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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental Study of Instabilities in Hydrogen-Air Fueled Rotating Detonation Combustion Presentation

Conventional gas turbine engines rely on an idealized constant pressure combustion process that in reality produces a pressure decrease as a result of viscous and other non-reversible losses. An alternative approach is rotating detonation combustion (RDC) which is a form of pressure gain combustion in which one or more detonation waves propagate an annular channel resulting in an increase in pressure across, subsequently providing greater work availability compared to deflagration ultimately leading to opportunities for greater thermodynamic efficiency when used in gas turbine engines that conventionally relies on constant. Modern gas turbine engines often rely on pre-mixed reactants to limit NOx emissions, although this may result in greater susceptibility to instabilities such as flashback and thermoacoustic oscillation, particularly for applications that utilize hydrogen as the fuel. Research in RDC has focused on non-premixed reactants thus limiting the occurrence of flashback, and high frequency detonation wave propagation (kHz) may interfere with the occurrence of thermoacoustic oscillations. Thermal NOx emissions are controlled through rapid combustion and sudden expansion of the working fluid. Although RDC may not be susceptible to instabilities encountered in conventional state of the art gas turbine engine combustion, there may be other mechanisms occurring that support instabilities that could be detrimental to performance.

Weber, Justin↗
DOE OSTI2024

Colorado State University Extension Industrial Assessment Center

Since its inception in 1984, the Colorado State University Industrial Assessment Center has performed industrial assessments at more than 720 manufacturing facilities in Colorado, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. From 2017 to 2019 there was a funding gap and the IAC shutdown. In 2020 through DOE extension funding the University relaunched the IAC as an extension center in order to provide assessments to underserved areas. Under this award, the CSU Industrial Assessment Center (IAC) was rebuilt with the help of student employees and the director. The CSU team experienced difficulty as the program was in the process of being restarted right as the 2020 pandemic hit. Nonetheless, the CSU IAC was instrumental in providing energy assessments to manufacturers in Colorado and Wyoming during the period of performance of 09/2019 – 12/2022. The Department of Energy's Industrial Assessment Centers (IACs) provide a valuable service to small and medium-sized manufacturers seeking to optimize their operations. These university-based centers offer no-cost, on-site assessments conducted by engineering faculty and students, analyzing energy consumption, production processes, and waste streams. They utilize advanced data acquisition systems to record operational data, and then use the data to create assessment recommendations. These recommendations form the foundation of the comprehensive energy report. The comprehensive report delivers actionable recommendations for enhancing energy efficiency, reducing waste, and reducing greenhouse gas emissions and improving productivity, often identifying significant cost savings. Furthermore, IACs facilitate access to implementation grants, enabling the businesses to readily adopt these improvements. This program not only strengthens individual businesses but also contributes to national goals of training the next generation of energy experts, as well as increasing industrial competitiveness and reduced environmental impact.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

[Challenges and Opportunities in] Process Modeling of Intensified Chemical Processes

Before the benefits of process intensification can be fully realized, a multitude of advances in process modeling will be necessary. Process intensification (PI) has the potential to speed development of chemical engineering innovations. Among its many benefits, PI can increase the driving forces (physical and/or chemical) for transport phenomena, separations, and/or reactions in chemical processes, and inspire novel process configurations with major technical and economic benefits. Examples of PI applications include integrated process units such as heat exchange networks, sorption- or membrane-enhanced reactors, and dividing-wall distillation columns, among others [AIChE(2017)].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Cellulosic Biomass Sugars to Advantage Jet Fuel: Catalytic Conversion of Corn Stover to Energy Dense, Low Freeze Point Paraffins and Naphthenes (CRADA CRD-12-462 Final Report)

NREL will provide scientific and engineering support to Virent Energy Systems in three technical areas: Process Development/Biomass Deconstruction; Catalyst Fundamentals; and Technoeconomic Analysis. The overarching objective of this project is to develop the first fully integrated process that can convert a lignocellulosic feedstock (e.g., corn stover) efficiently and cost effectively to a mix of hydrocarbons ideally suited for blending into jet fuel. The proposed project will investigate the integration of Virent Energy System's novel aqueous phase reforming (APR) catalytic conversion technology (BioForming) with deconstruction technologies being investigated by NREL at the 1-500 L scale. Corn stover was chosen as a representative large volume, sustainable feedstock.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2015

