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DOE OSTI2025

𝜂 and 𝜂′ Production in 𝐽/𝜓 Radiative Decays from Quantum Chromodynamics

We present a first principles calculation within quantum chromodynamics (QCD) of the radiative decays of the 𝐽/𝜓 into the light pseudoscalar mesons 𝜂 and 𝜂′. Within a lattice computation we obtain the transition form factors as a function of photon virtuality from the timelike region, accessible experimentally via the “Dalitz” decay 𝐽/𝜓 →𝑒 + ⁢𝑒 − ⁢𝜂 (′) , through to the real photon point corresponding to 𝐽/𝜓 →𝛾⁢𝜂 (′) . This is the first calculation in lattice QCD with two (heavier than physical) degenerate flavors of light quark and a heavier strange quark, in which the 𝜂′ appears as the first excited state with pseudoscalar isoscalar quantum numbers. We access it reliably by using variationally optimized operators , the use of which also improves the purity of the 𝐽/𝜓 and 𝜂 signals, reducing systematic uncertainties. High quality results at a large number of kinematic points are obtained in a typically noisy disconnected process by using a novel correlator averaging procedure. Our results show the expected enhanced production of the 𝜂′ over the 𝜂 in this process, and suggest that the demonstrated lattice technology is suitable for future calculations considering processes in which light meson resonances are produced.

form factors↗

DOE OSTI2024

Understanding Processes Controlling the Temporal and Spatial Variations of PBL Structures Over the ARM SGP Site

The surface heat, moisture, and momentum fluxes are transferred to the atmosphere above through the planetary boundary layer (PBL), where vertical mixing due to turbulent eddies of different sizes plays critical roles. Therefore, reliably representing PBL processes in numerical models is critical for weather, climate, and air quality prediction. Currently, there are over ten PBL schemes that are selectable within the advanced research version of the Weather Research and Forecasting (WRF) model, indicative of the challenges in capturing the impacts of turbulence within the PBL in models. Further improvements in PBL parameterizations are needed for both weather and climate models, as emphasized in many recent national reports, but require an advanced understanding of the underlying boundary layer processes from observations. This project takes advantage of Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) investments in the atmospheric boundary layer observations and Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) simulations to characterize PBL structures, understand key physical processes controlling the mixed layer development, and to evaluate PBL parameterization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Spatiotemporal mapping of microscopic strains and defects to reveal Li-dendrite-induced failure in all-solid-state batteries

Solid-state electrolytes (SSEs) are key to the success and reliability of all-solid-state lithium batteries, potentially enabling improvements in terms of safety and energy density over state-of-the-art lithium-ion batteries. However, there are several critical challenges to their implementation, including the interfacial instability stemming from the dynamic interaction of as-formed dendritic lithium during cycling. Here, we emphasize the importance of studying the spatial distribution and temporal evolution of strains and defects in crystalline solid-state electrolytes at the micro-scale, and how this affects dendrite growth. A proof-of-principle study is demonstrated using the synchrotron radiation based micro Laue X-ray diffraction method, and a custom-developed in-situ cycling device. Defects and residual strains are mapped, and the evolution of intragranular misorientation is observed. The feasibility of using this technique is discussed, and recommendations for micro-strain engineering to address the Li/SSEs interfacial issues are given. Additionally, work directions are pointed out with the consideration of combining multi-techniques for “poly-therapy”.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Novel Dosimetry Method for Small Animal Irradiators Using 3D-printed Mouse Phantoms and Alanine Dosimeters

Abstract Accurate dosimetry is a crucial component of small animal and preclinical irradiation studies. Various dosimetry options are available but fail to characterize complex geometries and variable energy spectra of modern x-ray irradiators accurately. These options also lack national/international standards of recognition. This paper presents a novel dosimetry system, Dosequate, which uses murine phantoms embedded with alanine dosimeters and paired with x-ray energy spectra corrections to deliver consistent and accurate dosimetry measurements. This study compares Dosequate measurements against a Precision X-RAD 320 internal ion chamber and the treatment planning system of an Xstrahl Small Animal Radiation Research Platform. Results demonstrate the accuracy and reproducibility of the Dosequate system, highlighting its potential for standardizing dosimetry in preclinical research throughout the industry. Results demonstrate the accuracy and reproducibility of the Dosequate system, highlighting its potential for standardizing dosimetry in preclinical research throughout the industry. The Dosequate dosimetry method provides a robust and standardized approach for measuring absorbed dose in small animal irradiators. Its accuracy, reproducibility, and ability to account for complex irradiation geometries make it a valuable tool for preclinical research. This system has the potential to significantly improve the intercomparability of studies across different facilities and enhance the reliability of results.

