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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High Performance Heat Pipe Power Transient Testing at SPHERE Facility

Microreactors are being researched, designed, and built at Idaho National Laboratory (INL). Microreactors are small reactors defined at less than 20MW of power. These reactor concepts are also being looked at throughout industry for various applications. An important aspect of these reactor designs is economic feasibility i.e. lower overnight capital cost. The driving factors for implementing microreactors are quick setup and takedown, minimal operators, and the ability to manufacture them readily and to fit in mid-sized containers for transport. A specific area of research to aid in successful integration of these factors within the designs is passive heat removal of the core’s thermal power. Interest in heat pipes to achieve this passive heat removal has been shown across multiple industry partners. Because of this interest, INL has developed a test facility to facilitate experimental tests for sodium filled heat pipes. INL has developed the Single Primary Heat Extraction and Removal Emulator (SPHERE) facility to run experiments on high performance, sodium filled heat pipes. As mentioned above, heat pipes are passive heat transfer devices. Radially, heat pipes are broken up into an outer wall, a small annular gap, a wick structure, and a centerline gap. They function by utilizing latent heat transfer. Heat pipes are traditionally separated into three regions, an evaporator (heat input), an adiabatic region, and finally a condenser region (heat removal). As heat is being applied to the evaporator, the working fluid undergoes a phase change to a vapor. This phase change causes a differential pressure across the axial length of the pipe driving flow down the center gap of the heat pipe. The vapor flows down past the adiabatic region to the condenser where the heat is removed. This heat removal forces the working fluid to phase change back to a liquid. The wick structure is then utilized to drive the flow back towards the evaporator by capillary forces. This backflow is aided by the annular gap. Because this heat transfer mechanism functions with latent heat transfer, the heat pipe is close to isothermal down the axial length. Heat pipes can operate under a wide range of working fluids. Considerations for these working fluids are primarily driven by operating temperatures amongst other important factors based around overall performance. Sodium filled heat pipes operate from 450°C up to 900°C. This temperature range works well for the current microreactor designs. In conjunction with this experimental capability, INL has developed a modeling software to simulate heat pipe physics within reactor cores. This modeling software is called Sockeye and functions under the established INL Multiphysics Object Oriented Simulation Environment (MOOSE). SPHERE also supports Sockeye development by providing the modeling team with experimental data on an array of setups and operating parameters to support validation efforts. A power transient experiment was performed utilizing the SPHERE facility to continue to aid with Sockeye development. The testing followed a proposed test plan to ramp up and down the temperature of the heat pipe. Sockeye models steady state heat pipe operation with high accuracy, the data provided by the power transient testing aims to assist with the validation efforts and further enhance transient modeling capability of the tool [2].

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters

Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gravothermal evolution of dark matter halos with differential elastic scattering

Here, we study gravothermal evolution of dark matter halos in the presence of differential self-scattering that has strong velocity and angular dependencies. We design controlled N-body simulations to model Rutherford and Møller scatterings in the halo, and follow its evolution in both core-expansion and -collapse phases. The simulations show the commonly-used transfer cross section underestimates the effects of dark matter self-interactions, but the viscosity cross section provides an accurate approximation for modeling angular-dependent dark matter scattering. We investigate thermodynamic properties of the halo, and find that the three moments of the Boltzmann equation under the fluid approximation are satisfied. We further propose a constant effective cross section, which integrates over the halo's characteristic velocity dispersion with weighting kernels motivated by kinetic theory of heat conduction. The effective cross section provides a good approximation to differential self-scattering for most of the halo evolution. It indicates that we can map astrophysical constraints on a constant self-interacting cross section to an SIDM model with velocity- and angular-dependent scatterings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phenomena Identification and Ranking Tables for High Temperature Gas-Cooled Microreactors

Micro-scaled high-temperature gas-cooled reactors (micro-HTGRs) offer a promising option for reliable power in remote or off-grid locations. While the safety characteristics of modular HTGRs have been widely studied, a micro-HTGR configuration alters several key thermal-fluid phenomena that govern both normal operation and passive decay-heat removal. In many proposed concepts, the reactor vessel is oriented horizontally and integrated into an ISO shipping container to enhance transportability and modular deployment. This report documents a Phenomena Identification and Ranking Table (PIRT) exercise focused on the thermal hydraulic safety phenomena relevant to all micro-HTGRs. The objective is to systematically identify, describe, and rank the importance, uncertainty, and modeling complexity of the key phenomena that control core and vessel temperatures during normal operation, pressurized conduction cooldown (PCC), and depressurized conduction cooldown (with air ingress) conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Can we observe the ion-neutral drift velocity in prestellar cores?

