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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Carbon Capture Pilot at Vicksburg Containerboard Mill (Final Technical Report)

This is the final technical report for the DOE-OCED project DE-CD0000051. The report provides the progress at the close of the project. The objective of the project is to design and build a large pilot plant for carbon dioxide (CO 2 ) capture from a pulp and paper (P&P) mill using RTI’s non-aqueous solvent (NAS) technology at a capacity of 120,000 t-CO 2 /year, with >90% CO 2 captured. The pilot plant will be used for testing and evaluating the NAS capture process using real flue gas from the P&P mill’s power boiler for a minimum of 1 year of parametric testing and a minimum of 2,000 hours of continuous long-term testing. The testing will provide data for process optimization and scale-up for the P&P industry, provide information on interaction of flue gas contaminants on solvent performance and degradation, and inform strategies for emission control. At the end of the project, the pilot plant will be managed by International Paper (IP), the host site owner, which will continue to capture CO 2 , sequester the captured CO 2 , and be eligible for the 45Q credit.

42 ENGINEERING↗
DOE OSTI2022

Charging Infrastructure Technologies: Development of a Multiport, >1 MW Charging System for Medium- and Heavy-Duty Electric Vehicles

Development of a Multiport, >1 MW Charging System for Medium- and Heavy-Duty Electric Vehicles project will develop research tools for a framework to design, optimize, and demonstrate key components of a multi-port 1+ MW medium-voltage connected charging system. The objectives of this effort are to develop strategies and technologies for multi-port 1+ MW grid-connected stations to recharge MD/HD electric vehicles at fast-charging travel plazas or at fleet depots; through industry engagement, charging station utilization and load analysis, grid impacts and interconnection analysis, detailed power electronics component design and controller demonstration, site and battery charge control design and controller demonstration; and charging connector design.

1+MW charging↗
DOE OSTI2024

Developing Smart Building Technology Modules to Enhance Workforce Preparedness: A Case for AI-Driven Academic and Professional Education

Smart building technologies are resources that improve building energy efficiency and resilience, reduce carbon emissions, and provide load flexibility to the grid. However, in both academic curricula and building professionals’ continuing education, there is a lack of systematic instruction on methods to integrate multiple energy systems including distributed energy resources (DER), smart building technologies, AI (Artificial Intelligence) tools and key concepts, components, and controls, including “Internet of Things” (IoT) devices. In today’s dynamic workforce, this major gap in smart building technology education prevents stakeholders from being able to attract talent with an understanding and preparation to adopt smart building technologies in building design and operations. A federally funded project included a partnership between Slipstream and Texas A&M University (TAMU) to develop a semester-long smart building curriculum for engineering college students with the ability to adapt the contents for workforce development of professionals in building services. The final product consists of 16 training videos adapted for building professionals and the public. The educational content and training materials cover the benefits of building energy systems, the latest sensor technologies and IoT devices, all with a focus on smart building technologies. The key drivers are on topics related to smart building controls (i.e., energy management information systems), smart building control platforms, cybersecurity, grid-interactive-efficient buildings (GEBs), smart building control methods, and occupant-centric control. Although not explicitly included the technologies nod to the need for AI driven technologies to prepare engineers and industry professionals to be future ready. This paper describes the project approach, provides outlines of the training materials, and identifies lessons learned in creating the content for this course. The authors suggest ways to scale the instruction of smart building concepts to empower the workforce to accelerate the adoption of smart building technologies and AI-based teaching and learning in higher education and building sector.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Standard Library Plant Controller Model Specification for a Grid-Forming Hybrid Control Inverter-Based Resource (REPCGFM_C1)

This document describes a standard library plant controller model to interface with the grid-forming hybrid control inverter-based resource (IBR) model. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control algorithms to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Standard Library Grid-Forming Hybrid Control Inverter-Based Resource Model Specification (REGFM_C1)

This document describes a standard library grid-forming (GFM) hybrid control inverter-based resource (IBR) model. The GFM hybrid control approach implements both a typical GFM control and a typical grid-following (GFL) control inside one single inverter simultaneously, so that it can take advantage of both methods without comprising the benefits of a typical GFM. The initial version of model specification was jointly developed by Pacific Northwest National Laboratory (PNNL), Tesla Energy, and EPRI, and it was revised multiple times later to incorporate suggestions from WECC MVS members. Tesla Energy provided main control blocks to support the development of this model specification. This standard library model is developed to help the utility industry better understand the GFM technology. The model could be used to represent equipment for long-term planning studies where vendor-specific models are not available. As equipment matures and improves, standard library models will be updated to capture the new functionalities of GFMs. It is not intended that these models will always remain representative of all future GFM technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A combination interferometric and morphological image processing approach to rapid quality assessment of additively manufactured cellular truss core components

Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Here we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

7 Innovations in high-rate composite manufacturing: integrating additive manufacturing with compression molding process

Advanced composites play a pivotal role in modern engineering, offering exceptional strength-to-weight ratios and tailored properties, essential for various industries. High-rate composite manufacturing techniques have rapid production capabilities, which are essential for meeting the demands of industries requiring cost-saving, efficiency, and quick turnaround times. This chapter explores the Additive Manufacturing- Compression Molding (AM-CM) system developed by Oak Ridge National Laboratory (ORNL) for advanced composites manufacturing. The AM-CM system integrates additive manufacturing with compression molding, facilitating the production of polymer composite parts with superior mechanical properties and meticulously controlled microstructures. This innovative system not only ensures precise material deposition but also operates as a fast composite manufacturing process, enhancing productivity and performance, which are needed attributes across industrial applications. Through comprehensive mechanical testing and microstructural analysis, AM-CM promotes remarkable fiber alignment and reduced porosity in composite parts compared to alternative thermoplastic high-rate composite manufacturing methods. Furthermore, AM-CM enables overmolding reinforcement using continuous carbon fiber and supports selective reinforcement through customizable toolpaths. It also facilitates the production of hybrid materials to achieve tailored mechanical properties. Future advancements in AM-CM technology aim to enhance process efficiency, broaden material versatility, and improve part performance. This involves exploring novel materials, advancing process monitoring, implementing automation technologies, and integrating artificial intelligence (AI) and machine learning (ML) for predictive modeling and real-time optimization in composite manufacturing. These developments will establish the AM-CM system as a transformative technology in composite manufacturing, driving innovation across industries.

Hassen, Ahmed [ORNL] (ORCID:0000000328521222)↗
DOE OSTI2025

Refining Control, Charging, and Battery Chemistry for CO 2 e Savings in Heavy-Duty Off-Road Plug-In Series Hybrid

With current and future regulations continuing to drive reductions in carbon dioxide equivalent (CO 2 e) emissions in the on-road industry, the off-road industry is also likely to be regulated for fuel and CO 2 e savings. This work focuses on converting a heavy-duty off-road material handler from a conventional diesel powertrain to a plug-in series hybrid, achieving a 49% fuel reduction and 29% CO 2 e reduction via simulation. Control strategies were refined for energy savings, including a regenerative braking strategy to increase regenerative braking and a load-following hydraulic strategy to decrease electrical energy consumption. The load-following hydraulic control shuts off the hydraulic electric machine when it is not needed—an approach not previously seen in a load-sensing, pressure-compensated system. Furthermore, these strategies achieved a 24.1% fuel savings, resulting in total savings of 61% in fuel and 41% in CO 2 e in the plug-in series compared to the conventional machine. Beyond control strategies, this study evaluated battery chemistry and charging strategy refinements for total cost of ownership (TCO) and lifetime CO 2 e. LFP batteries emerged as the most cost-effective and least emitting due to their longer lifespan, which reduced replacement frequency. Charging comparisons showed that Level 2 charging (L2C) typically resulted in lower TCO but higher lifetime CO 2 e than DC fast charging (DCFC). DCFC costs were heavily influenced by local demand charges, and DCFC emissions were heavily influenced by local grid emissions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Review and Gap Analysis of Heliostat Components and Controls

This investigation provides a comprehensive literature review pertaining to heliostat components and controls as part of the U.S. Department of Energy (DOE), Heliostat Consortium (Heliocon) program. Here, this work presents a detailed assessment of subcomponents, controls and wireless communications elements that comprise various designs of helisotats within concentrating solar power (CSP) installations. Additionally, this work also provides the results of an industry survey, intended to compliment the literature discussion, to provide a gap analysis of the primary technology and cost areas that need to be addressed to help improved to spur concentrating solar power (CSP) bankability. Although the results of the study determined several key areas for development, three strategic areas identified were: (1) the use of advanced composite materials to replace a need for expensive steel within the structure and mirror substrate, (2) employment of closed-loop controls for automated calibration, reduction of commissioning time and O&M hours, reduction of drive requirements, as well as overall cost reduction, and (3) the need for more Heliostat-centric codes and standards to facilitate engineering confidence in the development of new features, cost reductions, or other design iterations to be seamlessly introduced without optical performance problems.

