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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2024

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

In support of DOE's H2@Scale initiative, this project leverages with national lab capabilities at SNL, NREL, and ANL with collaboration and funding cost share from California agencies (CEC, South Coast AQMD, and GO-Biz) to enable the build-out of heavy-duty (HD) hydrogen fueling stations with large dispensing capacity and high flow rates by providing tools and information that lead to more efficient design, acceptance, and commissioning. In this presentation, we describe the progress as related to the subtasks of: HD Reference Station Design, HD Station Test Device Design, and the Station Capacity Model.

AMR↗
DOE OSTI2023

Extension of Argonne’s Plant Dynamics Code (PDC) Capabilities to TerraPower Direct-Cycle Supercritical CO2 (“Pascal”) Nuclear Reactor Concept. Final CRADA report

Argonne National Laboratory (the Contractor) and TerraPower, LLC, (the Participant), entered into a Cooperative Research and Development Agreement (CRADA) to extend the Plant Dynamics Code (PDC) to model the Pascal reactor plant. PDC is the system-level computer code developed at Argonne, primarily for design and transient analysis of supercritical carbon dioxide (sCO2) energy conversion systems for various power plants. Pascal is a supercritical carbon dioxide (sCO2)-cooled direct-cycle nuclear power reactor under development by TerraPower. New features were added to the code to model components and systems specific to the Pascal plant and to make the code readily available as a tool for design, control, and safety analysis for this and other direct-cycle power plants. TerraPower provided design information of the Pascal reactor and the requirements for the development of the new PDC features. Argonne modified the PDC capabilities to introduce the new features.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Quantum Computing – Real-Time Data Processing from a Dilution Refrigerator

This poster presents a real-time data visualization system for monitoring and displaying data from a Bluefors control unit connected to a dilution refrigerator. The goal is to provide an aesthetically pleasing and user-friendly web-based interface that continuously updates and displays critical data such as temperature and flow rates at various points within the refrigerator. Leveraging WebSocket technology, the system establishes multiple connections to the dilution refrigerators, enabling simultaneous monitoring of several units. The interactive webpage dynamically updates the data, providing researchers and operators with instant insights into the system's performance. The system's ability to stream and visualize data in real-time enhances the understanding of the dilution refrigerator's behavior, aiding in optimizing its operation and ensuring efficient scientific experiments. The application's web-based nature makes it easily accessible from any device with internet connectivity, promoting seamless collaboration and remote monitoring capabilities. Overall, this poster offers a comprehensive solution for real-time data visualization and analysis of dilution refrigerators, catering to the needs of researchers and scientists working in low-temperature physics and quantum computing fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Overview/Recap of the 2020 Accelerated Irradiation of Reactor Structural Materials Workshop

The workshop provided a snapshot look at current international, in-reactor testing and irradiation capabilities. Gaps were identified where possible, and discussions focused on potential mitigation strategies and recommended paths forward. As new material innovations are being developed for in-reactor applications for reactor life extension long-term operation, and advanced reactor technologies, there is an increased need for materials qualification and assessment programs. In-reactor testing capabilities are vital to the on-going success of these DOE-NE programs and initiatives. In recent years, multiple international research reactors have been placed in a permanent shut-down state and have begun full decommissioning. These activities have created new risks in the delivery of on-going and/or expected research programs. Beyond performing simple irradiations in test reactors, few facilities exist internationally which can perform instrumented, in-situ irradiations on structural materials, and with the recent shut down of facilities hosted at Halden and NRU (example: instrumented fatigue loop, and in-situ creep), there are further gaps in the industry left un-filled. A new focus is being placed on the use of accelerator- based technologies to fill in some of these gaps, but these must be viewed as supplemental, and not surrogates to in-reactor capabilities

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Polycrystalline Thin-Film Research: Copper Indium Gallium Diselenide

Copper indium gallium diselenide (CIGS) solar cells are one of the primary focuses of research by the Thin Film Material Science and Processing Group. The group develops processes and materials related to thin-film polycrystalline photovoltaic (PV) devices as well as the equipment required for routine analysis of these devices and materials. We work closely with other groups in the Materials Science Center to achieve a deeper understanding of thin-film materials and devices.