Environmental Sciences & Ecology↗

DOE OSTI2022

Direct measurement of 59 Ni( n, p ) 59 Co and 59 Ni( n, α ) 56 Fe at fast-neutron energies from 500 keV to 10 MeV

We report nuclear reaction data for neutron induced reactions on unstable nuclei are critical for a wide range of applications spanning studies of nuclear astrophysics, nuclear reactor designs, and radiochemistry diagnostics. However, nuclear data evaluations of the reaction cross sections are largely based on calculations due to the difficulty in performing this class of measurements and the resulting lack of experimental data. For neutron induced charged particle reactions at fast neutron energies, at the MeV scale, these cross section predictions are predominately driven by statistical Hauser-Feshbach calculations. In this work, we present partial and total 59 Ni(n, p) and 59 Ni(n, α) cross sections, measured directly with a radioactive 59 Ni target, and compare the results to the present nuclear data evaluations. In addition, the results from this work are compared to a recent study of the 59 Ni(n, xp) reaction cross section that was performed via an indirect surrogate ratio method. The expected energy trend of the cross section, based on the current work, is inconsistent with that of the surrogate work. This calls into question the reliability of that application of the surrogate ratio method and highlights the need for direct measurements on unstable nuclei, when feasible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Assessment of North Slope of Alaska (NSA) Snow Monitoring Arrays

Arrays of instruments for monitoring winter precipitation (snowfall) and snow cover on the ground installed in 2017 at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska (NSA) C1 and at Oliktok Point sites became operational in 2018. In 2022, the instruments from Oliktok Point were moved to NSA E12, about 5.4 km south of NSA C1, where two arrays now operate. The instrument arrays monitor wind speed and direction, snow depth at multiple locations, the horizontal flux of blowing snow, and the number and fall speed of hydrometeors. The arrays are monitored using digital cameras. Collectively, the instruments produce a wealth of data on falling and accumulated snow, but, as with any instrument array, some data are more reliable and accurate than others. In this document, we present our findings on the efficacy, accuracy, and reliability of each type of instrument. Overall, a key finding is that no single instrument provides sufficient information to determine the source of falling snow particles nor the cause of changes in snow depth. However, if used in concert, the instruments produce a reliable understanding of the processes affecting the snow cover depth distribution and the true winter precipitation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Experimental 3-dimensional tracking of the dynamics of a single electron in the Fermilab Integrable Optics Test Accelerator (IOTA)

We present the results of experimental studies on the transverse and longitudinal dynamics of a single electron in the IOTA storage ring. IOTA is a flexible machine dedicated to beam physics experiments with electrons and protons. A method was developed to reliably inject and circulate a controlled number of electrons in the ring. A key beam diagnostic system is the set of sensitive high-resolution digital cameras for the detection of synchrotron light emitted by the electrons. With 60–130 electrons in the machine, we measured beam lifetime and derived an absolute calibration of the optical system. At exposure times of 0.5 s, the cameras were sensitive to individual electrons. Camera images were used to reconstruct the time evolution of oscillation amplitudes of a single electron in all 3 degrees of freedom. The evolution of amplitudes directly showed the interplay between synchrotron-radiation damping, quantum excitations, and scattering with the residual gas. From the distribution of measured single-electron oscillation amplitudes, we deduced transverse emittances, momentum spread, damping times, and beam energy. Estimates of residual-gas density and composition were calculated from the measured distributions of vertical scattering angles. Combining scattering and lifetime data, we also provide an estimate of the aperture of the ring. To our knowledge, this is the first time that the dynamics of a single electron are tracked in all three dimensions with digital cameras in a storage ring.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Irradiation Vehicles for Evaluating SiC/SiC Cladding Bowing Under Neutron Flux Gradients

Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are among the most promising candidates for long term accident-tolerant nuclear fuel cladding. A key challenge related to their deployment is lateral bowing caused by differential radiation-induced swelling under dose or temperature gradients, which could obstruct coolant flow or interfere with control rod/blade movements. Although previous modeling efforts have predicted bowing behavior in light-water reactor (LWR) environments, experimental validation remains limited, especially at prototypic LWR temperatures. This study addresses that gap by irradiating six reduced-length SiC/SiC cladding tubes (~600 mm) in the High Flux Isotope Reactor (HFIR) at ~300°C, which is representative of LWR conditions. The tubes will be housed in a sealed vessel with an inert gas gap to maintain target temperatures and prevent direct coolant contact. Arranged in three pairs, each set will receive a different radiation dose (low, medium, high), with the central pair receiving ~0.1 displacements per atom (dpa)—the expected dose for peak bowing. The experiment will determine the dose-dependent bowing behavior and validate predictive finite element models. In this work, the tubes are freely suspended from pins to allow for unconstrained bowing; however, we present a concept for introducing localized constraints to represent grid spacer effects. Post-irradiation examination will include swelling measurements and profilometry to assess bowing and compare the results with model predictions. This work aims to confirm the conditions under which maximum bowing occurs so as to improve the reliability of SiC/SiC performance models in nuclear applications.

Russell, Nick [ORNL] (ORCID:0000000296099820)↗

DOE OSTI2020

Forecasting Megaelectron-Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms

We present the recent progress in upgrading a predictive model for megaelectron-volt (MeV) electrons inside the Earth's outer Van Allen belt. This updated model, called PreMevE 2.0, provides improved forecasts, particularly at outer L-shells, by adding upstream solar wind speeds to the model's input parameter list that originally includes precipitating electrons observed at low Earth orbits and MeV electron fluxes in situ measured by a geosynchronous satellite. Furthermore, based on several kinds of linear and artificial neural networks algorithms, a list of models was constructed, trained, validated, and tested with 42-month MeV electron observations from Van Allen Probes. Out-of-sample test results from these models show that, with optimized model hyperparameters and input parameter combinations, the top performer from each category of models has the similar capability of making reliable 1-day (2-day) forecasts of 1-MeV electron flux distributions with performance efficiency values ~0.87 (~0.82) averaged over the L-shell range of 2.8–6.6, significantly outperforming the previous version of PreMevE particularly at L-shells > ~4.5. Interestingly, the linear regression model is often the most successful when compared to other models, which suggests the relationship between dynamics of trapped 1-MeV electrons and precipitating electrons is dominated by linear components. Results also show that PreMevE 2.0 can reasonably well predict the onsets of MeV electron events in 2-day forecasts. PreMevE 2.0 is designed to be driven by observations from longstanding space infrastructure to make high-fidelity forecasts for MeV electrons, thus can be an invaluable space weather forecasting tool for the future.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Method of information entropy for convergence assessment of molecular dynamics simulations

The lack of a reliable method to evaluate the convergence of molecular dynamics simulations has contributed to discrepancies in different areas of molecular dynamics. Here, the method of information entropy is introduced to molecular dynamics for stationarity assessment. The Shannon information entropy formalism is used to monitor the convergence of the atom motion to a steady state in a continuous spatial domain and is also used to assess the stationarity of calculated multidimensional fields such as the temperature field in a discrete spatial domain. It is demonstrated in this work that monitoring the information entropy of the atom position matrix provides a clear indicator of reaching steady state in radiation damage simulations, non-equilibrium molecular dynamics thermal conductivity computations, and simulations of Poiseuille and Couette flow in nanochannels. A main advantage of the present technique is that it is non-local and relies on fundamental quantities available in all molecular dynamics simulations. Unlike monitoring average temperature, the technique is applicable to simulations that conserve total energy such as reverse non-equilibrium molecular dynamics thermal conductivity computations and to simulations where energy dissipates through a boundary as in radiation damage simulations. The method is applied to simulations of iron using the Tersoff/ZBL splined potential, silicon using the Stillinger–Weber potential, and to Lennard–Jones fluid. Its applicability to both solids and fluids shows that the technique has potential for generalization to other areas in molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Material effects on dynamics in triple-nozzle gas-puff Z pinches