Nitrate Salt Surrogate Blending Scoping Test Plan

Test blending equipment identified in the “Engineering Options Assessment Report: Nitrate Salt Waste Stream Processing”. Determine if the equipment will provide adequate mixing of zeolite and surrogate salt/Swheat stream; optimize equipment type and operational sequencing; impact of baffles and inserts on mixing performance; and means of validating mixing performance

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. For multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Image Analysis for Plug Bubbles in Horizontal Flow

Horizontal plug flow is different from horizontal slug flow in that relatively few small bubbles exist in plug flow, whereas slug flow is characterized by highly aerated liquid slugs and liquid films. While the nose position and nose propagation velocity of plug bubbles may provide physical insights in understanding the flow regime transition mechanism between the plug and slug flows, few systematic investigations on these parameters have been performed in previous research. In view of this, this paper presents the development of an image processing method for the purpose of (a) obtaining data for nose position and nose propagation velocity of plug bubbles and (b) benchmarking local four-sensor conductivity probe measurements of time-averaged bubble velocity and void fraction. (authors)

42 ENGINEERING↗
DOE OSTI2017

Soot and Spectral Radiation Modeling in ECN Spray A and in Engines

The amount of soot formed in a turbulent combustion system is determined by a complex system of coupled nonlinear chemical and physical processes. Different physical subprocesses can dominate, depending on the hydrodynamic and thermochemical environments. Similarly, the relative importance of reabsorption, spectral radiation properties, and molecular gas radiation versus soot radiation varies with thermochemical conditions, and in ways that are difficult to predict for the highly nonhomogeneous in-cylinder mixtures in engines. Here it is shown that transport and mixing play relatively more important roles as rate-determining processes in soot formation at engine-relevant conditions. It is also shown that molecular gas radiation and spectral radiation properties are important for engine-relevant conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

DOE Chair of Excellence in Environmental Disciplines-Final Technical Report

The report Massie Chair of Excellence Program at Universidad del Turabo, contract DE-FG02-95EW12610, during the period of 9/29/1995 to 9/29/2011. The initial program aims included development of academic programs in the Environmental Sciences and Engineering, and Research and Development focused initially on environmentally friendly processes and later revised also include: renewable energy and international cooperation. From 1995 -2005, the Program at UT lead the establishment of the new undergraduate program in electrical engineering at the School of Engineering (SoE), worked on requirements to achieve ABET accreditation of the SoE B.S. Mechanical Engineering and B.S. Electrical Engineering programs, mentored junior faculty, taught undergraduate courses in electrical engineering, and revised the electrical engineering curriculum. Engineering undergraduate laboratories were designed and developed. The following research sub-project was developed: Research and development of new perovskite-alumina hydrogen permeable asymmetrical nanostructured membranes for hydrogen purification, and extremely high specific surface area silica materials for hydrogen storage in the form of ammonia, Dr. Rolando Roque-Malherbe Subproject PI, Dr. Santander Nieto and Mr. Will Gómez Research Assistants. In 2006, the Massie Chair of Excellence Program was transferred to the National Nuclear Security Agency, NNSA and DNN. DoE required a revised proposal aligned with the priorities of the Administration. The revised approved program aims included: (1) Research (2) Student Development: promote the development of minority undergraduate and graduate students through research teams, internships, conferences, new courses; and, (3) Support: (a) Research administration and (b) Dissemination through international conferences, the UT Distinguished Lecturer Series in STEM fields and at the annual Universidad del Turabo (UT) Researchers Conference. Research included: Sub-Project 1: Synthesis and Characterization of low Refractive Index Aerogel Silica for Cherenkov Counters- Dr. Rolando Roque-Malherbe Sub-project PI, Dr. Jose Duconge Sub-project Co-PI, Dr. Santander Nieto Assistant Researcher, Francisco Diaz and Carlos Neira Associate Researchers. The initial aim of this sub-project was changed to the synthesis and characterization of extremely high specific surface area aerogel silica for gas storage. A high specific surface area silica gel that has applications in gas drying, cleaning operation useful in nuclear industry in process was developed. Sub-Project 2: Investigation Study of Magnetic and Electronic Transport Properties at Material Interfaces in Magnetic Multilayer Heterostructure using Gd. – Dr. Yazan Hijazi, Sub-project Co-PI. UT developed the capability and infrastructure to produce high quality thin-film magnetic films and magnetic multilayer structures with fine control over film quality and thickness using sputter deposition capability to perform in-house electric and magnetic characterization of these films. The research experimentally quantified the effect of Gd incorporation within the magnetic multilayer structure and produce magnetic media with exchanged decoupled multilevel magnetic anisotropy. From September 2006 to September 2011 the Massie Chair produced nineteen (19) publications, (including 3 books), five (5) presentations and three (3) international conferences abstracts. A total of fourteen (14) undergraduates and (6) graduate students acquired research experience. Two Ph.D. students presented their dissertations on topics related to nuclear energy and graduated as follows: María Cotto (May 2009) and Eric Calderón (May 2011). Five of the participating undergraduate students graduated: Ramon Polanco (BSME, May 2009), Jason Pérez (BSEE, May 2008), Rafael Colón (BSME, May 2008), Jessenia Marfisi (BS Chemistry, May 2008). Eleven (11) students were sent to National Laboratories (LANL, SNL and LLNL), NNSA and DoE facilities for summer internships. Twenty eight (28) undergraduate students participated in Summer Internships (2010, 2011) at the Puerto Rico Energy Center (PREC). Four international energy symposiums were held aligned with the DoE and the NNSA missions and dissemination of Massie Chair research activities (660 attendees). Academic programs developed or revised under advice of the Massie Chair: Ph.D. in Environmental Sciences (revised); MSc in Environmental Sciences (revised); MSc in Mechanical Engineering with concentration in Alternative Energy (new); BS in Industrial Management & Engineering (revised to fulfill the ABET requirements); BS in Civil Engineering including an environmental option (new); BS in Electrical Engineering (revised); and, Associate in Renewable Energy (new). The Puerto Rico Energy Center (PREC) was designed and developed under the Massie Chair initiative. Thirty-three (33) proposals were developed and submitted during the period of which 12 were approved in the amount of $ $1,931,306.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Plan for Developing TRISO Fuel Processing Technologies