Given the low-ionization fraction of molecular clouds, ambipolar diffusion is thought to be an integral process in star formation. However, chemical and radiative-transfer effects, observational challenges, and the fact that the ion-neutral drift velocity is inherently very small render a definite detection of ambipolar diffusion extremely non-trivial. Here, we study the ion-neutral drift velocity in a suite of chemodynamical, non-ideal magnetohydrodynamic (MHD), two-dimensional axisymmetric simulations of prestellar cores where we alter the temperature, cosmic-ray ionization rate, visual extinction, mass-to-flux ratio, and chemical evolution. Subsequently, we perform a number of non-local thermodynamic equilibrium (non-LTE) radiative-transfer calculations considering various idealized and non-idealized scenarios in order to assess which factor (chemistry, radiative transfer, and/or observational difficulties) is the most challenging to overcome in our efforts to detect the ion-neutral drift velocity. We find that temperature has a significant effect in the amplitude of the drift velocity with the coldest modelled cores (T = 6 K) exhibiting drift velocities comparable to the sound speed. Against expectations, we find that in idealized scenarios (where two species are perfectly chemically co-evolving) the drift velocity ‘survives’ radiative-transfer effects and can in principle be observed. However, we find that observational challenges and chemical effects can significantly hinder our view of the ion-neutral drift velocity. Finally, we propose that HCN and HCNH + ⁠, being chemically co-evolving, could be used in future observational studies aiming to measure the ion-neutral drift velocity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Robust Implicit Adaptive Low Rank Time-Stepping Methods for Matrix Differential Equations

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac–Frenkel time-dependent variational principle. In recent years, it has attracted a lot of attention due to its wide applicability. Our schemes are inspired by the three-step procedure used in the rank adaptive version of the unconventional robust integrator (the so called BUG integrator) (Ceruti et al. in BIT Numer Math 62(4):1149–1174, 2022) for DLRA. First, a prediction (basis update) step is made computing the approximate column and row spaces at the next time level. Second, a Galerkin evolution step is invoked using an implicit solves for the small core matrix. Finally, a truncation is made according to a prescribed error threshold. Since the DLRA is evolving the differential equation projected on to the tangent space of the low rank manifold, the error estimate of the BUG integrator contains the tangent projection (modeling) error which cannot be easily controlled by mesh refinement. This can cause convergence issue for equations with cross terms. To address this issue, we propose a simple modification, consisting of merging the row and column spaces from the explicit step truncation method together with the BUG spaces in the prediction step. In addition, we propose an adaptive strategy where the BUG spaces are only computed if the residual for the solution obtained from the prediction space by explicit step truncation method, is too large. Here, we prove stability and estimate the local truncation error of the schemes under assumptions. We benchmark the schemes in several tests, such as anisotropic diffusion, solid body rotation and the combination of the two, to show robust convergence properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Hydrodynamic Test Requirements Process Improvements

Hydrodynamic testing at Los Alamos National Laboratory would benefit from a process improvement for the requirements process. Cameo was used as a digital solution for requirements management to allow Lead Engineers to track requirements more effectively. This was identified as a process improvement throughout this Capstone project. This report includes a project proposal, business case, literature review, methodology, project plan, data analysis, decision-making report, financial analysis report, discussion, and conclusion. Initially, this project focused on figuring out a solution for the hydrotest requirement process improvements. The scope narrowed to focus on the use of Cameo for requirement capture and management. During this Capstone, four tests had digital models produced for requirements management in Cameo. The initial model was the baseline, with core requirements used across the tests. Commonalities in tests were used and the core requirements allowed for process efficiencies. In the data analysis, it was seen that overall, the implementation of using Cameo for requirements resulted in a decreasing trend for both schedule and normalized cost. Tests have different complexity levels which is also a factor in how long the requirements process will take. Additional data is needed to continue analyzing process improvements. Through decisionmaking and financial analysis, the recommendation was to use Cameo for requirements process improvement. Multiple experts provided feedback for requirements that were then captured within models. Numerous tangible and intangible benefits were identified with this process improvement. For return on investment, the metric of success was schedule reduction, which was overall seen. Four tests were analyzed, so future analysis will be needed. There is also not a great financial risk because the main cost would be purchasing more licenses. Individuals must generate requirements whether using this software or not. Overall, training is needed to help improve the skillsets of Lead Engineers but is already being supported on a regular frequency. A desktop guide was started associated with explaining the process, however, it is a work in progress. The team plans on adding additional information in the digital models to help status when requirements are met using verification methods and artifacts. From working on this project an improved understanding of Cameo and requirements was the result. There are future opportunities to extend the usage for requirements management and progress will continue after this project.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Cosmic Overture Echoed in a Stellar Final Act: Implications of Nanohertz Gravitational Waves for Core Collapse Supernova Neutrinos