Here, the gas-puff Z pinch has a long history with myriad applications as an efficient neutron or x-ray source. Its simplicity as a load configuration makes it suitable for studying fundamental plasma physics phenomena such as instabilities and energy transport. For example, the implosion of cylindrical shells onto a fusion fuel are inherently susceptible to instability growth on their external surfaces; if such instabilities are unmitigated, then the consequences in terms of degraded performance can be substantial. Similarly, mitigating heat transport from a hot fuel to its colder surrounding container can make fusion conditions more easily achievable. Here we have conducted a systematic study of triple-nozzle (outer liner, inner liner, fuel) gas puffs using two-dimensional (2D) magnetohydrodynamic simulations to investigate the effect of load material on the relevant dynamics. Analogous to past studies on spherical blast waves and converging shock waves, a trend emerges linking increased radiative cooling, lower adiabatic index, and increased magneto-Rayleigh-Taylor instability growth. Notably, our results suggest that, for the present configuration, Ar radiates less than both Ne and Kr during the early stages of the implosion while mass is being swept up and perturbations begin to seed instability growth. Consequently, pinches with Ar on the outer surface exhibit more stable 2D behavior. Here we also present a parameter scan of thermonuclear neutron yield, Y, as a function of peak current, I pk and dopant concentration with Ne or Ar, depending on the inner liner material. Above 6 MA, our results suggest Y ∝ $I$$^{5}_{pk}$ and even substantial mixing (10% by volume) of Ne into the fuel does not drastically reduce yield, suggesting an Ar/Ne/fuel configuration may reliably achieve DD thermonuclear yields of 10 13 – 10 14 /cm in the 10–20 MA range.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Speckle contrast of interfering fluorescence X-rays

With the development of X-ray free-electron lasers (XFELs), producing pulses of femtosecond durations comparable with the coherence times of X-ray fluorescence, it has become possible to observe intensity–intensity correlations due to the interference of emission from independent atoms. This has been used to compare durations of X-ray pulses and to measure the size of a focused X-ray beam, for example. Here it is shown that it is also possible to observe the interference of fluorescence photons through the measurement of the speckle contrast of angle-resolved fluorescence patterns. Speckle contrast is often used as a measure of the degree of coherence of the incident beam or the fluctuations of the illuminated sample as determined from X-ray diffraction patterns formed by elastic scattering, rather than from fluorescence patterns as addressed here. Commonly used approaches to estimate speckle contrast were found to suffer when applied to XFEL-generated fluorescence patterns due to low photon counts and a significant variation of the excitation pulse energy from shot to shot. A new method to reliably estimate speckle contrast under such conditions, using a weighting scheme, is introduced. The method is demonstrated by comparing the speckle contrast of fluorescence observed with pulses of 3 fs to 15 fs duration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

2020 State of the Science Report, Chapter 12: Adaptive Management Related to Marine Renewable Energy

As the marine renewable energy (MRE) industry is rapidly ramped up from single devices to commercial-scale deployments, developers and regulators will need evidence of the environmental effects of MRE to inform project development and consenting/permitting (hereafter consenting) processes. Uncertainty surrounding the potential impacts of novel RE technologies on sensitive marine animals, habitats, and ecosystem processes means that even robust baseline environmental information cannot comprehensively address all pre-deployment knowledge gaps. Tools and practical approaches are needed to help with the sustainable development of the industry. Adaptive management (AM), also referred to as learning by/while doing, enables projects to be deployed incrementally, despite uncertainty, in a way that prevents unacceptable harm to the marine environment. If rigorously implemented, this approach may provide a reliable mechanism for closing knowledge gaps, thereby retiring risks for future MRE developments. This chapter explores and suggests a pathway for applying a passive approach to AM for the consenting of single devices and array-scale MRE projects. Complementary information is available online at https://tethys.pnnl.gov/state-of-thescience-2020 -supplementaryadaptive-management. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-12-adaptive-management

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

BOSS quasar outflows traced by C iv

ABSTRACT We investigate possible factors that drive fast quasar outflows using a sample of 39 249 quasars at median redshift 〈z〉 ≈ 2.17. Unique to this study, the quasar redshifts are re-measured based on the Mg ii emission line, and explore unprecedented outflow velocities (>6000 km s−1), while maintaining statistical significance. We measure reliable C iv blueshifts for 1178 quasars with velocities >2500 km s−1. From those, 255(13) quasars have blueshifts above 4000(6000) km s−1, with the highest C iv velocity ≈7000 km s−1. Several correlations are observed, where higher C iv blueshifts in general are in quasars with broader, weaker C iv emission profiles, weak He ii emission, larger Eddington ratios, and bluer ultraviolet (UV) continuum slope across the rest-frame UV to near-infrared. Analysis reveals two primary factors contributing to faster outflows: higher Eddington ratios, and softer far-UV continuum (hν >24.6 eV). We find supporting evidence that radiative line driving may generate extreme outflow velocities, influenced by multiple factors as suggested by the aforementioned correlations. This evidence highlights the importance of considering a multidimensional parameter space in future studies when analyzing large C iv blueshifts to determine the fundamental causes of outflows.

