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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Experimental Investigation of Turbine Vane Heat Transfer for Alternative Fuels

The focus of this program was to experimentally investigate advanced gas turbine cooling schemes and the effects of and factors that contribute to surface deposition from particulate matter found in coal syngas exhaust flows on turbine airfoil heat transfer and film cooling, as well as to characterize surface roughness and determine the effects of surface deposition on turbine components. The program was a comprehensive, multi-disciplinary collaborative effort between aero-thermal and materials faculty researchers and the Department of Energy, National Energy Technology Laboratory (NETL). The primary technical objectives of the program were to evaluate the effects of combustion of syngas fuels on heat transfer to turbine vanes and blades in land-based power generation gas turbine engines. The primary questions to be answered by this investigation were; What are the factors that contribute to particulate deposition on film cooled gas turbine components? An experimental program was performed in a high-temperature and pressure combustion rig at the DOE NETL; What is the effect of coal syngas combustion and surface deposition on turbine airfoil film cooling? Deposition of particulate matter from the combustion gases can block film cooling holes, decreasing the flow of the film coolant and the film cooling effectiveness; How does surface deposition from coal syngas combustion affect turbine surface roughness? Increased surface roughness can increase aerodynamic losses and result in decreased turbine hot section efficiency, increasing engine fuel consumption to maintain desired power output. Convective heat transfer is also greatly affected by the surface roughness of the airfoil surface; Is there any significant effect of surface deposition or erosion on integrity of turbine airfoil thermal barrier coatings (TBC) and do surface deposits react with the TBC in any way to decrease its thermal insulating capability? Spallation and erosion of TBC is a persistent problem in modern turbine engines; and What advancements in film cooling hole geometry and design can increase effectiveness of film cooling in turbines burning high-hydrogen coal syngas due to the higher heat loads and mass flow rates of the core flow? Experimental and numerical investigations of advanced cooling geometries that can improve resistance to surface deposition were performed. The answers to these questions were investigated through experimental measurements of turbine blade surface temperature and coolant coverage (via infrared camera images and thermocouples) and time-varying surface roughness in the NETL high-pressure combustion rig with accelerated, simulated surface deposition and advanced cooling hole concepts, coupled with detailed materials analysis and characterization using conventional methods of Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-Ray Diffraction (XRD), 3-D Surface Topography (using a 3-D stylus profilometer). Detailed surface temperatures and cooling effectiveness could not be measured due to issues with the NETL infrared camera system. In collaboration with faculty startup funding from the principal investigator, experimental and numerical investigations were performed of an advanced film cooling hole geometry, the anti-vortex hole (AVH), focusing on improving cooling effectiveness and decreasing the counter-rotating vortex of conventional cooling holes which can entrain mainstream particulate matter to the surface. The potential benefit of this program is in gaining a fundamental understanding of how the use of alternative fuels will effect the operation of modern gas turbine engines, providing valuable data for more effective cooling designs for future turbine systems utilizing alternative fuels.

10 SYNTHETIC FUELS↗
DOE OSTI2017

2014 Navajo Nation Energy and Water Consumption

The Navajo Nation is the home of the largest land-based Indian reservation in the U.S., covering more than twenty-seven thousand square miles. The land in the southwestern U.S. holds an abundance of natural resources, which are intimately integrated in the history, economy, and growth of the Navajo tribe. This report aims to wholly visualize the Navajo Nation’s resources and energy and water consumption using quantitative data and systems engineering analysis. The energy and water flow chart visualizations provide structured information for tribal leaders, policymakers, and educators around energy and water system discussions, technology development opportunities, and policy decisions. The analysis of both energy and water is a first step to visualizing the interconnectedness and complexities of the energy-water-food nexus of the nation. The goal of this energy analysis was to first estimate coal resource consumption because of the considerable impact coal has on the Navajo economy, recently as much as $26 million per year in coal royalties.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

