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DOE OSTI2021

Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport

Computation of correlated ionic transport properties from molecular dynamics in the Green-Kubo formalism is expensive, as one cannot rely on the affordable mean square displacement approach. We use spectral decomposition of the short-time ionic displacement covariance to learn a set of diffusion eigenmodes that encode the correlation structure and form a basis for analyzing the ionic trajectories. This allows systematic reduction of the uncertainty and accelerate computations of ionic conductivity in systems with a steady-state correlation structure. We provide mathematical and numerical proofs of the method’s robustness and demonstrate it on realistic electrolyte materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities

Infrastructure in future smart and connected communities is envisioned as an aggregate of public services, including energy, transportation, and communication systems, all intertwined with each other. The intrinsic interdependency among these systems may exert the underlying influence on both design and operation of the heterogeneous infrastructures. Yet, few prior studies have tapped into the interdependency among these systems in order to quantify their potential impacts during standard operation. In response to this, this paper proposes an open-source, flexible, integrated modeling framework suitable for designing coupled energy, transportation, and communication systems and for assessing the impact of their interdependencies. First, a novel multi-level, multi-layer, multi-agent approach is proposed to enable flexible modeling of the interconnected systems. Then, for the framework's proof of concept, preliminary component and system-level models for different systems are designed and implemented using Modelica, an equation-based object-oriented modeling language. Finally, three case studies of gradually increasing complexity are presented (energy, energy + transportation, and energy + transportation + communication) to evaluate the interdependencies among the three systems. Quantitative analyses show that the deviation of the average velocity on the road can be 10.5% and the deviation of the power drawn from the grid can be 7% with or without considering the transportation and communication system at the peak commute time, indicating the presence of notable interdependencies. The proposed modeling framework also has the potential to be further extended for various modeling purposes and use cases, such as dynamic modeling and optimization, resilience analysis, and integrated decision making in future connected communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Estimating Spatial Distribution Impacts of Rooftops Solar PV on Dynamic Hosting Capacity Evaluation for a Real Distribution Feeder

This paper models the sensitivity of dynamic hosting capacity analysis to the spatial distribution of distributed PV scenarios, random, close and far from substation deployments, at various penetration levels on a real distribution feeder, in a quasi-static time series (QSTS) power flow simulation using high resolution time-aware metrics. These spatial distribution scenarios were chosen to capture a wide range of potential operation impacts of these deployments using a set of thermaland voltage-based metrics such as instantaneous violations and moving averages for both thermal and voltage constraints. This study uses actual load and PV data up-scaled from 1-hour time step to 1-minute resolution to fully characterize the interaction between the daily changes in load and PV output, and their impacts on distribution system operations.

distribution system↗

DOE OSTI2016

Unsteady Adjoint of Pressure Loss for a Fundamental Transonic Turbine Vane

High-fidelity simulations, e.g., large eddy simulation (LES), are often needed for accurately predicting pressure losses due to wake mixing and boundary layer development in turbomachinery applications. An unsteady adjoint of high-fidelity simulations is useful for design optimization in such aerodynamic applications. In this paper, we present unsteady adjoint solutions using a large eddy simulation model for an inlet guide vane from von Karman Institute (VKI) using aerothermal objectives. The unsteady adjoint method is effective in capturing the gradient for a short time interval aerothermal objective, whereas the method provides diverging gradients for long time-averaged thermal objectives. As the boundary layer on the suction side near the trailing edge of the vane is turbulent, it poses a challenge for the adjoint solver. The chaotic dynamics cause the adjoint solution to diverge exponentially from the trailing edge region when solved backward in time. This results in the corruption of the sensitivities obtained from the adjoint solutions. An energy analysis of the unsteady compressible Navier–Stokes adjoint equations indicates that adding artificial viscosity to the adjoint equations can dissipate the adjoint energy while potentially maintaining the accuracy of the adjoint sensitivities. Analyzing the growth term of the adjoint energy provides a metric for identifying the regions in the flow where the adjoint term is diverging. Results for the vane obtained from simulations performed on the Titan supercomputer are demonstrated.