The growing evidence for nanohertz gravitational waves, from NANOGrav and other observations, may be pointing to a cosmological first-order phase transition at temperatures of 𝒪⁢(10−100)⁢MeV. Such an interpretation requires beyond the Standard Model dynamics in this energy range. If so, it may well be the case that galactic core-collapse supernova explosions would produce the key components related to the first-order phase transition, leaving detectable imprints on the spectrum of neutrinos emitted in the initial few seconds of the collapse. This might provide further evidence in support of the early universe interpretation of the nanohertz gravitational wave signal. The scenario proposed here is also suggestive of a low-mass seesaw mechanism to explain neutrino masses. We outline the prospects for future observations of Galactic supernovae to uncover the signals of this scenario, with further confirmation from future pulsar timing array measurements of primordial nanohertz gravitational waves.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Experimental X-ray Charge-Density Studies–A Suitable Probe for Superconductivity? A Case Study on MgB 2

Case studies of 1T-TiSe 2 and YBa 2 Cu 3 O 7-δ have demonstrated that X-ray diffraction (XRD) studies can be used to trace even subtle structural phase transitions which are inherently connected with the onset of superconductivity in these benchmark systems. However, the utility of XRD in the investigation of superconductors like MgB 2 lacking an additional symmetry-breaking structural phase transition is not immediately evident. Nevertheless, high-resolution powder XRD experiments on MgB 2 in combination with maximum entropy method analyses hinted at differences between the electron density distributions at room temperature and 15 K, that is, below the T c of approx. 39 K. The high-resolution single-crystal XRD experiments in combination with multipolar refinements presented here can reproduce these results but show that the observed temperature-dependent density changes are almost entirely due to a decrease of atomic displacement parameters as a natural consequence of a reduced thermal vibration amplitude with decreasing temperature. Our investigations also shed new light on the presence or absence of magnesium vacancies in MgB 2 samples–a defect type claimed to control the superconducting properties of the compound. Here, we propose that previous reports on the tendency of MgB 2 to form non-stoichiometric Mg 1–x B 2 phases (1 – x ~ 0.95) during high-temperature (HT) synthesis might result from the interpretation of XRD data of insufficient resolution and/or usage of inflexible refinement models. Indeed, advanced refinements based on an Extended Hansen–Coppens multipolar model and high-resolution X-ray data, which consider explicitly the contraction of core and valence shells of the magnesium cations, do not provide any significant evidence for the formation of non-stoichiometric Mg 1–x B 2 phases during HT synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Indicator-directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems

Modern high-performance and warehouse computing centers show strong interest in minimizing system power consumption while satisfying customers’ quality of service (QoS). Dynamic voltage and frequency scaling (DVFS) is effective for achieving this goal. Nevertheless, automating the process online and making it transparent to users must address three major challenges: (1) Complexity — today’s hardware components (e.g., CPUs, GPUs, memory, network, etc.) can be configured in several or dozens of frequency/voltage states for satisfying divergent system demands. Given their combination and the emergence of heterogeneity, searching the optimal configuration in the design space online can be timing consuming. (2) QoS guarantee — user-defined objectives such as power constraint and performance target must be monitored, predicted and ensured at the best effort. (3) Adaptability — various known and unknown workloads run on systems. Workloads characteristics should be quickly determined and configurations dynamically adjusted in accord with workloads and QoS. In this work, we focus on applications exhibiting an interesting feature – iterative or periodic, which is common among conventional HPC and emerging machine learning workloads. We propose an online dynamic power-performance (ODPP) management framework to dynamically adjust GPU DVFS configurations to meet performance and power objectives and constraints, without any code annotation or intrusion. Particularly, ODPP extracts the performance and power indicators for applications from their resources utilization profiles in a short episode. It further automatically constructs an accurate model that infers from the indicators how the application's performance and power vary with GPU core and memory frequencies. Aided with the model, for both seen and unseen applications, ODPP can quickly determine the most appropriate DVFS configuration for their execution. We evaluate ODPP on an NVIDIA GPU using multiple exascale computing (ECP) and deep learning applications.

