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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr −1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr −1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10 3 ± 0.9×10 3 km 3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Nelson, Jacob A.↗
DOE OSTI2026

V2XConnect: Harmonizing the Landscape of Bidirectional Charging Codes, Standards, and Communication Protocols

The utility grid is constantly evolving with new generation sources and diverse loads from backup generators, backup batteries, rooftop photovoltaics (PV), and flexible charging loads. Each of these technologies presents consumers with an opportunity to work with their local utility to promote grid stability, reliability, and affordability. Through a wide range of programs, utilities are incentivizing the use of these resources to benefit the grid. However, especially for devices with inverters that supply power back to the grid, it is important that these assets comply with local grid codes to ensure human safety, power quality, and grid reliability. One of the most promising of these new technologies is the bidirectional electric vehicle (EV) coupled with bidirectional electric vehicle supply equipment (EVSE). This report introduces the technologies that enable bidirectional charging and how these systems operate. It then outlines the necessary interconnection codes and industry standards that govern the operations of grid-tied inverters, including those in bidirectional charging. A key challenge is then outlined from the complex landscape of communication protocols and proprietary systems designed to coordinate these grid assets. Finally, a single gateway solution is proposed to harmonize communications between all assets across an entire site for a cohesive response to grid codes and utility programs that is flexible enough to support a range of market options.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

NSUF University Research Reactor Fitness Workshop

University research reactors have been a cornerstone of nuclear engineering research and education since the first reactor was deployed at North Carolina State University in the 1950s. The population of university reactors grew to a high of almost 80 in 1970 but has dropped to 25 operating today, also shrinking the community, availability of vendors and the talent pipeline. The nation’s fleet of TRTRs serves as a vital resource for educating the next generation of nuclear engineers and as a flexible testbed for innovative reactor technologies. Typically, the reactors have a very small staff with responsibilities ranging through research and operations, isotope production, regulatory compliance, facility maintenance, and university teaching obligations. Knowledge transfer and staffing were identified as critical areas in a recent study of US university research reactor fitness. This panel discusses the unique challenges and potential solutions to these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

ARIES: NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities

This presentation about ARIES was given at the NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities. ARIES was designed to fill a significant gap: there is no research platform that can support the nation's transition to a decarbonized energy system. ARIES will demonstrate and de-risk a future energy system with more than 50% renewable generation by 2030, that is just, affordable, flexible, clean, secure, resilient, and reliable, even in the off-road transportation sector.

ARIES↗
DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗
DOE OSTI2024

Leveraging Hydropower Multi-Sensor Data for Inference and Age-Informed Modeling

Increased demand of operational flexibility such as faster ramp up/down in generation, and more frequent start/stops are putting hydropower plants and their associated components in unprecedented stress. Consequently, these plants are at the high risk of extended and more frequent outage to accommodate unscheduled, and unexpected maintenance. Therefore, hydropower plants are in critical need of data driven and age-informed analysis for their regular and unscheduled operation. Yet not all hydropower plants are exhaustively equipped with sensors and/or measurement streams for their respective components – demanding solutions on how to detect, identify, and locate the cause of any event from the unobservable. Idaho National Laboratory (INL) analyzed the anonymized measurements and event records from the Hydropower Research Institute (HRI) to address this issue, as part of the Water Power Technologies Office (WPTO) funded one year multi-lab project. First, we investigated how time series of multiple sensor measurements can be leveraged to identify an event “root cause” as well as to develop an inference (i.e., estimate the unobservable) problem. INL also investigated how individual hydropower components’ reaction or response times vary across the pre-event, during event, and post-event conditions – enabling the hydropower dynamic models to be age-informed. Finally, the impact of clustering multi-sensor time series on short-term vibration prediction is analyzed. INL will present key findings from these analyses and recommend next steps for stakeholder adoption.

