) during 2012 and 2013 at the Next-Generation Ecosystem Experiments (NGEE) Arctic field site near Utqiagvik (Barrow), Alaska. In 2012, Ca, Mg, K, P, Fe, Mn, Cu, Zn, B, S, Pb, Al, Cd, NO3-N and NH4-N availability were measured during spring, summer and winter from probes installed in the centers, edges and troughs of four polygons in each of four areas of contrasting moisture regime and polygon type (Areas A, B, C, and D of Intensive Site 1). In 2013, probes were installed in centers, edges and troughs of four polygons in each of two areas (A and B, with low-centered and high-centered polygons respectively) at two-week intervals and at 3 soil depths to capture fine-scale seasonal dynamics of NO3-N and NH4-N. PRS probes are ion exchange resin membranes held in plastic supports that are inserted into soil to measure ion supply in situ. The anion and cation exchange with the membrane is intended to mimic plant uptake and thus provide a relevant measure of soil nutrient bioavailability. Measurements are made per area of probe membrane and cannot be converted to concentrations or related to soil volume. This dataset includes five csv files and three pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Pervasive symmetry-lowering nanoscale structural fluctuations in the cuprate La 2−𝑥 ⁢Sr 𝑥 ⁢Cu⁢O 4

The cuprate superconductors are among the most widely studied quantum materials, yet there remain fundamental open questions regarding their electronic properties and the role of structural degrees of freedom. Recent neutron and x-ray scattering measurements uncovered exponential scaling with temperature of the strength of orthorhombic fluctuations in the tetragonal phase of La 2−𝑥⁢ Sr 𝑥 ⁢Cu⁢O 4 and Tl 2 ⁢Ba 2 ⁢Cu⁢O 6+𝛿 , unusual behavior that closely resembles prior results for the emergence of superconducting fluctuations, and that points to a common origin rooted in inherent correlated structural inhomogeneity. Here, in this study, we use neutron and x-ray diffuse scattering to provide further insight into structural fluctuations in La 2−𝑥 ⁢Sr 𝑥 ⁢Cu⁢O 4 . We perform measurements up to temperatures that approach the melting point of the undoped parent compound, and we investigate the effects of in situ in-plane uniaxial elastic stress and plastic deformation. Our neutron scattering results for the parent compound La 2 ⁢Cu⁢O 4 reveal that short-range orthorhombic fluctuations persist to the maximum experimental temperature of nearly 1000 K, i.e., to a significant fraction of the crystallization temperature. At this temperature, the spatial characteristic length extracted from the momentum-space data is still about three lattice constants. The neutron scattering experiment enables quasistatic discrimination and reveals that the response is increasingly dynamic at higher temperatures. We also find that neither compressive elastic stress along the tetragonal [110] direction nor irreversible plastic deformation activating the ⟨100⟩⁢[001] slip system significantly alter the robust orthorhombic fluctuations. Overall, these results support the notion that these fluctuations couple to subtle, underlying inhomogeneity that underpins the cuprate phase diagram. Finally, in La 1.8⁢ Sr 0.2⁢ Cu⁢O 4 , we uncover low-energy structural fluctuations at a nominally forbidden reflection that are distinct from the orthorhombic distortions. While the origin of these fluctuations is not clear, they might be related to the presence of extended defects such as dislocations or stacking faults.