Zou, Pengfei↗
DOE OSTI2024

On the Training and Generalization of Deep Operator Networks

Here, we present a novel training method for deep operator networks (DeepONets), one of the most popular neural network models for operators. DeepONets are constructed by two subnetworks, namely the branch and trunk networks. Typically, the two subnetworks are trained simultaneously, which amounts to solving a complex optimization problem in a high dimensional space. In addition, the nonconvex and nonlinear nature makes training very challenging. To tackle such a challenge, we propose a two-step training method that trains the trunk network first and then sequentially trains the branch network. The core mechanism is motivated by the divide-and-conquer paradigm and is the decomposition of the entire complex training task into two subtasks with reduced complexity. Therein the Gram–Schmidt orthonormalization process is introduced which significantly improves stability and generalization ability. On the theoretical side, we establish a generalization error estimate in terms of the number of training data, the width of DeepONets, and the number of input and output sensors. Numerical examples are presented to demonstrate the effectiveness of the two-step training method, including Darcy flow in heterogeneous porous media.

deep operator networks↗
DOE OSTI2023

Logical Majorana zero modes in a nanowire network

We present a scheme to use physical Majorana quasizero modes at each junction of a two-dimensional nanowire network to build a logical Majorana zero mode, the location of which is controllable through gate voltages. The wire network is a way to realize a recent proposal to imprint a Kekulé vortex pattern on a honeycomb lattice via gate voltages. We show that a specific type of junction, other than a naive Y or T junction, is needed to realize, without breaking time-reversal symmetry, an artificial “graphene” system with Majorana fermions instead of complex ones at each site. The junction we propose (i) traps exactly one physical Majorana (quasi)zero mode at each site of either a brick wall or honeycomb lattice and (ii) allows this mode to hybridize with all three neighboring sites. Using a lattice of these junctions and starting from an electronic, tight-binding model for the wires, we imprint the voltage patterns corresponding to the Kekulé vortex and observe the emergence of the logical Majorana zero mode at the vortex core. By suitable adiabatic modulations of gate voltages as a function of time, the positions of individual Kekulé vortices can be moved, and in this manner, non-Abelian braiding of the logical Majoranas bound to the vortex cores can be performed. We provide the range of parameters where these excitations could be realized experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

An Active Detection Scheme for Sensor Spoofing in Grid-tied PV Systems

In this paper an active detection scheme for sensor spoofing (manipulated externally via a cyber attack) in grid-tied PV systems is discussed. The core of the proposed active detection scheme is to introduce a private (secret) watermarking signal into the control inputs of the DC-DC converter and DC-AC inverter stages to detect any malicious spoofing (manipulation) of voltage/current sensor measurements controlling both the DC-DC converter maximum power point tracking (MPPT) stage and the DC-AC inverter of the grid-tied PV system. Several types of possible spoofing mechanisms (attack models) are discussed. The proposed sensor spoofing attack detector system consists of injecting a small magnitude of digital watermarking signal (DWS) and conduct three statistical watermark tests on the reported sensor measurements to determine if a) the proposed system is healthy and operating as expected b) if sensor signals were spoofed (manipulated) externally or c) if a particular sensor is malfunctioning due to a faulty hardware. It is shown via extensive simulations that the proposed DWS approach is robust in detecting malicious external manipulation of sensors controlling the grid tied PV system. A testing platform is currently under development and the experimental results will be discussed in the conference presentation.

Ibrahim, Hasan↗
DOE OSTI2020

Cellular cofferdams for hydropower use. Final report

This report presents the results of a comprehensive study on a proposal to use cellular cofferdams as basis for the design and construction of water retaining structures to sustainably and cost-effectively harness hydropower. Previously, cellular cofferdams have been widely used mainly as temporary water exclusion devices to permit dry construction of in-water structures such as dams, locks, bridge footings and piers, and hydroelectric power plants. Design and construction requirements for cellular cofferdams are less stringent than for hydropower dams. To make cellular cofferdams suitable for permanent hydropower use, different design concepts that utilize cellular cofferdams as the main or core element of the water-retaining dam structure are proposed. One key design concept is the so-called “dry construction technique” in which the granular fill in cofferdam cells and the downstream berm are permanently kept dry in contrast to the wet construction technique for temporary use of cellular cofferdams. The viability of the proposed permanent cellular cofferdam design concepts is demonstrated using well-established structural and geotechnical design procedures and computational modeling. The improved performance of the proposed design concepts, particularly in combination with the dry construction technique, show cellular cofferdams have the potential to be used as basis for the construction of permanent hydropower dam structures that are versatile, with less impact on the environment, and will cost less to build than conventional hydropower dams.