13 HYDRO ENERGY↗
DOE OSTI2022

Benchmarking Demand Flexibility in Commercial Buildings and Flattening the Duck – Addressing Baseline and Commissioning Challenges

With the transition from our traditional electric grid to a cleaner grid with renewable power generation, there is a need to enable building loads to be flexible. Load shedding and shifting will be essential for flattening the “Duck” for decarbonization. This paper explored the trend in the timing of DR events as a reflection of the grid’s needs using recent four years of event data from 203 retail stores in 11 states. The events are becoming significantly shorter with 2-hour duration being the most popular; shifting to late afternoon and early evening is another trend beyond California. Benchmarking will be essential for accounting DF as a reliable grid resource. This paper addresses a challenging aspect of benchmarking – inaccuracies in counterfactual baseline methods can introduce significant DF metrics variations in addition to weather and building characteristics related factors. The conventional “10/10” with adjustment baseline method has inherent limitation by design for load shifting applications. Therefore, it is imperative to identify alternative methods. This study compared three hourly regression baseline methods with “10/10” methods using two groups of commercial buildings that participated in DR programs: (1) 121 big-box retail stores, and (2) 11 office buildings in CA. The 14-day hourly outdoor temperature regression method was found to produce least error in the tested datasets and is promising for load shifting. The paper also pointed out that commissioning issues can also be a significant barrier for achieving consistent DF performance, which building managers and utilities should be aware of.

Liu, Jingjing↗
DOE OSTI2026

Developments in Performance and Portability of BlockGen

For more than a decade Monte Carlo event generators with the current matrix element algorithms have been used for generating hard scattering events on CPU platforms, with excellent flexibility and good efficiency. While the HL-LHC is approaching and precision requirements are becoming more demanding, many studies have been made to solve the bottleneck in the current Monte Carlo event generator tool chains. The novel BlockGen family of fast matrix element algorithms shown in this report, is one of the new developments that are more suitable for GPU acceleration. We report the development experience of porting BlockGen using Kokkos. Moreover, we discuss the performance of the Kokkos version in comparison with the dedicated GPU version in CUDA.

Bothmann, E. [Gottingen U.]↗
DOE OSTI2020

Advancing How We Learn from Biodesign to Mitigate Risks with Next-Generation Genome Engineering

In the last decade, the unprecedented simplicity and flexibility of the CRISPR-Cas system has made it the dominant transformative tool in gene and genome editing. However, this democratized technology is both a boon and a bane, for which we have yet to understand the full potential to investigate and rewrite genomes (also named “genome biodesign”). Rapid CRISPR advances in a range of applications in basic research, agriculture, and clinical applications pose new risks and raise several biosecurity concerns. In such a fast-moving field of research, we emphasize the importance of properly communicating the quality and accuracy of results and recommend new reporting requirements for results derived from next-generation genome engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Electrification Futures Study: Power Systems Operation with Newly Electrified and Flexible Loads

The Electrification Futures Study (EFS) is a multi-year study designed to analyze the impacts of widespread electrification in the U.S. energy system. In this webinar we present the detailed power systems operational analysis from the final report in the EFS series. For this analysis, we simulate multiple 2050 power systems for the conterminous United States to assess how variations in the magnitude and shape of electricity demand driven by electrification, and the extent of load participation to more-actively provide grid services, might impact the hourly operation, operational costs, and emissions of various power systems in 2050. The impacts of electrification and demand flexibility are overlayed across systems with significantly greater penetrations of variable renewable energy than today. Overall, we find that the high electrification scenarios envisioned in the EFS with significant VRE penetration (66% of annual national generation) can be operated to meet future increased levels of electrified demand. We also find that demand-side flexibility can enhance operational efficiency and reduce overall annual production costs by $5-$10 billion. The complementary relationship between flexible electric vehicle charging loads and solar generation is particularly pronounced, but in the absence of demand-side flexibility electrification can lead to increased wind and solar curtailment. By helping to reduce renewable curtailment, flexibility can also reduce power sector CO2 emissions. The analysis highlights the value of increased integration and coordination of demand- and supply-side resources in future electric system planning and operations—particularly under high electrification futures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