ATOM - Accelerating therapeutics through opportunities in medicine

Create a new paradigm of drug discovery that would reduce the time from an identified drug target to clinical candidate from the current ~6 years to just 12 months. ATOM will develop, test, and validate a multidisciplinary approach to drug discovery in which modern science, technology and engineering, supercomputing, simulations, data science, and artificial intelligence are highly integrated into a single drug-discovery platform that can ultimately be shared with the drug development community at-large.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Frontiers of Materials Research: A Decadal Survey

Modern materials science builds on knowledge from physics, chemistry, biology, mathematics, computer and data science, and engineering sciences to enable us to understand, control, and expand the material world. Although it is anchored in inquiry-based fundamental science, materials research is strongly focused on discovering and producing reliable and economically viable materials, from super alloys to polymer composites, that are used in a vast array of products essential to today’s societies and economies. Frontiers of Materials Research: A Decadal Survey is aimed at documenting the status and promising future directions of materials research in the United States in the context of similar efforts worldwide. This third decadal survey in materials research reviews the progress and achievements in materials research and changes in the materials research landscape over the last decade; research opportunities for investment for the period 2020-2030; impacts that materials research has had and is expected to have on emerging technologies, national needs, and science; and challenges the enterprise may face over the next decade.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Roadmap for thermal property measurements of Molten Salt Reactor systems

Thermal properties of molten salts, both with and without fissile and fertile material, are fundamental to modeling and simulation that supports design, construction, operation, and accident progression evaluation of molten salt reactors. This roadmap provides guidance to the research community on the types and amounts of required data for base, or carrier, salt systems, recommends simulated burnup fuel salt compositions to evaluate, and provides a technical foundation for a focused salt property evaluation matrix. The property values generated from both computation and experimental methods are used to develop models that constitute the Molten Salt Thermal Properties Database (MSTDB). While the building blocks of MSTDB are fundamental in nature, its data facilitates constructing engineering models that allow stakeholders to investigate the behavior of specific compositions of interest and supports broader modeling and simulation of MSRs through coupling to multi-physics, multi-scale mass accountancy tools.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance

The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Cell-free bioelectrocatalytic platform for carbon dioxide reduction (Final Technical Report)

The University of Minnesota (UMN) EcoSynBio Team aimed to develop a cell-free, enzyme-based platform for the electro- biocatalytic conversion of CO2 into formate as a platform chemical for further upgrading. This type of bio electrocatalytic process delivers a clean product stream without the need for extensive separation from the electrolyte as in electrochemical synthesis and microbial processes. The reduction reaction is catalyzed by metal-dependent formate dehydrogenases (mFDHs) that are capable of efficient electrocatalytic CO2 reduction without the need of costly co-factors. The development of an efficient, scalable electrobiocatalytic process with high total turnover numbers and viable space time yields, however, was not without its challenges. The UM team has developed a protein-based scaffolding system that facilitates enzyme stabilization and attachment to electrodes along with electron transfer. Yet, although FDHs are highly promising enzymes for cell-free, electrobiochemical CO2 reduction, they are also greatly understudied and especially for applications in electrocatalysis. The UM team used the best described mFDH from Clostridium as its benchmark system and spent significant time and effort in attempting to replicate published data and finally, redesigned a recombinant production system for proper metal co-factor incorporation. The UM team has also identified a small set of new enzyme homologs from extreme microorganisms with superior stabilities that have yielded initial structural data for further engineering. In addition, a new bioelectrocatalytic reactor system has been developed that can be 3D printed and used for enzyme attachment to electrodes. In summary the project has generated critical basic information for the further development of this class of enzymes for the electricity driven reduction of CO2 into formate as platform chemical for upgrading into various other chemicals, including fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Preproduction Using Automated Process Design

A new approach to the computer-assisted design (CAD) of machining processes is outlined. Mathematical apparatus for the solution of standard problems is proposed, and the source code for its implementation is developed. The source code for an experimental CAD system is developed. An interactive graphical input is used for dimensional data.