Spieker, R. J. [Univ. of Minnesota, Minneapolis, M↗

DOE OSTI2014

Development of a 6DOF robotic motion phantom for radiation therapy

Purpose: The use of medical technology capable of tracking patient motion or positioning patients along 6 degree-of-freedom (6DOF) has steadily increased in the field of radiation therapy. However, due to the complex nature of tracking and performing 6DOF motion, it is critical that such technology is properly verified to be operating within specifications in order to ensure patient safety. In this study, a robotic motion phantom is presented that can be programmed to perform highly accurate motion along any X (left–right), Y (superior–inferior), Z (anterior–posterior), pitch (around X), roll (around Y), and yaw (around Z) axes. In addition, highly synchronized motion along all axes can be performed in order to simulate the dynamic motion of a tumor in 6D. The accuracy and reproducibility of this 6D motion were characterized. Methods: An in-house designed and built 6D robotic motion phantom was constructed following the Stewart–Gough parallel kinematics platform archetype. The device was controlled using an inverse kinematics formulation, and precise movements in all 6 degrees-of-freedom (X, Y, Z, pitch, roll, and yaw) were performed, both simultaneously and separately for each degree-of-freedom. Additionally, previously recorded 6D cranial and prostate motions were effectively executed. The robotic phantom movements were verified using a 15 fps 6D infrared marker tracking system and the measured trajectories were compared quantitatively to the intended input trajectories. The workspace, maximum 6D velocity, backlash, and weight load capabilities of the system were also established. Results: Evaluation of the 6D platform demonstrated translational root mean square error (RMSE) values of 0.14, 0.22, and 0.08 mm over 20 mm in X and Y and 10 mm in Z, respectively, and rotational RMSE values of 0.16°, 0.06°, and 0.08° over 10° of pitch, roll, and yaw, respectively. The robotic stage also effectively performed controlled 6D motions, as well as reproduced cranial trajectories over 15 min, with a maximal RMSE of 0.04 mm translationally and 0.04° rotationally, and a prostate trajectory over 2 min, with a maximal RMSE of 0.06 mm translationally and 0.04° rotationally. Conclusions: This 6D robotic phantom has proven to be accurate under clinical standards and capable of reproducing tumor motion in 6D. Such functionality makes the robotic phantom usable for either quality assurance or research purposes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Dynamics of hydrogen–ammonia–natural gas lean-premixed high-pressure flames

The influence of fuel composition on self-excited combustion instabilities in a high-pressure combustor operated with ammonia, hydrogen, and natural gas fuels is characterized with high-frequency pressure measurements and imaging of the flame structure. A micromix multi-stage injector with 19 elements is used to introduce the fuel blend premixed with heated air into an optically accessible combustor operated at ~1.1 MPa. As hydrogen is substituted for natural gas, longitudinal thermoacoustic instabilities are observed in the combustor with pressure fluctuation amplitudes as large as 8% of the mean chamber value. In the absence of natural gas, limit-cycle instability magnitude is largely insensitive to ammonia addition. However, fuel compositions with > 20% natural gas result in positive correlation between instability amplitude and ammonia concentration. Spatial distribution of heat release in the combustor evaluated from OH* chemiluminescence imaging reveals axial growth in the regions of heat release fluctuation as hydrogen decreases, thus correlating flame length to instability amplitude. Distinct transitions from the first harmonic of the fundamental longitudinal acoustic mode (~1100 Hz) to the fundamental mode (~550 Hz) are observed with root mean square pressure fluctuations exceeding 7% of the mean chamber value. Here, these cases correspond to hydrogen mole fractions ≤ 50%. Analysis of the phase relationship between pressure fluctuations upstream and downstream of the flame zone indicates acoustic coupling of the injector as a key contributor to instability growth.

03 NATURAL GAS↗

DOE OSTI2022

Predicting spring green-up across diverse North American grasslands

Vegetation phenology influences many ecosystem and climate processes, such as carbon uptake and energy and water cycles. Thus, understanding drivers of vegetation phenology is crucial for predicting current and future impacts of climate change on ecological systems. Existing models can accurately predict the date of spring green-up in temperate forests but tend to perform poorly in grassland systems. We hypothesize this is because most do not incorporate water availability, a primary limiting factor for grassland plants. In this study, we used long-term datasets of digital imagery from the PhenoCam Network of 43 diverse North American grassland sites (195 site-years) to test existing spring phenology models, as well as develop several new models that incorporate precipitation or soil moisture (53 models). As a result, most of the new models performed substantially better, with the best model requiring sufficient accumulated precipitation followed by warm temperatures to trigger spring onset (root mean square error, RMSE, between predicted and observed dates = 16.0 days). Importantly, the best model performed well across all grassland types using a single set of parameters, from temperate to arid grasslands. Since plants are adapted to their local climates, model performance was further improved when parameters were independently optimized for four separate climate regions (RMSE = 10.4 days). Therefore, both sufficient precipitation and temperature are required for grassland green-up, but optimal thresholds vary by region. Running the top model with projected climate data (representative concentration pathway 8.5) suggests that, depending on the climate region, spring onset will occur up to 12 days earlier within 100 years in temperature-limited sites, but the trend is unclear for precipitation-limited sites (3.5 ± 8.0 days later). This new phenology model improves our ability to understand and predict grassland dynamics, with implications for both current and future ecosystem processes related to carbon and water cycling.

54 ENVIRONMENTAL SCIENCES↗