capabilities↗
DOE OSTI2024

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the potential contributions of deep learning network architectures that employ stacked LSTM for end-of-season maize grain yield prediction. A secondary aim is to expand the capabilities of these networks by adapting them to better accommodate and leverage the multi-modality properties of remote sensing data. In this study, a multi-modal deep learning architecture that assimilates inputs from heterogeneous data streams, including high-resolution hyperspectral imagery, LiDAR point clouds, and environmental data, is proposed to forecast maize crop yields. The architecture includes attention mechanisms that assign varying levels of importance to different modalities and temporal features that, reflect the dynamics of plant growth and environmental interactions. The interpretability of the attention weights is investigated in multi-modal networks that seek to both improve predictions and attribute crop yield outcomes to genetic and environmental variables. This approach also contributes to increased interpretability of the model's predictions. The temporal attention weight distributions highlighted relevant factors and critical growth stages that contribute to the predictions. The results of this study affirm that the attention weights are consistent with recognized biological growth stages, thereby substantiating the network's capability to learn biologically interpretable features. Accuracies of the model's predictions of yield ranged from 0.82-0.93 R 2 ref in this genetics-focused study, further highlighting the potential of attention-based models. Further, this research facilitates understanding of how multi-modality remote sensing aligns with the physiological stages of maize. The proposed architecture shows promise in improving predictions and offering interpretable insights into the factors affecting maize crop yields, while demonstrating the impact of data collection by different modalities through the growing season. By identifying relevant factors and critical growth stages, the model's attention weights provide valuable information that can be used in both plant breeding and crop management. The consistency of attention weights with biological growth stages reinforces the potential of deep learning networks in agricultural applications, particularly in leveraging remote sensing data for yield prediction. To the best of our knowledge, this is the first study that investigates the use of hyperspectral and LiDAR UAV time series data for explaining/interpreting plant growth stages within deep learning networks and forecasting plot-level maize grain yield using late fusion modalities with attention mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

PMEL Passive Acoustics Research: Quantifying the Ocean Soundscape from Whales to Wave Energy

Passive acoustic monitoring of the global ocean has increased dramatically over the last decade, providing insights into seasonal sea ice and wind/wave variability, biodiversity, geophysical hazards, and anthropogenic noise impacts. All of these phenomena are sentinels of marine ecosystem health and ocean climate change. Recognizing the utility of underwater sound, the Pacific Marine Environmental Laboratory (PMEL) formed a passive acoustic research program with the goal of quantifying deep-ocean and coastal soundscapes in support of NOAA’s mission to conserve and manage marine ecosystems. PMEL Acoustics Program researchers have built a stable of novel ocean technologies, including autonomous stationary hydrophones, mobile platforms, and near-real-time surface buoys with satellite communication capability. These passive acoustic monitoring systems have been deployed in every major ocean basin on Earth, enabling significant advancements in understanding of natural and anthropogenic sounds. This progress includes evaluation of human-made sound levels across US waters, observations of ship noise fluctuations during the COVID-19 pandemic, and evaluation of noise levels from offshore wave-energy devices. Progress in natural sound research includes assessment of seasonal variability in the presence of endangered cetacean species due to population recovery and/or changing ocean temperatures as well as early detection of the collapse of an Antarctic ice shelf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Designing a Dynamic Material via Interlocking Kraft Lignin with Ultrahigh Molecular Weight Poly(ethylene oxide)

The environmental issues stemming from plastic waste and the excessive use of petroleum-based chemicals are both concerning and urgent. To effectively address this problem, we need to adopt a comprehensive approach involving developing more sustainable and renewable materials. These materials should be capable of demonstrating similar or even better performance than functional polymers synthesized from petroleum-based chemicals. Our research aims to develop more sustainable materials by leveraging the intrinsic characteristics of a natural polymer, lignin, a byproduct of the biorefinery industries. We utilized the three-dimensional branching structure of lignin as a material framework. We employed an approach to co-reactive melt processing of kraft lignin with aliphatic flexible chains of soft cross-linkers through the reaction of the cross-linker epoxy chain ends with lignin functional groups. Our study demonstrates that the interlocked structure formed from the co-blending of kraft lignin with ultrahigh molecular weight poly(ethylene oxide) and the cross-linking of lignin chains through a solvent-free process can manipulate the macromolecular interactions and relaxation. This manipulation results in materials that exhibit a wide range of thermomechanical properties and self-healing and shape memory effects, with drastically improved stiffness in a single material. We have explored the fundamental understanding of the macromolecular chain relaxation dynamics originating from the interlocking structure formation. In conclusion, this investigation utilized various techniques, including thermal, mechanical, rheology, and quasi-elastic neutron scattering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Porous Iron Electrodes Reduce Energy Consumption During Electrocoagulation of a Virus Surrogate: Insights into Performance Enhancements Using Three-Dimensional Neutron Computed Tomography