42 ENGINEERING↗
DOE OSTI2019

Composite Heat Shields in Intense Energy Fluxes with Diffusion

A method is proposed for bench testing of reusable composite samples under intense thermal and ionizing radiation. Tests are conducted under intense energy fluxes. As a result of the tests, the temperature field and the displacement field at the surface of heat-shielding composite and in its depth are determined at different times. The proposed mathematical model adequately determines describes the temperature distribution in the composite shield under the action of intense energy and radiation fluxes. The influence of diffusion and the temperature field on the displacement field in the composite is studied. The theoretical results are compared with experimental data.

42 ENGINEERING↗
DOE OSTI2019

Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

IgG Antibody 3D Structures and Dynamics

Antibodies are vital for human health because of their ability to function as nature’s drugs by protecting the body from infection. In recent decades, antibodies have been used as pharmaceutics for targeted therapy in patients with cancer, autoimmune diseases, and cardiovascular diseases. Capturing the dynamic structure of antibodies and characterizing antibody fluctuation is critical for gaining a deeper understanding of their structural characteristics and for improving drug development. Current techniques for studying three-dimensional (3D) structural heterogeneity and variability of proteins have limitations in ascertaining the dynamic structural behavior of antibodies and antibody-antigen complexes. Here, we review current techniques used to study antibody structures with a focus on the recently developed individual-particle electron tomography (IPET) technique. IPET, as a particle-by-particle methodology for 3D structural characterization, has shown advantages in studying structural variety and conformational changes of antibodies, providing direct imaging data for biomolecular engineering to improve development and clinical application of synthetic antibodies.

antibody dynamics↗
DOE OSTI2020

On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs

Physics informed neural networks (PINNs) are deep learning based techniques for solving partial differential equations (PDEs) encountered in computational science and engineering. Guided by data and physical laws, PINNs find a neural network that approximates the solution to a system of PDEs. Such a neural network is obtained by minimizing a loss function in which any prior knowledge of PDEs and data are encoded. Despite its remarkable empirical success in one, two or three dimensional problems, there is little theoretical justification for PINNs. As the number of data grows, PINNs generate a sequence of minimizers which correspond to a sequence of neural networks. We want to answer the question: Does the sequence of minimizers converge to the solution to the PDE? We consider two classes of PDEs: linear second-order elliptic and parabolic. By adapting the Schauder approach and the maximum principle, we show that the sequence of minimizers strongly converges to the PDE solution in C 0 . Furthermore, we show that if each minimizer satisfies the initial/boundary conditions, the convergence mode becomes H 1 . Computational examples are provided to illustrate our theoretical findings. To the best of our knowledge, this is the first theoretical work that shows the consistency of PINNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Experimental Validation of a Spectral-Based Structural Analysis Model Implemented in the Design of the VolturnUS 6MW Floating Offshore Wind Turbine

The following work presents a spectral-based structural analysis method implemented in the design of the VolturnUS 6MW Floating Offshore Wind Turbine hull developed to increase system optimization. To begin, a description of the methodology is provided which details how transfer functions relate the hull's structural response to first order wave kinematics and wind turbine aerodynamics. Following the model definition, focus is placed on model validation using results from an experimental 1:52 scale model test of the VolturnUS system (shown in Fig. 1) conducted at the University of Maine's Alfond W2 Ocean Engineering Laboratory. Using data acquired from load cells installed at various locations in the hull the accuracy of the model is assessed through the use of power spectra and statistics. The performance of the structural model is considered over a range of environmental conditions representing design load cases prescribed by the American Bureau of Shipping for class certification of floating offshore wind turbines.

artificial intelligence, offshore projects plannin↗
DOE OSTI2022

Long Term Damage Testing (NREL)

