Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “technology performance level”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tunable Rapid Uptake Amino Polymer Aerogels for Direct Air Capture of Carbon Dioxide (Final Scientific/Technical Report)

The Palo Alto Research Center (PARC) developed a novel CO 2 adsorbent material, and in collaboration with Lawrence Livermore National Laboratory (LLNL), demonstrated its state-of-the-art performance for direct air capture. The target application for this technology is in direct air carbon capture and storage (DACCS), for which the adsorbent material provides the critical function of binding CO 2 from ambient air. At the beginning of the project, the technology concept and application were established, representing technology readiness level (TRL) 2. The hypothesis was that a microporous polymer comprising a high density of primary amines would make an exceptional adsorbent for direct air capture, and the goal of the project was to prove that hypothesis and advance the technology to TRL 3. To accomplish this, we approached the challenge from the perspective of materials synthesis optimization with the narrow focus of achieving the target material properties. This approach was successful, and we now have a synthetic procedure that results in a novel adsorbent material with the target material properties. The chemical name for the novel adsorbent material is poly(vinylamine-co-divinylbenzene) (PVAm-DVB).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

NG-CT Peaker Upgrades with Bottoming Cycle: Preliminary Analysis

The National Energy Technology Laboratory (NETL) has conducted a preliminary analysis exploring a significant opportunity to increase the nation's power grid capacity and reliability. The study focuses on retrofitting under-utilized natural gas combustion turbines (NG-CTs), often called "peaker" plants, with a bottoming cycle to capture waste heat and generate additional electricity. This analysis shows that upgrading these existing assets could add approximately 26,250 MW of new power capacity across the United States. A detailed study of the PJM Interconnection, the nation's largest grid operator, confirmed the benefits of these upgrades. Key findings for the PJM region include: - A median increase in the plants' capacity factor by 17 percentage points. - A projected 36.2% median reduction in the levelized cost of electricity (LCOE) for the upgraded plants, with nearly 88% of them expected to break even. - An average reduction in the regional wholesale price of electricity by approximately 3.0% in the year 2030. - A significant boost to grid reliability, with a 46% reduction in projected Loss of Load Hours (LOLH). These findings suggest that retrofitting peaker plants is a promising and economically viable strategy to enhance grid performance, reduce electricity costs, and meet future demand without the challenges associated with building entirely new facilities.

bottoming cycle↗
DOE OSTI2022

Proton-Mediated and Ir-Catalyzed Iron/Iron-Oxide Redox Kinetics for Enhanced Rechargeability and Durability of Solid Oxide Iron–Air Battery

Long duration energy storage (LDES) is an economically attractive approach to accelerating clean renewable energy deployment. The newly emerged solid oxide iron–air battery (SOIAB) is intrinsically suited for LDES applications due to its excellent low-rate performance (high-capacity with high efficiency) and use of low-cost and sustainable materials. However, rechargeability and durability of SOIAB are critically limited by the slow kinetics in iron/iron-oxide redox couples. Here the use of combined proton-conducting BaZr 0.4 Ce 0.4 Y 0.1 Yb 0.1 O 3 (BZC4YYb) and reduction-promoting catalyst Ir to address the kinetic issues, is reported. It is shown that, benefiting from the facilitated H + diffusion and boosted FeOx-reduction kinetics, the battery operated under 550 °C, 50% Fe-utilization and 0.2 C, exhibits a discharge specific energy density of 601.9 Wh kg –1 -Fe with a round-trip efficiency (RTE) of 82.9% for 250 h of a cycle duration of 2.5 h. Under 500 °C, 50% Fe-utilization and 0.2 C, the same battery exhibits 520 Wh kg –1 -Fe discharge energy density with an RTE of 61.8% for 500 h. This level of energy storage performance promises that SOIAB is a strong candidate for LDES applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Particle flow reconstruction for the CMS Phase-II Level-1 Trigger