Electrocoagulation has attracted significant attention as an alternative to conventional chemical coagulation because it is capable of removing a wide range of contaminants and has several potential advantages. In contrast to most electrocoagulation research that has been performed with nonporous electrodes, in this study, we demonstrate energy-efficient iron electrocoagulation using porous electrodes. In batch operation, investigation of the external pore structures through optical microscopy suggested that a low porosity electrode with sparse connection between pores may lead to mechanical failure of the pore network during electrolysis, whereas a high porosity electrode is vulnerable to pore clogging. Electrodes with intermediate porosity, instead, only suffered a moderate surface deposition, leading to electrical energy savings of 21% and 36% in terms of electrocoagulant delivery and unit log virus reduction, respectively. Neutron computed tomography revealed the critical role of electrode porosity in utilizing the electrode’s internal surface for electrodissolution and effective delivery of electrocoagulant to the bulk. Energy savings of up to 88% in short-term operation were obtained with porous electrodes in a continuous flow-through system. Further investigation on the impact of current density and porosity in long-term operation is desired as well as the capital cost of porous electrodes.

42 ENGINEERING↗
DOE OSTI2022

Inverter Design with High Short-Circuit Fault Current Contribution to Enable Legacy Overcurrent Protection for Islanded Microgrids

The resiliency offered by a microgrid may be lost if the microgrid is not properly protected during short-circuit faults inside its boundaries. Many studies conclude that protecting microgrids in islanded mode is very challenging due to the limited short-circuit capability of distributed energy resources (DERs). The limited short-circuit capability of DERs typically inhibits the use of reliable and affordable overcurrent protective devices in microgrids. Although extensive research on microgrid protection is available in the literature, to date this research has not led to a cost-effective, commercially available relay that effectively tackles the challenges of microgrid protection. This work proposes hardware modifications to enhance the current contribution of an energy storage inverter with the objective of enabling the use of legacy overcurrent protection for islanded microgrids. This paper demonstrates through experimental results that few modifications are required in the inverter to significantly enhance its current contribution. In this study, a three-phase energy storage inverter was modified to provide three times its rated current during three-phase faults, which proved sufficient current for enough time to enable fuse-relay, and relay-to-relay coordination. The proposed modifications effectively increase the current contribution of the inverter, which is a promising advancement to allow the adoption of overcurrent protective devices for protecting microgrids.

Ferrari Maglia, Max↗
DOE OSTI2022

Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case

solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.

14 SOLAR ENERGY↗
DOE OSTI2023

Reposcanner

SAND2023-05455O Reposcanner provides a highly modular, extensible framework for defining routines for mining data from software repositories and performing analyses on that data to yield valuable insights on team behaviors. Reposcanner features seamless support for different version control platforms like GitHub, Gitlab, and Bitbucket; smart parsing of URLs; intelligent credential management capabilities; and a comprehensive test suite. Reposcanner is connected to the Exascale Computing Project and is intended for research purposes.

Mundt, Miranda↗
DOE OSTI2020

Advanced Sensors and Instrumentation (ASI) Program Plan. Nuclear Energy Enabling Technologies (NEET)