Engineering↗

DOE OSTI2025

Investigation into the instantaneous centre of rotation for enhanced design of floating offshore wind turbines

The dynamic behaviour of floating offshore wind turbines (FOWTs) involves complex interactions of multivariate loads from wind, waves, and currents, which result in complex motion characteristics. Although methods for analysing global motion responses are well-established, the time- and location-dependent kinematics remain underexplored. This paper investigates the instantaneous centre of rotation (ICR), a point of zero velocity at a time instance of general plane motion. Understanding and strategically positioning the ICR can reduce the dynamic motion in critical structural locations, enhancing the performance and structural robustness of FOWTs. The paper presents a method for computing the ICR using time-domain simulation results and proposes a statistical analysis approach suitable for design studies. Building on prior research, it examines the sensitivity of the ICR to external loading and design features, providing insights into how these factors influence motion response and how the motion response influences the statistics of the ICR, structural loads, and other performance metrics of interest. The study explores two FOWT configurations, a spar and a semisubmersible, identifying design variables that most effectively control the ICR statistics and identifying the ICR statistics most correlated with the responses of interest. Finally, through two case studies, we demonstrate how to apply these new insights in a practical design scenario. By adjusting the design variables most correlated with the ICR (fairlead vertical position and centre of mass for the spar and mooring line length and offset column diameter for the semisubmersible), we successfully modified the designs of the floating support structures to reduce the loads in the mooring lines, tower base, and blade roots, improving the ultimate strength and fatigue characteristics compared to the original designs.

17 WIND ENERGY↗

DOE OSTI2018

Pixelated CZT Technology for the Detection, Identification, and Localization of Gamma-Ray Sources - 18311

Radioactive waste-management applications require good measurements to qualitatively and quantitatively characterize waste materials. Often these measurements must be done in situ, and the user wishes to learn something of the isotopic and spatial distribution of the source. Therefore, there is a need for a portable instrument that can map radioactive contamination and quantify sources. This presentation introduces several instruments that have been applied to this task, along with example measurements in relevant applications. All instruments are based on 3D-position-sensitive CdZnTe (CZT) detectors. This technology routinely achieves better than 1.1% FWHM energy resolution at 662 keV and operates at room temperature with a startup time under 2 minutes. All are packaged in portable enclosures with WiFi and Bluetooth capabilities for wireless communication. These capabilities allow the technology to be used in more advanced measurements in the field. A unique capability of these detectors is the ability to image the spatial distribution of gamma rays from a single stationary measurement. The first product, Polaris-H, has been in use at commercial nuclear power plants since 2013. The system, currently used at over 50% of the US nuclear-power fleet, integrates a 3D-position-sensitive CZT detector, associated readout electronics, an embedded computer, a battery with over 7-hour life, an optical camera, and a laser range finder in a portable water-proof enclosure. The system connects wirelessly to a tablet which displays a gamma-ray spectrum and isotope-specific images of the gamma-ray distribution in all directions in real time. The CZT detectors have a dynamic range from 50 keV up to 3 MeV. Coded aperture or pinhole imaging is used for energies below 250 keV, and Compton imaging is used for energies above 250 keV. List-mode data is saved to an external USB memory stick to enable more advanced analysis, including isotopic activity analysis, via H3D's post-processing software. Additional systems based on the same architecture have been developed to optimize the technology for other applications. These include Polaris-H Quad, which provides over 3 times the sensitivity for applications involving weaker sources, and Polaris-H Shield, which uses a collimator to provide images and isotope information over a narrower field of view in order to measure weaker sources in the presence of stronger sources of the same isotope. H3D has also developed custom systems that have been mounted on robots and drones that enable remote operation of the technology. Results from the measurements collected at commercial nuclear power plants and other applicable sites will be presented to show how these instruments can be used to detect, identify, and localize gamma-ray sources. Advanced analysis techniques to show the accurate quantification of the gamma-ray source will also be presented. Applications range from characterizing simple objects, to locating hottest points, estimating contamination distributions on an isotope-by-isotope basis, and differentiating scatter and direct emissions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Surrogate Modeling of Nonlinear Dynamic Systems: A Comparative Study