DOE's Regional Test Center program has fielded several strings of PV modules as part of their Long Term Testing program. Some of these modules have been installed since 2016 and have been exposed to severe weather events. A key to developing long lifespans for PV modules (in excess of 30 years) is understanding how damage and defects develop, propagate and progress. Researchers at the NREL Regional Test Center have started developing testing procedures and analysis tools in order to characterize modules in a controlled manner with the goal of understanding how damage spreads under normal operations. Characterization methods include EL and IR imaging, outdoor and indoor IV curves, and long term exposure monitoring. Modules to be evaluated will be chosen based on severity of defect, ability to track changes in defect and space requirements. The samples will be loaded at maximum power using grid-tied inverters or other means. Gathering and reporting on this data may help engineers and scientists design for damage and improve long-term performance.

crack damage↗
DOE OSTI2022

Idaho National Laboratory (INL) Wireless Test Beds for Over the Air (OTA) experimentation

Invited Keynote talk that contains material from talks already presented by INL wireless team & Wireless Security Institute in various forums. VISION: Advance 5G national leadership and accelerate the secure adoption of 5G and beyond technology. MISSION: Provide best in class policy and decision data, security evaluation, engineering support, and technology development enabling government and industry to maximize the benefits of 5G and beyond technology. END STATE: Broad, diversely funded RDD&D portfolio, INL established as National Authority on Wireless Security.

5G↗
DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Nuclear Requalification of the ATR Core

The Advanced Test Reactor (ATR) creates a unique, high neutron flux materials testing environment that subsequently causes neutron embrittlement damage to its beryllium reflector. The reflector is eventually required to be replaced during a reactor Outage. Concurrently, a piece-for-piece core replacement is conducted to maintain reactor functionality called a core internals changeout (CIC). Once changeout is complete, ATR Reactor Engineering utilizes previous CIC data, notably 1977-1994 CIC data, to conduct predictive criticality analysis on the new, unirradiated core. However, CIC data has been inconsistently reported over the years making it difficult, and in some cases impossible, to utilize. These inconsistencies arise in various forms of not using correct units, inconsistent diagram usage, and not portraying the same kind of data similarly across the reports. To work around this inconsistency issue, Reactor Engineering is implementing the use of several new neutronic modeling codes that utilize modern computation speeds and methods to model the new core in different criticality environments. Further validation is then conducted by nuclear testing and bringing the reactor critical and conducting various irradiation tests. Upon completion and certification that the reactor passed all testing requirements, ATR can once again re-start normal operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Analysis of backwash settings to maximize net water production in an engineering-scale ultrafiltration system for water reuse

Ultrafiltration (UF) has been widely utilized as water pretreatment for different applications especially in water reuse. The UF system operation is characterized by a filtration phase, where particles accumulate on the membrane surface resulting in an increase in the transmembrane pressure (TMP) and a cleaning phase, where foulants are removed through cleaning cycles including physical backwash and chemical-enhanced backwash (CEB). In this study, data from an engineering-scale UF system treating reclaimed wastewater were used to assess the impact of backwashing on the filtration process. TMP backwash trigger, backwash duration, and CEB frequency were purposely varied for a cycle-by-cycle investigation on the net water production, water recovery, initial operating TMP, and filtration cycle duration. As the TMP backwash trigger was varied between 62 and 145kPa, the maximum net water production (63 m 3 /d) was achieved at 103kPa and water recovery remained relatively constant at approximately 92%. Backwash durations of 45, 65, and 85s were performed where both net water production and water recovery yielded similar results (~63 m 3 /d and ~ 91%) compared with 103kPa TMP backwash trigger. The CEB frequency was also lowered from one every three backwashes (1/3) to 1/6 and 1/12 and resulted in decreased net water production and water recovery while the initial TMP increased. Interestingly, the total number of CEBs remained approximately constant regardless of their frequency. In conclusion, results suggest that CEB is an important fouling control process to maximize water production.

42 ENGINEERING↗