The upgrade of the CMS detector for the high-luminosity LHC will include trackfinding for the first time in the Level-1 trigger, enabling Particle Flow reconstruction of every event in addition to comprehensive pileup mitigation. The Correlator trigger will reconstruct isolated leptons and photons, hadronic jets, and energy sums, assisted in many cases by machine learning to benefit from the complete particle-level event record. Here, we present the logic of these algorithms, possible implementations using large FPGAs and their demonstration in prototype hardware, in addition to the expected physics performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Strategic National Level Exercises Program White Paper - Draft

The general objective of this white paper is to share lessons learned and provide interdisciplinary recommendations on how to use NLE to evaluate, assess and improve national nuclear security regimes. The specific objectives of this white paper are: — To describe the type of exercises, benefits and requirements — To outline the different capacity areas and capability performance levels — To provide concrete and actionable recommendations to INS’s partners on how to use NLE to improve national nuclear security regimes.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

EBSD of Rough Native CuInGaSe2 Thin-Films

The polycrystalline Cu (In, Ga) Se2, or CIGS, based thin-film materials system has long been studied for use in photovoltaic technologies, where its bandgap tunability, mechanical flexibility, and relatively low production costs are all appealing. Nonetheless, significant defect populations, which serve to reduce efficiency, create performance instabilities, and increase concerns about long-term reliability, have hindered wide-scale adoption. Prior work, including application of a scanning probe based deep level trap spectroscopy (SP-DLTS) defect mapping technique and scanning transmission electron microscope (STEM) based electron energy loss spectroscopy (EELS), has shown that the most detrimental defects, with energy level near mid-gap (thus serving as a carrier recombination center), are most likely caused by CuIn/Ga antisites and tend to cluster at or around certain grain boundaries [1,2]. However, the exact nature of these particular boundaries — their structures, chemistries, or even the relative misorientation of their associated grains — and their relation to this defect clustering and/or its formation is yet unknown. As such, electron backscatter diffraction (EBSD) orientation mapping, directly correlated with defect-sensitive techniques like SP-DLTS and/or STEM-EELS, could prove critical for providing the final missing links toward understanding the mechanisms behind these defects. Indeed, recent studies using correlative electron beam induced current (EBIC) with EBSD have been able to identify boundaries, and their relative misorientations, that possess detrimental electronic properties [3]. However, because EBIC is unable to resolve the defect energy levels, many questions are left unanswered. Furthermore, this study, and others like it, employed focused ion beam (FIB) milling to flatten the natively-rough CIGS [3-5], which may run the risk of changing the nature of any near-surface defect structures.

14 SOLAR ENERGY↗
DOE OSTI2022

Field-Deployable Quantum Memory for Quantum Networking

High-performance quantum memories are an essential component for regulating temporal events in quantum networks. As a component in quantum-repeaters, they have the potential to support the distribution of entanglement beyond the physical limitations of fiber loss. This will enable key applications such as quantum key distribution, network-enhanced quantum sensing, and distributed quantum computing. Here, we present a quantum memory engineered to meet real-world deployment and scaling challenges. The memory technology utilizes a warm rubidium vapor as the storage medium, and operates at room temperature, without the need for vacuum- and/or cryogenic- support. Here, we demonstrate performance specifications of high-fidelity retrieval (95%) and low operation error (10 –2 ) at a storage time of 160 µs for single-photon level quantum memory operations. We further show a substantially improved storage time (with classical-level light) of up to 1ms by suppressing atomic diffusions. The device is housed in an enclosure with a standard 2U rackmount form factor, and can robustly operate on a day scale in a noisy environment. This result marks an important step toward implementing quantum networks in the field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Center for Tokamak Transient Simulations (RPI Unstructured Mesh Developments for FES SciDAC4 Partnerships) (Final Report)

The goal of this project was the development of unstructured mesh technologies for fusion simulation codes” for FES SciDAC partnerships and to integrate those technologies into the simulation workflows of those partnerships. Specific developments were executed in support of the following FES SciDAC4 partnerships: Partnership Center for High‐fidelity Boundary Plasma Simulation (HBPS), Center for Integrated Simulation of Fusion Relevant RF (RF‐SciDAC), Center for Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces (PSI2), and Center for Tokamak Transient Simulations (CTTS). The key unstructured mesh development areas addressed in this project include (i) methods to most effectively perform PIC calculations on unstructured meshes; (ii) creating meshes for fusion systems accounting for any desired level of geometric complexity and providing physics aware mesh configurations, (iii) adapting unstructured meshes to control the discretization errors, (iv) executing unstructured mesh calculations on GPU accelerated systems, (v) supporting physics/application‐specific PIC operations including surface/wall interactions of particles, (vi) providing infrastructure tools to support the interactions of solvers with unstructured meshes, and (vii) providing advanced methods for coupling plasma physics codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Igiugig Site Visit Report