Surrogate models play a vital role in overcoming the computational challenge in designing and analyzing nonlinear dynamic systems, especially in the presence of uncertainty. This paper presents a comparative study of different surrogate modeling techniques for nonlinear dynamic systems. Four surrogate modeling methods, namely, Gaussian process (GP) regression, a long short-term memory (LSTM) network, a convolutional neural network (CNN) with LSTM (CNN-LSTM), and a CNN with bidirectional LSTM (CNN-BLSTM), are studied and compared. All these model types can predict the future behavior of dynamic systems over long periods based on training data from relatively short periods. The multi-dimensional inputs of surrogate models are organized in a nonlinear autoregressive exogenous model (NARX) scheme to enable recursive prediction over long periods, where current predictions replace inputs from the previous time window. Three numerical examples, including one mathematical example and two nonlinear engineering analysis models, are used to compare the performance of the four surrogate modeling techniques. The results show that the GP-NARX surrogate model tends to have more stable performance than the other three deep learning (DL)-based methods for the three particular examples studied. The tuning effort of GP-NARX is also much lower than its deep learning-based counterparts.

42 ENGINEERING↗

DOE OSTI2017

Coherence Spectroscopy in the Condensed Phase: Insights into Molecular Structure, Environment, and Interactions

The role of coherences, or coherently excited superposition states, in complex condensed-phase systems has been the topic of intense interest and debate for a number of years. In many cases, coherences have been utilized as spectators of ultrafast dynamics or for identifying couplings between electronic states. In rare cases, they have been found to drive excited state dynamics directly. Interestingly though, the utilization of coherences as a tool for high-detail vibronic spectroscopy has largely been overlooked until recently, despite their encoding of key information regarding molecular structure, electronically sensitive vibrational modes, and intermolecular interactions. Furthermore, their detection in the time domain makes for a highly comprehensive spectroscopic technique wherein the phase and dephasing times are extracted in addition to amplitude and intensity, an element not afforded in analogous frequency domain “steady-state” measurements. However, practical limitations arise in disentangling the large number of coherent signals typically accessed in broadband nonlinear spectroscopic experiments, often complicating assignment of the origin and type of coherences generated. Two-dimensional electronic spectroscopy (2DES) affords an avenue by which to disperse and decompose the large number of coherent signals generated in nonlinear experiments, facilitating the assignment of various types of quantum coherences. 2DES takes advantage of the broad bandwidth necessary for achieving the high time resolution desired for ultrafast dynamics and coherence generation by resolving the excitation axis to detect all excitation channels independently. This feature is beneficial for following population dynamics such as electronic energy transfer, and 2DES has become the choice method for such studies. Simultaneously, coherences arise as oscillations at well-defined coordinates across the 2D map often atop those evolving population signals. By isolating the coherent contribution to the 2DES data and Fourier transforming along the population time, a 3D spectral representation of the coherent 2D data is generated, and coherences are then ordered by their oscillation frequency, ν2. Individual coherences can then be selected by their frequency and evaluated via their distinct “2D coherence” spectra, yielding a significantly more distinctive set of spectroscopic signatures over other 1D methodologies and single-point 2DES analysis. Given that coherences of different origin result in unique 2D coherence spectra, these characteristics can be catalogued and compared directly against experiment for prompt assignment, a strategy not afforded by traditional 2DES analysis. In this Account, a structure-driven time-independent spectral model is discussed and employed to compare the 2D fingerprints of various coherences to experimental 2D coherence spectra. The frequency-domain approach can easily integrate ab initio derived vibronic parameters, and its correspondence with experimental coherence spectra of a model compound is demonstrated. Several examples and applications are discussed herein, from 2D Franck–Condon analysis of a model compound, to identifying the signatures of interpigment vibronic coupling in a photosynthetic light-harvesting complex. The 3D spectral approach to 2DES provides remarkable spectroscopic detail, in turn leading to new insights in molecular structure and interactions, which complement the time-resolved dynamics simultaneously recorded. The approach presented herein has the potential to distill down the convoluted set of nonlinear signals appearing in 2D coherent spectra, making the technique more amenable to high-detail vibronic spectroscopy in inherently complex condensed phase systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Nonlinear Anti-(Parity-Time) Symmetric Dimer

