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

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

P-doping-free III-nitride high electron mobility light-emitting diodes and transistors

We report that a simple metal-AlGaN/GaN Schottky diode is capable of producing GaN band-edge ultraviolet emission at 3.4 eV at a small forward bias larger than ∼2 V at room temperature. Based on the surface states distribution of AlGaN, a mature impact-ionization-induced Fermi-level de-pinning model is proposed to explain the underlying mechanism of the electroluminescence (EL) process. By experimenting with different Schottky metals, Ni/Au and Pt/Au, we demonstrated that this EL phenomenon is a “universal” property of metal-AlGaN/GaN Schottky diodes. Since this light-emitting Schottky diode shares the same active structure and fabrication processes as the AlGaN/GaN high electron mobility transistors, straight-forward and seamless integration of photonic and electronic functional devices has been demonstrated on doping-free III-nitride heterostructures. Using a semitransparent Schottky drain electrode, an AlGaN/GaN high electron mobility light-emitting transistor is demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Probing interfacial momentum closures in two-phase bubbly flow with machine learning-aided methods

Computational fluid dynamics (CFD) approach has already reached a high level of maturity for single-phase flows, however the development of closure models for two-phase flow requires additional attention. Multiphase CFD (M-CFD) methods resolve the conservation equations for mass, momentum and energy while differing in the approaches and strategies adopted in the physical closure models. The most widely adopted framework for M-CFD is the Eulerian-Eulerian two-fluid approach which assumes that all phases are co-existing inside each computational cell. For each fluid, the full set of conservation equations is solved; therefore, each fluid has a different velocity field. For adiabatic two-phase flow, the mechanisms of the interfacial momentum transfer are modeled by the interfacial forces representing different physical mechanisms. One of the crucial issues in the development and application of two-fluid model is the understanding of the interfacial momentum closures which determines the bubble distribution and migration behaviors. Dedicated experiments are performed to support the physical understanding and drive the closures’ development. However, limitations exist due to the uncertainties in the experimental measurement and the simplified analytical assumptions which have difficulties on representing the complex non-linear flow fields. In this paper, a data-driven approach, Feature Similarity Measurement (FSM), is developed and proposed to resolve the challenges of modeling the interfacial forces closures. Case study is performed with two-phase flow scenarios where the high-fidelity experimental data is available. Within the Eulerian-Eulerian two-fluid framework, only momentum equations for gas and liquid phases are solved and reduced-order interfacial momentum closures are aided with FSM. Predictions of void fraction and velocity fields are analyzed and demonstrate the potential of machine learning-driven interfacial forces closures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Mu2e Experiment [PowerPoint]

The Mu2e experiment at Fermilab is detailed. In summary, it improves the limit on μN → eN by four orders of magnitude; Many NP models predict R μe ~ 10 -14 - 10 -16 ; R&D is mature, with physics data collection beginning in 2021; and lastly, an upgraded experiment is planned.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Overview of Advanced Reactor Simulation Capabilities to Support Demonstrations

The Virtual Test Bed (VTB) was established to support the deployment of advanced reactors by facilitating the use of state-of-the-art modeling and simulation capabilities. These tools are able to solve previously prohibitive challenge problems in greater levels of fidelity and in a multi-physics framework. A VTB repository was recently set up to host models for a wide variety of reactor types and using a range of NEAMS-developed software. Table I summarizes the different capabilities already available in the repository and up-and-coming near/long term ones. The repository currently hosts models for a wide variety of reactor types, including High-Temperature Gas Cooled Reactors (HTGR), Sodium Fast Reactors (SFR), Fluoride salt cooled High-temperature Reactors (FHR), Molten Salt Reactors (MSR), and Heat-Pipe Microreactors (HP-MR). It should be noted that work is ongoing for all of the models and each example problem is at a different state of maturity.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Prediction and evaluation of route dependent dosimetry of BPA in rats at different life stages using a physiologically based pharmacokinetic model