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) sponsors a crosscutting technology development (CTD) program addressing common instrumentation & controls (I&C) needs in all DOE-NE sponsored programs. In 2012, DOE-NE initiated the Nuclear Energy Enabling Technology (NEET) Program to conduct research, development, and demonstration (RD&D) in crosscutting technologies that directly support and enable the development of existing, new and advanced reactor designs, and fuel cycle technologies. These technologies will advance the state of nuclear technology, improve its competitiveness, and promote continued contribution to meeting our Nation’s energy and environmental challenges. The NEET Program has spurred innovation in the field of sensors and instrumentation, advanced methods for manufacturing, and cyber security. The Advanced Sensors and Instrumentation (ASI) program is one element of the NEET CTD that has spurred innovation in the measurement science field by funding research on sensors, instrumentation and controls, communication, and advanced analytics that measure system parameters, gauge component control input, and provide power plant owners and operators critical awareness so they can plan and safely manage operational evolutions. The NEET ASI Program has carried out research and development (R&D) required to develop and deploy innovative and advanced sensors, and instrumentation and control capabilities for current and future nuclear energy systems, and to enable the advanced technologies essential to NE’s R&D efforts needed to realize mission goals. The concept of technology readiness assessment is helpful for the classification of instrumentation technology as part of the program strategy. A technology readiness assessment evaluates technology maturity using the Technology Readiness Level (TRL) scale and was pioneered by the National Aeronautics and Space Administration in the 1980s for space technology. It has recently been adopted to advance fuels and materials. The NEET ASI program objective is to mature instruments technology to TRL 6, which is “demonstration of the technology in relevant environment.” While there may be instances in which a different strategy is justified, the aim of the program is to respond to DOE program and stakeholder needs for nuclear instrumentation then hand off the technology after demonstration for integration in a more complex system, for example an irradiation test, experimental loop or a plant component such as the core, primary system or heat exchanger. A mechanism to continue some level of support from NEET ASI during and after the adoption (for example, to maintain fabrication and calibration capabilities) will be defined as the first example of technology hand off comes to fruition. In addition, several paths exist within DOE to complement NEET ASI activities to extend the maturity beyond TRL, for example through GAIN, technology commercialization funding, and small-business programs. Role of NEET ASI CINR projects in the TRL space, and integration with direct funded demonstration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Active Irradiation Testing of Temperature Sensing Capability of Clad Sapphire Optical Fibers with Type 2 Bragg Gratings using Optical Backscatter Reflectometry

This work investigated the temperature-sensing capabilities of Type II fiber Bragg gratings (FBGs) inscribed in sapphire optical fiber in the Ohio State University Research Reactor (OSURR). A Luna Innovations 4600 optical backscatter reflectometer (OBR) was used to interrogate FBGs in three sapphire optical fibers with an internal cladding that was developed by Ohio State. The sapphire fibers were fusion-spliced to silica lead fibers. In addition to the sapphire fibers, two silica fibers with the same Type II FBGs were included in the experiment as a reference. The fiber-based sensors were irradiated in the Central Irradiation Facility (CIF) of the OSURR for a total of 40 hours over 5 days at a reactor power of 450 kW, resulting in a total neutron fluence of approximately 2.5 × 10 18 n/cm 2 and a gamma dose of approximately 3.48 Grad. Two K-type thermocouples were included within the rig: one at the core centerline and the other 12 inches above the top of the core. The temperature was not actively controlled, but the thermocouples were used to provide a reference to which the fiber-based temperature measurements could be compared.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Examination of the Extreme Cold Weather Event Affecting the Power System in Texas - February 2021 [Slides]

This presentation examines the extreme cold weather event that affected the power system in Texas in February 2021. The Texas load-shedding events were caused by a combination of record-high demand and cold weather issues that reduced the output from all types of generation. While some wind turbines were shutting down due to cold temperatures and icing and a lack of cold-weather packages, hourly wind output was accurately predicted. Extreme weather events historically drive grid reliability. Additional examination of more extreme events is needed to understand their impacts on the power system. As a national lab, NREL has the capabilities and facilities to help the industry address these types of challenges. NREL also has significant simulation and analysis capabilities (such as NAERM) that can help understand the impacts of extreme events. NREL also developed the Advanced Research on Integrated Energy Systems (ARIES) Research Platform, which enables evaluation of technologies that smooth grid operations during events like this.

17 WIND ENERGY↗
DOE OSTI2020

Final Report for Tech-X Corporations’s contribution to Enhancing Understanding of High Energy Density Plasmas from Wire Array and Solid Liner Implosions Using Fluid Modeling with Kinetic Closures

Recent results from experiments and simulation of magnetically driven pulsed power liners have explored the role of the early-time electrothermal instability in the evolution of the magneto-Rayleigh-Taylor instability. Our focus will be on understanding the development of such instabilities and the potential stabilization mechanisms via electron thermal conduction, viscosity, and large magnetic fields which we expect could play a significant role in supporting the success of the MagLIF program. Experiments have shown that studies of high-energy density plasmas from wire-array implosions require physics modeling that goes well beyond simple models such as ideal magnetohydrodynamics. The goal of this work is to provide increased understanding of these experiments by employing simulations with a multi-fluid extended-MHD model which uses kinetic closures for thermal conduction, resistivity and viscosity. We will use codes easily available to the wider research community, including university students, with a secondary goal of providing the community with well-benchmarked tools capable of advanced modeling of high-energy-density plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