In the present work we propose a nonlinear anti- P T -symmetric dimer, that at the linear level has been experimentally created in the realm of electric circuit resonators. We find four families of solutions, the so-called upper and lower branches, both in a symmetric and in an asymmetric (symmetry-broken) form. We unveil analytically and confirm numerically the critical thresholds for the existence of such branches and explore the bifurcations (such as saddle-node ones) that delimit their existence, as well as transcritical ones that lead to their potential exchange of stability. We find that out of the four relevant branches, only one, the upper symmetric branch, corresponds to a spectrally and dynamically robust solution. We subsequently leverage detailed direct numerical computations in order to explore the dynamics of the different states, corroborating our spectral analysis results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

The Araucaria Project: The first-overtone classical Cepheid in the eclipsing system ogle-LMC-CEP-2532

We present here the first spectroscopic and photometric analysis of the double-lined eclipsing binary containing the classical, first-overtone (FO) Cepheid OGLE-LMC-CEP-2532 (MACHO 81.8997.87). The system has an orbital period of 800 days and the Cepheid is pulsating with a period of 2.035 days. Using spectroscopic data from three high-class telescopes and photometry from three surveys spanning 7500 days, we are able to derive the dynamical masses for both stars with an accuracy better than 3%. This makes the Cepheid in this system one of a few classical Cepheids with an accurate dynamical mass determination (M{sub 1}=3.90±0.10 M{sub ⊙}). The companion is probably slightly less massive (3.82±0.10 M{sub ⊙}), but may have the same mass within errors (M{sub 2}/M{sub 1}=0.981±0.015). The system has an age of about 185 million years and the Cepheid is in a more advanced evolutionary stage. For the first time precise parameters are derived for both stars in this system. Due to the lack of the secondary eclipse for many years, not much was known about the Cepheid’s companion. In our analysis, we used extra information from the pulsations and the orbital solution from the radial velocity curve. The best model predicts a grazing secondary eclipse shallower than 1 mmag, hence undetectable in the data, about 370 days after the primary eclipse. The dynamical mass obtained here is the most accurate known for a FO Cepheid and will contribute to the solution of the Cepheid mass discrepancy problem.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Strong Reduction in Amplitude of the Interfacial Segmental Dynamics in Polymer Nanocomposites

Despite the wide use of polymer nanocomposites (PNCs) in various applications, our understanding of the microscopic parameters controlling their macroscopic properties remains limited. In this study, we examine the dielectric strength of segmental dynamics, Δε IL (T) in the interfacial polymer layer surrounding the nanoparticles in PNCs. The presented analysis reveals a significant drop in Δε IL (T) and its anomalous temperature dependence in the polymer layer adsorbed to nanoparticles. The drop in Δε IL (T) was observed in all samples regardless of whether segmental relaxation time in the interfacial layer was slower or faster than in the bulk polymer, excluding interpretation of the “dead” layer. We ascribe the observed decrease in the dielectric strength to the restricted amplitude of segmental relaxation in the interfacial/adsorbed layer. Our results provide a new perspective on discussion of dynamics in the interfacial layer in PNCs and thin polymer films, demonstrating that not only segmental relaxation time but also its amplitude can be strongly affected by the interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗

DOE OSTI2017

Water and chloride ions migration in porous cementitious materials: An experimental and molecular dynamics investigation

The interactions of water and chloride ions penetration into porous mortar have been investigated experimentally and modelled by molecular dynamics. The water distribution visualized by neutron radiography and chloride penetration by Electron Probe Micro-Analysis indicate that separation of chloride ions from water during the penetration process took place and water ran much deeper into the material than chloride ions. The relationship between the penetration depth of water and chloride ions can be described by a linear function despite different water-cement ratio. Furthermore, molecular dynamics attributes the different transport mechanisms of water and ions in porous cementitious materials to three reasons: the nanostructure of hydration product play filtering role to screen chloride ions with larger hydration shell; as compared with water, ions reside in the calcium silicate surface for longer time due to the strong interfacial bonding; chloride ions accumulate and form CaCl ionic cluster, slowing down the migrating rate.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Rapid activation of non-oriented mechanophores via shock loading and spallation