Bisphenol A (BPA) has received considerable attention throughout the last decade due to its widespread use in consumer products. For the first time a physiologically based pharmacokinetic (PBPK) model was developed in neonatal and adult rats to quantitatively evaluate age-dependent pharmacokinetics of BPA and its phase II metabolites. The PBPK model was calibrated in adult rats using studies on BPA metabolism and excretion in the liver and gastrointestinal tract, and pharmacokinetic data with BPA in adult rats. For immature rats the hepatic and gastrointestinal metabolism of BPA was inferred from studies on the maturation of phase II enzymes coupled with serum time course data in pups. The calibrated model predicted the measured serum concentrations of BPA and BPA conjugates after administration of 100 μg/kg of d6-BPA in adult rats (oral gavage and intravenous administration) and postnatal days 3, 10, and 21 pups (oral gavage). The observed age-dependent BPA serum concentrations were partially attributed to the immature metabolic capacity of pups. A comparison of the dosimetry of BPA across immature rats and monkeys suggests that dose adjustments would be necessary to extrapolate toxicity studies from neonatal rats to infant humans. - Highlights: • A PBPK model predicts the kinetics of bisphenol A (BPA) in young and adult rats. • BPA metabolism within enterocytes is required for fitting of oral BPA kinetic data. • BPA dosimetry in young rats is different than adult rats and young monkeys.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

RELAP5-3D Modeling in the OECD-NEA HTTF Benchmark

Prismatic gas-cooled reactors are a technologically mature reactor concept of interest for near- to mid-term deployment. To accelerate the deployment of these reactors, the DOE's Advanced Reactor Technologies Gas-Cooled Reactor campaign is spearheading a thermal hydraulics code validation benchmark based on the High Temperature Test Facility at Oregon State University. This presentation provides an introduction to that benchmark and an overview of some of the RELAP5-3D validation activities stemming from that benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Review of the WECC EDT phase 2 EIM benefits analysis and results report.

A region-wide Energy Imbalance Market (EIM) was recently proposed by the Western Electricity Coordinating Council (WECC). In order for the Western Area Power Administration (Western) to make more informed decisions regarding its involvement in the EIM, Western asked Argonne National Laboratory (Argonne) to review the EIM benefits study (the October 2011 revision) performed by Energy and Environmental Economics, Inc. (E3). Key components of the E3 analysis made use of results from a study conducted by the National Renewable Energy Laboratory (NREL); therefore, we also reviewed the NREL work. This report examines E3 and NREL methods and models used in the EIM study. Estimating EIM benefits is very challenging because of the complex nature of the Western Interconnection (WI), the variability and uncertainty of renewable energy resources, and the complex decisions and potentially strategic bidding of market participants. Furthermore, methodologies used for some of the more challenging aspects of the EIM have not yet matured. This review is complimentary of several components of the EIM study. Analysts and modelers clearly took great care when conducting detailed simulations of the WI using well-established industry tools under stringent time and budget constraints. However, it is our opinion that the following aspects of the study and the interpretation of model results could be improved upon in future analyses. The hurdle rate methodology used to estimate current market inefficiencies does not directly model the underlying causes of sub-optimal dispatch and power flows. It assumes that differences between historical flows and modeled flows can be attributed solely to market inefficiencies. However, flow differences between model results and historical data can be attributed to numerous simplifying assumptions used in the model and in the input data. We suggest that alternative approaches be explored in order to better estimate the benefits of introducing market structures like the EIM. In addition to more efficient energy transactions in the WI, the EIM would reduce the amount of flexibility reserves needed to accommodate forecast errors associated with variable production from wind and solar energy resources. The modeling approach takes full advantage of variable resource diversity over the entire market footprint, but the projected reduction in flexibility reserves may be overly optimistic. While some reduction would undoubtedly occur, the EIM is only an energy market and would therefore not realize the same reduction in reserves as an ancillary services market. In our opinion the methodology does not adequately capture the impact of transmission constraints on the deployment of flexibility reserves. Estimates of flexibility reserves assume that forecast errors follow a normal distribution. Improved estimates could be obtained by using other probability distributions to estimate up and down reserves to capture the underlying uncertainty of these resources under specific operating conditions. Also, the use of a persistence forecast method for solar is questionable, because solar insolation follows a deterministic pattern dictated by the sun's path through the sky. We suggest a more rigorous method for forecasting solar insolation using the sun's relatively predictable daily pattern at specific locations. The EIM study considered only one scenario for hydropower resources. While this scenario is within the normal range over the WI footprint, it represents a severe drought condition in the Colorado River Basin from which Western schedules power. Given hydropower's prominent role in the WI, we recommend simulating a range of hydropower conditions since the relationship between water availability and WI dispatch costs is nonlinear. Also, the representation of specific operational constraints faced by hydropower operators in the WI needs improvements. The model used in the study cannot fully capture all of the EIM impacts and complexities of power system operations. In particular, a primary benefit of the EIM is a shorter dispatch interval; namely, 5 minutes. However, the model simulates the dispatch hourly. Therefore it cannot adequately measure the benefits of a more frequent dispatch. A tool with a finer time resolution would significantly improve simulation accuracy. When the study was conducted, the rules for the EIM were not clearly defined and it was appropriate to estimate societal benefits of the EIM assuming a perfect market without a detailed specification of the market design. However, incorporating a more complete description of market rules will allow for better estimates of EIM benefits. Furthermore, performing analyses using specific market rules can identify potential design flaws that may be difficult and expensive to correct after the market is established. Estimated cost savings from a more efficient dispatch are less than one percent of the total cost of electricity production.