Gillette, Jarred (ORCID:0000000185284839)↗

DOE OSTI2022

Protection and Restoration Solutions to Reliable and Resilient Integration of Grid-connected PV Installations and Distributed Energy Resources: Design, Testbed, Proof of Work and Impact Studies (Final Report)

To gain a better understanding of the complex transients in a utility grid with a large number of solar PV installations coupled by PWM inverters during the protection and restoration period of the power grid, in this project a kW-level experimental system with dominating inverter-based resources and a hardware-in-loop simulation system with transmission and distribution models, as well as several SEL protective relays have been built and used. The major research findings of the project are summarized below in two perspectives: Experimental research: A self-organized ultra-high frequency solitary waveform is discovered and demonstrated in the hardware experimental system. Despite the familiarities, such a solitary waveform is distinct from any harmonics, transient, or resonance waves in that, it is 1) non-dispersive over time and space, 2) not associated with any active source or the linear superposition of sources, 3) half-cycle asymmetric, 4) not responding to filters or change of system characteristic resonance frequency, 5) ubiquitous as it occurs simultaneously everywhere in the system from DC supply, power lines, and the utility grid, and 6) explosive through tripping the protection or damaging susceptible devices or circuits. Analytical study: The nature of such a new waveform and an analytical explanation of its formation are studied based on related physics and non-linear science principles, with the following highlights: 1) such a new waveform follows the solutions to the Non-linear Schrödinger equation, so the classic linear perturbation theory is unable to explain or predict such a unique waveform as confirmed with the research team of RTDS; 2) the critical condition of occurrence of such a waveform is derived, which indicates that the breakings of solitary wave is a system synchronous issue between the utility grid in the 60Hz phasor domain and duty-ratio modulation of DC sources in the inverter switching frequency domain; 3) such a waveform carries energy mass so it could be detrimental; 4) such a waveform is deceiving as it is not readily detectable in the energy propagation direction by the primary protection equipment, while it is detrimental in the perpendicular direction of energy propagation, i.e. voltage direction. Thus, it has more likely challenges to the second primary equipment and devices, particularly at the weakest link and point such as aging insulation and inappropriate setting of susceptible devices. Therefore, such a waveform can be easily ignored in the aftermath investigation. The intellectual merits: The experimental discovery reveals certain unfamiliar transient phenomena that could challenge the integration of large-scale grid-connected solar PV installation during the group ride-through period of solar PV installations, commissioning of large-solar farms, or dramatic change of solar radiation conditions. Particularly, the research findings suggest that the occurrence of the unfamiliar transient phenomena is uniquely associated with the inverter-based solar PV installation, which is less likely to happen for rotary energy systems. The physics and non-linear science-based research work laid down an analytical path to the challenging transient stability problems including those that have been observed currently and future calls. Both experimental and analytical research results explain the limitation of many current research effects including some DoE research undertakings as well as possible solutions. The broader impacts: The research outcome of the project advances the understanding of the possible transient problems for the integration of inverter-based solar PV installation. It also highlights the theoretical and technical barriers for applying the conventional theory and technology to design and implement countermeasures against their adverse impacts of the large-scale solar PV installation and operation on grid reliability and security. More broadly, the research outcomes have shed some light on the open, fundamental challenges in the integration of large-scale solar photovoltaic energy into current and next-generation power grids across the country, and worldwide. The advanced physics and non-linear science-based analysis open up a path to harmonization of the renewables for societal energy needs via building a resilient and sustainable electric power infrastructure.

14 SOLAR ENERGY↗

DOE OSTI2025

Constraining nuclear mass models using 𝑟-process observables with multiobjective optimization

Modeling nuclear masses, particularly for nuclei far from stability, remains a key objective in nuclear physics. One contemporary approach is machine learning (ML), which trains on experimental data, but can suffer large errors when extrapolating toward neutron-rich species. In nature, such masses shape observables for the rapid neutron capture process (𝑟 process), which in principle could inform ML models. Here, we introduce a multiobjective optimization approach using the Pareto front algorithm. We show that this technique, capable of identifying models that generate 𝑟-process abundances aligning with both solar and stellar data, is a promising method to select ML models with reliable extrapolation power.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R 2 ) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

09 BIOMASS FUELS↗