Mechanophores (MPs), stimuli-responsive molecules that respond chromatically to mechanochemical reactions, are important for understanding the coupling between mechanics and chemistry as well as in engineering applications. However, the atomic-level understanding of their activation originates from gas phase studies or under simple linear elongation forces directly on molecules or polymer chains containing MPs. The effect of many-body distortions, pervasive in condensed-phase applications, is not understood. Therefore, we performed large-scale molecular dynamics (MD) simulations of a poly(methyl methacrylate)-spiropyran copolymer under dynamic mechanical loading and studied the activation of the MP under various conditions from dynamical compression to tension during unloading. Detailed analysis of the all-atom MD trajectories shows that the MP blocks experience significant many-body intramolecular distortion that can significantly decrease the activation barrier as compared with when deformation rates are slow relative to molecular relaxation time scales. Here we find that the reactivity of MPs under material compression states is governed by many-body effects of intramolecular torsions, whereas under tension, the reactions are governed by tensile stresses.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Dynamic PRA-Based Estimation of PWR Coping Time Using a Surrogate Model for Accident Tolerant Fuel

In this study, we propose an interpolation-based response surface surrogate methodology to manage a large number of scenarios in dynamic probabilistic risk assessment. It adopts the shape Dynamic Time Warping algorithm to cluster the interpolation neighborhood from time series sample data. The interpolation method was adapted from Taylor Kriging to allow a reduced-order model of the Taylor series. In order to demonstrate its applicability to complex issues in risk assessment for nuclear engineering, an example risk response surface to estimate emergency core cooling system (ECCS) criteria for triplex silicon carbide (SiC) accident-tolerant fuel was constructed. The response surface was exploited to estimate the cumulative failure probability of the fuel cladding structure due to the uncertainties in operator actions and safety systems. The functional failures were assessed based on a combination of individual layer failures computed by coupling Risk Analysis Virtual Environment software with a pressurized water reactor 1000-MW(electric) RELAP5 model and the in-house fuel performance assessment module. Results showed that SiC cladding failure probability spiked less than 1 min after a large-break loss-of- coolant accident whenever the current ECCS criteria for Zircaloy-4 (Zr-4) cladding was used. However, it still provides an increased safety margin of three orders of magnitude compared to Zr-4. This positive margin could be utilized to relax active ECCS requirements by allowing deviations of up to 450 s in its actuation time. The proposed surrogate methodology generated a response surface of SiC cladding failure probability reasonably well, with a significant savings of computation time. This methodology is expected to be useful in the analysis of system response with complex uncertainty sources.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗

DOE OSTI2015

Ultrafast carriers dynamics in filled-skutterudites

Carrier dynamics of filled-skutterudites, an important class of thermoelectric materials, is investigated using ultrafast optical spectroscopy. By tuning the wavelength of the probe laser, charge transfers at different electronic energy levels are interrogated. Analysis based on the Kramers-Kronig relation explains the complex spectroscopy data, which is mainly due to band filling caused by photo-excited carriers and free carrier absorption. The relaxation time of hot carriers is found to be about 0.4–0.6 ps, depending on the electronic energy level, and the characteristic time for carrier-phonon equilibrium is about 0.95 ps. These studies of carrier dynamics, which fundamentally determines the transport properties of thermoelectric material, can provide guidance for the design of materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Estimating heterotrophic respiration at large scales: challenges, approaches, and next steps

Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of "Decomposition Functional Types" (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing models to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present and discuss an example clustering analysis to show how model-produced annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from already-existing PFTs. A similar analysis, incorporating observational data, could form a basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with high-performance computing; rigorous testing of analytical results; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR at large scales.

carbon cycle↗