14 SOLAR ENERGY↗
DOE OSTI2014

Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

Protein Quantitation, proteomics↗
DOE OSTI2023

Roadmap for IES Modeling and Simulation Activities: Update 2023

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2020, a last comprehensive roadmap for the DOE-NE Integrated Energy Systems program was published. In 2017, a separate modeling and simulation capability development plan was published that was extensively updated in 2022. The current report incrementally updates the 2022 modeling and simulation capability roadmap. This is not a new report, but individual sections have been updated to reflect recent accomplishments and new directions of the program. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations (i.e., support component design and real-time operations of experimental demonstration systems). Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis, and proposes next steps for a time horizon over the next years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Roadmap for IES Modeling and Simulation Activities

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2017, the last modeling and simulation capability development plan was published. In 2020, a comprehensive roadmap for the DOE-NE Integrated Energy Systems program has been published. The current report is meant to update the 2017 modeling and simulation capability roadmap and complement the IES overall program roadmap published in 2020. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations, i.e., support component design and real time operations of experimental demonstration systems. Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis and proposes next steps for a time horizon over the next 4 to 5 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Coupled Hydrodynamic-Geomechanical Modelling of CO2-WAG Field Development at Farnsworth Unit: A Case Study

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS. This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers. Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles. This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.

02 PETROLEUM↗
DOE OSTI2020

Techno-Economic Modelling of Tidal Energy Converter Arrays in the Tacoma Narrows

Hydrokinetic tidal energy converter (TEC) technology is yet to become cost competitive with other renewable energy sources. Understanding the interaction between energy production and the costs incurred harvesting that energy may unlock the economic potential of this technology. Although hydrodynamic simulation of TEC arrays has matured over time, including demonstration of how small and large arrays affect the resource, integration of cost modelling is often limited. The advanced ocean energy array techno-economic modelling tool ‘DTOcean’ enables designers to calculate and improve the levelised cost of energy (LCOE) of an array through parametric simulation of the energy extraction, design of the electrical network, moorings and foundations, and simulation of the installation and lifetime operations and maintenance of the array. This work presents a verification of DTOcean’s ability to simulate the techno-economic performance of TEC arrays by reproducing the hypothetical RM1 reference model, a semi-analytical model of a TEC array based in the Tacoma Narrows of Washington state, U.S.A. It is demonstrated that DTOcean can produce a reasonable estimate to the LCOE predicted by the reference model, giving (in Euro cents per kiloWatt hour) 36.69 ¢/kWh against the reference model’s 34.612 ¢/kWh for 10 TECs, while for 50 TECs, DTOcean calculated 20.34 ¢/kWh compared to 17.34 ¢/kWh for the reference model.

Topper, Mathew B. R. (ORCID:0000000347324347)↗
DOE OSTI2019

Coupled Geomechanical Modeling to Assess Cap Rock Integrity and Mechanical Fault Stability: Application to Farnsworth Field Unit Project

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations in the Farnsworth, Texas, USA. Anthropogenic CO2 is sourced from a fertilizer and an ethanol plant. This work utilizes Farnsworth’s full-field, history-matched, compositional hydrodynamic coupled geomechanical model for assessing the impact of stress changes observed through the history matched field life. Production and injection induced stress changes, fault stability and caprock integrity investigations are performed to project the potential for fault reactivation and the loss of caprock integrity under shear failure. A static mechanical earth model (MEM) was constructed for use in transient coupled geomechanical model based on the existing Southwest Regional Partnership (SWP) geological model. The static MEM inherits the stratigraphic and structural features of the geologic model and incorporates additional overburden, underburden, and sideburden formations required to impose mechanical boundary conditions. Mechanical properties were distributed in the 3D MEM through integration of geophysical logs and 3-dimensional seismic elastic inversion properties using a combination of Bayesian and stochastic interpolation methods. These data are further enhanced by lab derived strength and failure criteria for the caprock interval. Additionally, interpreted faults and other geological features were included as part of the static structural framework to fully represent subsurface hydraulic and mechanical systems and appropriately integrate heterogeneity. Two-way coupling of hydrodynamic flow and geomechanical simulations incorporates the Kozeny-Carman relationship for updating permeability and is history matched through primary, secondary (waterflooding) and tertiary (CO2 WAG) recovery periods before performing a twenty year forecast. Two-way simulations are performed to understand the effective stress perturbations imposed by field operations: water injection and the more recent implementation of WAG. Evaluation of Mohr circles with liquid production and field pressure charts as well as slip tendency and distance to failure metrics indicate that neither our faults or cap rock are critically stressed. This paper presents the results of the Farnsworth initial attempts to integrate the seismic driven 3D MEM into coupled hydrodynamic geomechanical history match simulation workflow.