14 SOLAR ENERGY↗
DOE OSTI2020

Air pollution control strategies directly limiting national health damages in the US

Exposure to fine particulate matter (PM 2.5 ) from fuel combustion significantly contributes to global and US mortality. Traditional air pollution control strategies typically focus on emission reductions for specific air pollutants or sectors to maintain air pollutant concentrations within acceptable levels. Here we directly set national PM 2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, identifying endogenously the control actions, sectors, and locations that most cost-effectively reduce PM 2.5 mortality. Our results show that substantial health benefits can be cost-effectively achieved by using electricity to replace sources with high primary PM 2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. Increasing the stringency of PM 2.5 reduction targets expedites the phaseout of high emission intensity sources, leading to larger declines in major air pollutant emissions, but very limited co-benefits in reducing CO 2 emissions. Control strategies achieve the greatest mortality cost reductions in the East North Central and Middle Atlantic states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Depolymerizable and recyclable luminescent polymers with high light-emitting efficiencies

Luminescent polymers are of great interest in a number of photonic technologies, including electroluminescence, bioimaging, medical diagnosis, bio-stimulation and security signage. Incorporating depolymerizability and recyclability into luminescent polymers is pivotal for promoting their sustainability and minimizing their environmental impacts at the end of the product lifecycle, but existing strategies often compromise the light-emitting efficiencies. Here, in this study, we develop a strategy that utilizes cleavable moiety to create depolymerizable and recyclable thermally activated delayed fluorescence (TADF) polymers without compromising their high light-emitting efficiencies. The electroluminescent devices based on the TADF polymers achieved a high external quantum efficiency of up to 15.1 %. The TADF polymers can be depolymerized under either mild acidic or heating conditions, with precise control of the kinetics, and the obtained pure monomers can potentially be isolated and repolymerized for subsequent life applications. This work promotes the end-of-life environmental friendliness and circularity of luminescent materials, paving the way to a sustainable photonic industry. Developing depolymerizable and recyclable polymers with high light-emitting efficiencies is of vital importance for sustainable photonic technologies, but remains challenging. Here the authors design a strategy to develop such polymers based on the use of controllable cleavable moiety.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Building commissioning costs and savings across three decades and 1500 North American buildings

B.V. Building commissioning (Cx) is a process for assuring efficient building operations that can be applied to new construction and existing buildings, resulting in energy and non-energy benefits. Quantifying the benefits of commissioning is challenging, but a 2009 study of 643 commercial buildings provided a solid initial data set to which we added 839 additional buildings for a significantly expanded and updated meta-analysis representing 34.7 million square meters (373 million square feet) of floor area. Since 2009 the commissioning industry has continued to grow, driven by building codes, utility programs, and rising awareness of commissioning benefits. In parallel, building controls have become more sophisticated, and analytics software has emerged to assist with commissioning. We find that delivery mechanism and market segment are key determinants of outcomes, although significant and cost-effective savings are found across the spectrum. Median primary energy savings for Cx projects in existing buildings ranged from 5 percent for those conducted under utility programs, 9 percent for monitoring-based commissioning utility programs (i.e., augmented with submetering and diagnostics), and 14 percent for Cx projects outside of utility programs. Across all project types, median savings ranged from 3 percent for the lodging market segment to 16 percent for public order and safety facilities. Outcomes did not vary significantly by building size or by market segment. Energy savings are rarely estimated for new construction commissioning. We found that the median costs of Cx were lower for the 2018 sample than for the 2009 sample—$\$$2.85 per square meter ($\$$0.26 per square foot) for existing buildings (a 33 percent reduction) and $\$$8.78 per square meter ($\$$0.82 per square foot) for new construction (a reduction of almost 50 percent). The median simple payback time for existing buildings was 1.7 years, with a 25th–75th percentile range of 0.8–3.5 years. Overall, this article summarizes these and other key findings, and discusses how the 2018 data reflects shifts in commissioning practice and outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Synchrotron X-ray based particle image velocimetry to measure multiphase streamflow and densitometry