13 HYDRO ENERGY↗
DOE OSTI2020

CELLULAR COFFERDAMS AS PERMANENT HYDROPOWER DAM STRUCTURES

This paper presents the results of a comprehensive study on the potential use of cellular cofferdams as basis for the design and construction of water retaining structures to sustainably and cost-effectively harness hydropower. Previously, cellular cofferdams have been widely used mainly as temporary water exclusion devices to permit dry construction of in-water structures such as dams, locks, bridge footings and piers, and hydroelectric power plants. Design and construction requirements for cellular cofferdams are less stringent than for hydropower dams. To make cellular cofferdams suitable for permanent hydropower use, different design concepts that utilize cellular cofferdams as the main or core element of the water-retaining dam structure are proposed. One particular key design concept is the so-called “dry construction technique” in which the granular fill in cofferdam cells and the downstream berm are permanently kept dry in contrast to the wet construction technique for temporary use of cellular cofferdams. The viability of the proposed permanent cellular cofferdam design concepts is demonstrated using well-established structural and geotechnical design procedures and computational modeling. The improved performance of the proposed design concepts, particularly in combination with the dry construction technique, show cellular cofferdams have the potential to be used as basis for the construction of permanent hydropower dam structures that are versatile, with less impact on the environment, and will cost less to build than conventional hydropower dams.

13 HYDRO ENERGY↗
DOE OSTI2021

Ultrafast x-ray pump x-ray probe transient absorption spectroscopy: A computational study and proposed experiment probing core-valence electronic correlations in solvated complexes

Femtosecond X-ray pump X-ray probe experiments are currently possible at free electron lasers such as the linac coherent light source (LCLS), which opens new opportunities for studying solvated transition metal-ligand complexes. In order to make the most effective use of these kinds of experiments, it is necessary to determine which chemical properties an X-ray pump pulse will measure. In this paper, we have combined electron cascade calculations and excited-state time-dependent density functional theory calculations to predict the initial state prepared by an X-ray pump and the subsequent X-ray probe spectra at the Fe K-edge in the solvated model transition metal complex, K 4 Fe II (CN) 6 . We find several key spectral features that report on the ligand-field splitting, solvent-solute interactions, and the 3p and 3d electron interactions. We then show how these features could be measured in an experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Community Input on the Need, Scope, and Development Roadmap of a Proposed National Virtual Biosecurity for Bioenergy Crops Center (NVBBCC)

Brookhaven National Laboratory (BNL) was awarded a pilot project in FY22 under the U.S. Department of Energy (DOE) Office of Science Biopreparedness Research Virtual Environment (BRaVE) initiative, to define research priorities, needs, and requirements for a national virtual center devoted to the biosecurity of bioenergy crops. The mission of the proposed center, referred to as the National Virtual Biosecurity for Bioenergy Crop Center (NVBBCC), would be to provide the scientific basis and tools to detect, characterize, model, and mitigate biothreats to bioenergy crops. This function will be essential to ensure the projected increased US reliance over the next few decades on key plant-based energy products, such as biojet fuel. The NVBBCC is envisioned as a distributed, virtual center with multiple national laboratories at its core to maximize the use of existing unique facilities and expertise across the DOE complex. A major goal of the pilot project was to develop a roadmap for establishing NVBBCC through a series of meetings to gather community input. A total of about 150 individuals, drawn from DOE laboratories, the USDA, academia, NIH, DHS and the private sector participated in six planning meetings held in FY23. Four of the meetings were focused on specific research topics (disease detection, dispersion and disease propagation, biomolecular characterization of plant-pathogen interaction, and mitigation strategies). These four meetings were followed by a meeting that focused on computational needs to support collaborative, data-intensive research within a distributed center as well as workforce development. A final meeting focused on establishing and maintaining preparedness within NVBBCC to respond to an emerging disease within bioenergy crops and how it would collaborate and coordinate with USDA and DHS.

09 BIOMASS FUELS↗