02 PETROLEUM↗
DOE OSTI2014

Final technical report for Phenomic Analysis of Natural and Induced Variation in Brachypodium Distachyon DE-SC0001526

The goal of this project was to apply high-throughput, non-destructive phenotyping (phenomics) to collections of natural variants and induced mutants of the model grass Brachypodium distachyon and characterize a small subset of that material in detail. B. distachyon is well suited to this phenomic approach because its small size and rapid generation time allow researchers to grow many plants under carefully controlled conditions. In addition, the simple diploid genetics, high quality genome sequence and existence of numerous experimental tools available for B. distachyon allow us to rapidly identify genes affecting specific phenotypes. Our phenomic analysis revealed great diversity in biofuel-relevant traits like growth rate, biomass and photosynthetic rate. This clearly demonstrated the feasibility of applying a phenomic approach to the model grass B. distachyon. We also demonstrated the utility of B. distachyon for studying mature root system, something that is virtually impossible to do with biomass crops. We showed tremendous natural variation in root architecture that can potentially be used to design crops with superior nutrient and water harvesting capability. Finally, we demonstrated the speed with which we can link specific genes to specific phenotypes by studying two mutants in detail. Importantly, in both cases, the specific biological lessons learned were grass-specific and could not have been learned from a dicot model system. Furthermore, one of the genes affects cell wall integrity and thus may be a useful target in the context of biomass crop improvement. Ultimately, all this information can be used to accelerate the creation of improved biomass crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Precise relative locations for earthquakes in the northeast Pacific region

We report that double-difference methods applied to cross-correlation measured Rayleigh wave time shifts are an effective tool to improve epicentroid locations and relative origin time shifts in remote regions. We apply these methods to seismicity offshore of southwestern Canada and the U.S. Pacific Northwest, occurring along the boundaries of the Pacific and Juan de Fuca (including the Explorer Plate and Gorda Block) Plates. The Blanco, Mendocino, Revere-Dellwood, Nootka, and Sovanco fracture zones host the majority of this seismicity, largely consisting of strike-slip earthquakes. The Explorer, Juan de Fuca, and Gorda spreading ridges join these fracture zones and host normal faulting earthquakes. Our results show that at least the moderate-magnitude activity clusters along fault strike, supporting suggestions of large variations in seismic coupling along oceanic transform faults. Our improved relative locations corroborate earlier interpretations of the internal deformation in the Explorer and Gorda Plates. North of the Explorer Plate, improved locations support models that propose northern extension of the Revere-Dellwood fault. Relocations also support interpretations that favor multiple parallel active faults along the Blanco Transform Fault Zone. Seismicity of the western half of the Blanco appears more scattered and less collinear than the eastern half, possibly related to fault maturity. We use azimuthal variations in the Rayleigh wave cross-correlation amplitude to detect and model rupture directivity for a moderate size earthquake along the eastern Blanco Fault. Lastly, the observations constrain the seismogenic zone geometry and suggest a relatively narrow seismogenic zone width of 2 to 4 km.

58 GEOSCIENCES↗
DOE OSTI2019

QUIC-fire: A fast-running simulation tool for prescribed fire planning

Coupled fire-atmospheric modeling tools are increasingly used to understand the complex and dynamic behavior of wildland fires. Multiple research tools linking combustion to fluid flow use Navier-Stokes numerical solutions coupled to a thermodynamic model to understand fire-atmospheric feedbacks, but these computational fluid dynamics approaches require high-performance computing resources. We present a new simulation tool called QUIC-Fire to rapidly solve these feedbacks by coupling the mature 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. QUIC-Fire uses 3-D fuels inputs similar to the CFD model FIRETEC, allowing this tool to simulate effects of fuel structure on local winds and fire behavior. Results comparing fire behavior metrics to the computational fluid dynamic model FIRETEC show strong agreement. As a result, QUIC-Fire is the first tool intended to provide an opportunity for prescribed fire planners to compare, evaluate and design burn plans, including complex ignition patterns and coupled fire atmospheric feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