Synchrotron-based radiation techniques are increasingly used in the field of flow condition measurements. As a complicated multiphase flow, cavitation has been investigated in a wide variety of industrial fields, to prevent damages on spillways at large dams or intensify the bacteria eradication rate during water treatments. To control the detrimental effects of cavitating flows, the dynamics of and mechanisms affecting cavitation development shall be visualized and identified in real-time. Due to the large reflection and scattering effects of multiphase flow, standard visible-light imaging technologies cannot penetrate vapor bubbles and provide extremely limited information. In this study, the synchrotron source emitted high-flux X-ray pulses are used to capture flow motion and visualize internal structures with sufficiently high spatial and temporal resolutions. The image processing procedures on raw x-ray images are developed using 2D Fourier transform (FT) and wavelet transform (WT) to implement the contrast enhancement and de-noising. Through the edge detection algorithm, tracking either seeded particles or phase interfaces inside the opaque multiphase flow can be achieved to perform the particle image velocimetry. Further, with decomposing particle-only and particle-eliminated subplots from the X-ray phase-contrast image, the time-resolved velocity and void fraction fields are obtained simultaneously, paving a way for further flow condition analysis such as densitometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Analysis of biofilm assembly by large area automated AFM

Biofilms are complex microbial communities critical in medical, industrial, and environmental contexts. Understanding their assembly, structure, genetic regulation, interspecies interactions, and environmental responses is key to developing effective control and mitigation strategies. While atomic force microscopy (AFM) offers critically important high-resolution insights on structural and functional properties at the cellular and even sub-cellular level, its limited scan range and labor-intensive nature restricts the ability to link these smaller scale features to the functional macroscale organization of the films. We begin to address this limitation by introducing an automated large area AFM approach capable of capturing high-resolution images over millimeter-scale areas, aided by machine learning for seamless image stitching, cell detection, and classification. Large area AFM is shown to provide a very detailed view of spatial heterogeneity and cellular morphology during the early stages of biofilm formation which were previously obscured. Using this approach, we examined the organization of Pantoea sp. YR343 on PFOTS-treated glass surfaces. Our findings reveal a preferred cellular orientation among surface-attached cells, forming a distinctive honeycomb pattern. Detailed mapping of flagella interactions suggests that flagellar coordination plays a role in biofilm assembly beyond initial attachment. Additionally, we use large-area AFM to characterize surface modifications on silicon substrates, observing a significant reduction in bacterial density. This highlights the potential of this method for studying surface modifications to better understand and control bacterial adhesion and biofilm formation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unsupervised anomaly clustering via offset alignment in multivariate grid sensing data

Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online anomaly detection in electrical smart grids, where multivariate and multimodal sensing technologies play a vital role. However, detecting anomalies in such time-series data is challenging due to their inherent temporal dependencies and stochastic behavior. Traditional approaches based on supervised and semi-supervised learning methods depend on labeled datasets, which are often unavailable in real-world scenarios. While unsupervised methods have emerged as promising alternatives, these methods are highly susceptible to noise and outliers commonly present in sensing applications. Furthermore, deep learning-based anomaly detection methods, despite their performance, are often criticized for their black-box nature, limiting their applicability in safety-critical and online environments where interpretability and explainability are paramount. In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied to multivariate data collected from vibrational, voltage, and magnetic field sensors deployed in a local grid substation. Our results demonstrate the robustness of the algorithm in accurately clustering various anomalies/events across different sensing modalities. Additionally, we compare the effectiveness of the proposed approach against a simple pattern-based anomaly detection method, which performs well for univariate data but fails to generalize to multivariate and multimodal time-series data.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2022

Real-time Distribution Simulation and Application Development for Power Systems Education

To help bridge the gap between traditional power system engineering instruction and emerging industry needs, a new set of classroom and research tools are needed. Real-time simulation tools emulating power system control room software present an opportunity to introduce students to the array of operational considerations, technical challenges, and decision-making associated with power system operations. The GridAPPS-D platform is proposed to support coursework and academic research as it provides an open-source platform for simulation, application development, and software integration. The GridAPPS-D platform, simulation capabilities, development environment, and interactive training are discussed in the context of lessons-learned from implementation for undergraduate and graduate students in the US and India. A series of potential GridAPPS-D supported academic capabilities are introduced.

Active distribution networks, open educational res↗