EPiC-GAN: Equivariant point cloud generation for particle jets

With the vast data-collecting capabilities of current and future high-energy collider experiments, there is an increasing demand for computationally efficient simulations. Generative machine learning models enable fast event generation, yet so far these approaches are largely constrained to fixed data structures and rigid detector geometries. In this paper, we introduce EPiC-GAN - equivariant point cloud generative adversarial network - which can produce point clouds of variable multiplicity. This flexible framework is based on deep sets and is well suited for simulating sprays of particles called jets. The generator and discriminator utilize multiple EPiC layers with an interpretable global latent vector. Crucially, the EPiC layers do not rely on pairwise information sharing between particles, which leads to a significant speed-up over graph- and transformer-based approaches with more complex relation diagrams. We demonstrate that EPiC-GAN scales well to large particle multiplicities and achieves high generation fidelity on benchmark jet generation tasks.

Buhmann, Erik↗
DOE OSTI2026

Fiber coupled laser ultrasound system using a single mode hollow core fiber for excitation laser: Theory and demonstration for on-machine thickness gauging

Laser ultrasound (LU) is a technique that uses a pump laser and a probe laser to optically generate and detect elastic waves in a material. Despite its advantages over traditional contact transducer-based ultrasound, industrial adoption has been limited by complex optical setups and the inability of multi-mode fibers to deliver a stable Gaussian profile for the pump laser. Here, we report a fully fiber-coupled thermoelastic LU system that uses an anti-resonant hollow-core single-mode fiber to deliver 1 mJ nanosecond pulses of 1064 nm light, while preserving the fundamental Gaussian mode (pump laser). When combined with a fiber-coupled interferometer (probe laser), a small, flexible, and environmentally robust sensor capable of optically generating and detecting high frequency broadband ultrasound is realized. We demonstrate such an LU system implemented in situ on a four-axis precision lathe. High-resolution thickness gauging is performed, before and after precision cutting, by exciting and measuring a zero-group velocity guided wave mode. The measurements are verified with ex-situ traceable coordinate measuring machine data. Mean absolute deviations of 0.1%, of nominal thickness, before cutting, and 0.2% and 0.3%, after stepped and tapered cuts, respectively, are reported. A theoretical background for thermoelastic ultrasound generation in an elastic waveguide is also presented. Attention is given to the effect of the pump laser profile on wave generation to elucidate the importance of using single-mode laser light. The fiber-coupled system demonstrated is well-suited for use in scientific and engineering sensing applications and facilitates the adoption of LU for industrial non-destructive testing.

Engineering↗
DOE OSTI2021

Optimal strategies for a cost-effective and reliable 100% renewable electric grid

This paper explores cost-optimal pathways to 100% renewable power systems for the U.S. building stock. We show that long-duration misalignments of supply and demand, spanning from multi-day to seasonal timescales, present a dominant challenge that must be addressed to meet real-time 100% renewable targets. While long-duration misalignments can be addressed through energy storage, we show that alternative and readily available solutions that are more cost-effective should be considered first. Through a techno-economic analysis, we identify cost-optimal, region-dependent, supply-side, and demand-side strategies that reduce, and in some U.S. regions eliminate, the otherwise substantial capacities and associated costs of long-duration energy storage. Investigated supply-side strategies include optimal mixes of renewable portfolios and oversized generation capacities. Considered demand-side strategies include building load flexibility and building energy efficiency investments. Our results reveal that building energy efficiency measures can reduce long-duration storage requirements at minimum total investment costs. In addition, oversizing and diversifying renewable generation can play a critical role in reducing storage requirements, remaining cost effective even when accounting for curtailed generation. We identify regionally dependent storage cost targets and show that for emerging long-duration energy storage innovations to achieve broad adoption, their costs will need to compete with the decreasing cost of renewables. The findings of this research are particularly important given that most long-duration storage technologies are currently either uneconomical, geologically constrained, or still underdeveloped.