The National Renewable Energy Laboratory (NREL) team conducted a site visit during January 23-25, 2019 with the Igiugig Village Council (IVC) and other stakeholders to assist the community of Igiugig in refining their long-term energy strategy. The agenda included a tour of the village, data collection, presentations, long-term visioning exercises, identification of energy scenarios, and a school presentation. Participants in the site visit activities spanned a range of local, regional, government, and industry participation. There were 24 attendees at the all-day community workshop on Thursday, January 24th, with participants from the IVC, NREL, Bristol Bay Native Association (BBNA), Bristol Bay Native Corporation (BBNC), Lake and Peninsula Borough, Alaska Energy Authority, Intergrid, ORPC, Deer Stone Consulting, the Southwest Alaska Municipal Conference, and University of Alaska Fairbanks - Alaska Center for Energy and Power. Igiugig is a well-organized rural Alaskan community, with a leadership team that appears to have broad community support. The use of consensus-based decision making is one tangible example of how the leadership team actively invokes and promotes community-focused thinking. The NREL team observed anecdotal evidence of how this approach seems to be strengthening the community: active participation in the visioning exercise, a student hosted fund-raiser dinner at the school, a clean and organized landfill, and well-maintained roads and buildings. Igiugig has wind, solar, and river hydrokinetic resources readily available within the community. Wind has shown to be a promising resource in the region, and has been integrated into microgrids around the state, but the community has had mixed success with wind technologies: some devices failed quickly and others continue to operate. The economics of solar energy are improving in Alaska, and economical solar projects are being installed around the state. Considering that economic activity in Igiugig peaks during the summer sport fishing season, solar could prove to be a valuable supplement to the electrical system. Igiugig has been a test site for two different river hydrokinetic devices, and they have began a third project to operate ORPC's RivGen device, which is delivering valuable device performance data, operations and maintenance experience, and design refinement information. Already, this device has made over 7-million revolutions, and delivered over 8 MWh of power to the community. Igiugig's river resource is fairly unique because it is available year-round and has the potential to provide reliable base-load power for months at a time. A preliminary investigation of this diverse resource mix suggests that Igiugig could achieve very high levels (70% or more) of annual renewable generation contributions. A critical step in pursuing this path is identifying the mix of energy assets (generation and storage) that best meets the community's budget, needs, and goals. The assets that a community installs early in their grid-modernization initiative can constrain the options that are economical at later stages, which may lead to sub-optimal solutions. This is where technical and economic analysis of potential scenarios (i.e., distinct mixes of energy assets) can be useful in identifying the most promising pathways so that a community can make informed and strategic decisions about the assets they install. These analyses are most accurate and informative when they are based on actual technology performance and cost data. As the RivGen project continues to operate and generate this data, we will be better prepared to evaluate the technology's long-term viability and to identify research areas that would improve it. Igiugig's energy projects are at the cutting edge of two intersecting technology areas: 1) deploying an operational river hydrokinetic turbine, and 2) integrating renewable energy sources to achieve very high percent renewables. If these projects are successful, the lessons learned and technologies developed could be valuable for other microgrids around the world. Igiugig's unique resource mix make it an ideal location for this work, and the community's organizational strength make it an ideal partner in this ground-breaking work. Ongoing support for technical assistance to manage and address technical challenges along the way will maximize the probability of project success.