100% renewable↗
DOE OSTI2024

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Reduced-Order Model of a Nuclear Power Plant with Thermal Power Dispatch

This paper presents reduced-order modeling of thermal power dispatch (TPD) from a pressurized water reactor (PWR) for providing heat to nearby heat consuming industrial processes that seek to take advantage of nuclear heat to reduce carbon emissions. The reactor model includes the neutronics of the reactor core, thermal–hydraulics of the primary coolant cycle, and a three-lump model of the steam generator (SG). The secondary coolant cycle is represented with quasi-steady state mass and energy balance equations. The secondary cycle consists of a steam extraction system, high-pressure and low-pressure turbines, moisture separator and reheater, high-pressure and low-pressure feedwater heaters, deaerator, feedwater and condensate pumps, and a condenser. The steam produced by the SG is distributed between the turbines and the extraction steam line (XSL) that delivers steam to nearby industrial processes, such as production of clean hydrogen. The reduced-order simulator is verified by comparing predictions with results from separate validated steady-state and transient full-scope PWR simulators for TPD levels between 0% and 70% of the rated reactor power. All simulators indicate that the flow rate of steam in the main steam line and turbine systems decrease with increasing TPD, which causes a reduction in PWR electric power generation. The results are analyzed to assess the impact of TPD on system efficiency and feedwater flow control. Due to the simplicity of the proposed reduced-order model, it can be scaled to represent a PWR of any size with a few parametric changes. In the future, the proposed reduced-order model will be integrated into a power system model in a digital real-time simulator (DRTS) and physical hardware-in-the-loop simulations.

08 HYDROGEN↗
DOE OSTI2022

Coordinated Ramping Product and Regulation Reserve Procurements in CAISO and MISO using Multi-Scale Probabilistic Solar Power Forecasts (Pro2R)

How can probabilistic solar forecasts lower costs and improve reliability for independent system operator (ISO) markets? We tackle this question in three steps. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty in those forecasts to error distributions for net load ramps for the California ISO (CAISO) using statistical and machine learning methods. Projected net load errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Finally, a multi-period look-ahead production cost model quantifies how conditional ramp requirements can a) decrease operating costs by lowering requirements compared to often conservative unconditional methods, and b) reduce generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. In addition to the products just described (quantification of solar uncertainty, its translation into requirements for ramp capability product, and quantification of the benefits of more accurate ramp requirements), this project also developed a visualization system that alerts system operators of ramp and uncertainty conditions within the network based on solar forecasts. The system is called Resource Forecast and Ramp Visualization for Situational Awareness (RaVIS). These four products represent significant advances in the state-of-the-art of probabilistic solar forecasting, development of weather-informed reserve requirements, production costing methods for estimating the benefits of more accurate reserve requirements, and visualization of system status, respectively. Yet the products are also practical and can be immediately implemented, potentially enabling system operators to save millions of dollars in ramp product procurement costs per year.

14 SOLAR ENERGY↗
DOE OSTI2025

Simulation Results of a Thermal Power Dispatch System from a Generic Pressurized Water Reactor in Normal and Abnormal Operating Conditions

Amid economic pressures in the U.S. electricity market, nuclear utilities are exploring new revenue streams, including hydrogen production. A generic pressurized water reactor simulator was modified to incorporate a novel design for a TPD system coupled to a hydrogen production plant. Standard malfunctions were included in the simulation design, including steam line breaks at various system locations and flow interruptions in the hydrogen plant due to multiple faults, reflecting anticipated operational challenges. It is imperative that the TPD system operation has a minimal effect on the reactor power, primary coolant system, and turbine system operation and performance. Due to the specific design and application of this TPD system, with the proposed turbine control system changes, the overall impact on the existing plant systems is low. Normal TPD operating scenarios resulted in minor effects on the existing plant systems: reactor power changes by at most 0.2%, and gross generator output changes by 20.5 MWe from 100 MWt of TPD. The most severe malfunction analyzed in this work is a full TPD steam line break downstream of the extraction location, which results in an increase in reactor power of about 0.5%. The gross generator output decreases by 36 MWe, a total decrease of 60 MWe from the full power steady state (FPSS) condition. These results indicate that an industrial hydrogen production plant could be coupled thermally to a nuclear power plant with limited effects on the existing system operation and safety.

08 HYDROGEN↗