13 HYDRO ENERGY↗
DOE OSTI2023

System design and prototyping for the CMS Level-1 Trigger at the High-Luminosity LHC

For the High-Luminosity Large Hadron Collider, the trigger and data acquisition system of the CMS experiment will be entirely replaced. Novel design choices have been explored, including ATCA prototyping platforms with SoC controllers and newly available interconnect technologies with serial optical links with data rates up to 28 Gb/s. Trigger analyses will be performed through sophisticated algorithms, including widespread use of Machine Learning, in large FPGAs, such as the Xilinx Ultrascale family. The system will process over 50 Tb/s of detector data with an event rate of 750 kHz. Here, we describe system design and prototyping and review trigger algorithm exemplars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System: Preprint

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, The prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site- specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de- risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves. For the Spanish version of this report, see NREL/CP-5700-88482 (https://www.nrel.gov/docs/fy24osti/88482.pdf).

deployment↗
DOE OSTI2026

Towards Generalizable and Efficient Circuit Topology Design: A Graph-Transformer-based Surrogate Model with Curriculum Learning

Unlike circuit parameter and sizing optimizations, the automated design of analog circuit topologies poses significant challenges for learning-based approaches. One challenge arises from the combinatorial growth of the topology space with circuit size, which limits the topology optimization efficiency. Moreover, traditional circuit evaluation methods are time-consuming, while the presence of data discontinuity in the topology space makes the accurate prediction of circuit performance exceptionally difficult for unseen topologies. To tackle these challenges, we design a novel Graph-Transformer-based Network (GTN) as the surrogate model for circuit evaluation, offering a substantial acceleration in the speed of circuit topology optimization without sacrificing performance. Our GTN model architecture is designed to embed voltage changes in circuit loops and current flows in connected devices, enabling accurate performance predictions for circuits with unseen topologies. To address the cold start problem when scaling GTN to large-scale circuits, we further introduce a curriculum learning strategy that progressively trains GTN from small-scale to large-scale circuits. This approach enables the model to first learn fundamental physical principles from simpler topologies and gradually adapt to complex configurations, effectively bridging the circuit complexity gap and improving prediction accuracy. Taking the power converter circuit design as an experimental task, our GTN model significantly outperforms an analytical approach and baseline methods directly utilizing graph neural networks. Furthermore, GTN achieves less than 5% relative error and 196× speed-up compared with high-fidelity simulation. Notably, our GTN surrogate model empowers an automatic circuit design framework to discover circuits of comparable quality to those identified through high-fidelity simulation while reducing the time required by up to 98.2%. With curriculum learning, the enhanced GTN achieves a 51% improvement for performance prediction of large-scale circuits compared to the GTN model without this strategy. These advancements establish GTN as a scalable framework for automated analog circuit design across varying circuit complexity levels.

Lu, Haoshu [New Jersey Institute of Technology (NJ↗
DOE OSTI2025

Reservoir Dynamics in Proposed Operational Scenarios Where CO 2 -EOR Fields are Transitioned From CO 2 -Flood Enhanced Oil Recovery to Dedicated Carbon Storage: A Field Case Study

This study models the transition of CO 2 -enhanced oil recovery (CO 2 -EOR) fields to dedicated carbon storage using a generalized reservoir model informed by real field data, SACROC. Through scenario-based simulations, the work evaluates how reservoir depletion levels, boundary conditions, fluid properties, and domain size affect pressure buildup, CO 2 plume migration, and long-term containment performance. The results inform practices for repurposing oil fields into reliable CO 2 storage sites.

02 PETROLEUM↗
DOE OSTI2022

Optical Transmission Characterization of Fused Silica Materials Irradiated at the CERN Large Hadron Collider

The Target Absorbers for Neutrals (TANs) represent one of the most radioactive regions in the Large Hadron Collider (LHC). Seven 40 cm long fused silica rods with different dopant specifications, manufactured by Heraeus, were irradiated in one of the TANs located around the ATLAS experiment by the Beam RAte of Neutrals (BRAN) detector group. This campaign took place during the Run 2 p+p data taking, which occurred between 2016 and 2018. This paper reports a complete characterization of optical transmission per unit length of irradiated fused silica materials as a function of wavelength (240 nm - 1500 nm), dose (up to 18 MGy), and level of OH and H$_2$ dopants introduced in the manufacturing process. The dose delivered to the rods was estimated using Monte Carlo simulations performed by the CERN FLUKA team.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Colloidal Quantum Dot Solar Cells: Progressive Deposition Techniques and Future Prospects on Large-area Fabrication

Colloidally grown nanosized semiconductors yield extremely high-quality optoelectronic materials. Many examples have pointed to near perfect photoluminescence quantum yields, meaning non-radiative optical processes (losses) can be completely suppressed allowing for technology-leading materials as high purity color centers in display technology and emitters in LEDs. Furthermore, because of high chemical yield, and improved understanding of the surfaces, these materials, particularly colloidal quantum dots (QDs) can also be ideal candidates for other optoelectronic applications. Given the strong drive toward carbon neutrality and limiting climate change, electricity from solar photovoltaics will play a large role in the power generation sector. QDs have been developed and shown dramatic improvements over the past 15 years as photoactive materials in photovoltaics and have unique potential with various innovative deposition properties which could lead to exceptionally low-cost and high-performance devices. Once the key issues related to charge transport in optically thick arrays are addressed, QD-based photovoltaic technology could become a better candidate for practical application. In this article, w e show how the possibilities of different deposition techniques could bring QD-based solar cells to the industrial level and discuss the challenges for perovskite QD solar cells in particular, to achieve large-area fabrication for further advancing technology to solve pivotal energy and environmental issues.

14 SOLAR ENERGY↗
DOE OSTI2023

On dysprosium utilisation in multi-main-phase Nd–Dy–Fe–B magnets with core–shell microstructures

The development of high-performance Nd–Dy–Fe–B magnets that minimise the consumption of the scarce rare earth (RE) element Dy remains a major global scientific and technological quest. Here, we designed an alloy microstructure comprising of a uniform Dy-lean core–Dy-rich shell in a series of multi-main-phase (MMP) Nd–Dy–Fe–B magnets. The resulting MMP Dy1 and Dy3 magnets with an overall Dy level of 1 and 3 wt.% possessed values of 0.48 and 0.29 T/wt.% of coercivity increment per unit weight percentage of the Dy addition, respectively. Most importantly, the resulting MMP Dy3 magnet exhibited a high coercivity (2.38 T), an excellent thermal stability of the coercivity (|β| = 0.531%/°C), a high squareness factor (> 95%), all with little diminishment in the remanent magnetisation (1.35 T) and maximum energy product (43.6 MGOe). These properties are superior to the currently available sintered Nd–Dy–Fe–B magnets which utilise higher levels of Dy of 5 wt.%. Via magnetic and multi-scale microstructural characterisation experiments and micromagnetic simulations, the formation of the Dy-lean core–Dy-rich shell microstructure is rationalised via solid-state-diffusion and solution reprecipitation during liquid-phase sintering. The Dy-lean core–Dy-rich shell microstructure and the non-ferromagnetic low-Fe RE-rich grain boundary phase led to the synergistic magnetic performance. This is significant in the context of the MMP Nd–Dy–Fe–B magnets being applied to large-scale production. The present work establishes a pathway for the more sustainable utilisation of Dy in permanent magnets via formation of a uniform core–shell microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Model-based economic analysis under uncertainty for PFAS treatment by granular activated carbon and ion exchange technologies

Recent drinking water regulations have imposed the need for per- and polyfluoroalkyl substances (PFAS) remediation. In response, treatment facilities may be required to retrofit existing treatment schemes to treat PFAS below maximum contaminant levels (MCLs). Adsorption technologies such as granular activated carbon (GAC) and ion exchange (IX) have been demonstrated to be effective; however, there are limited techno-economic metrics available which provide guidance on technology selection and design for diverse PFAS-containing source water conditions. Process systems engineering (PSE) tools which can traditionally perform these analyses are hindered by the data availability, model validity, and understanding of treatment phenomena for emerging contaminants. This work employs published data regressions, statistical models, process models, techno-economic analyses, and other process systems tools in a model-based uncertainty framework to consider the limitations of emerging contaminant research. Through this analysis framework, economic results are provided as probabilistic distributions based on the uncertainty of the models and diverse conditions that treatment facilities experience.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