This Plan demonstrates the availability of technologies for processing TRISO used nuclear fuel for waste management and actinide recovery purposes. These technologies are judged to be at a very low level of technology readiness and as such they constitute a fertile research area for the DOE-NE’s Office of Materials and Chemical Technologies. Strategies to mature the technologies to a point where they can reasonably be considered in engineering alternatives analyses typically involve laboratory-scale tests using fuel simulant to characterize process streams and demonstrate key engineering features. Several criteria are available to help selecting candidate technologies for further maturation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Intercellular adhesion molecule-1 expression by skeletal muscle cells augments myogenesis

We previously demonstrated that the expression of intercellular adhesion molecule-1 (ICAM-1) by skeletal muscle cells after muscle overload contributes to ensuing regenerative and hypertrophic processes in skeletal muscle. The objective of the present study is to reveal mechanisms through which skeletal muscle cell expression of ICAM-1 augments regenerative and hypertrophic processes of myogenesis. This was accomplished by genetically engineering C2C12 myoblasts to stably express ICAM-1, and by inhibiting the adhesive and signaling functions of ICAM-1 through the use of a neutralizing antibody or cell penetrating peptide, respectively. Expression of ICAM-1 by cultured skeletal muscle cells augmented myoblast–myoblast adhesion, myotube formation, myonuclear number, myotube alignment, myotube–myotube fusion, and myotube size without influencing the ability of myoblasts to proliferate or differentiate. ICAM-1 augmented myotube formation, myonuclear accretion, and myotube alignment through a mechanism involving adhesion-induced activation of ICAM-1 signaling, as these dependent measures were reduced via antibody and peptide inhibition of ICAM-1. The adhesive and signaling functions of ICAM-1 also facilitated myotube hypertrophy through a mechanism involving myotube–myotube fusion, protein synthesis, and Akt/p70s6k signaling. Our findings demonstrate that ICAM-1 expression by skeletal muscle cells augments myogenesis, and establish a novel mechanism through which the inflammatory response facilitates growth processes in skeletal muscle. - Highlights: • We examined mechanisms through which skeletal muscle cell expression of ICAM-1 facilitates events of in vitro myogenesis. • Expression of ICAM-1 by cultured myoblasts did not influence their ability to proliferate or differentiate. • Skeletal muscle cell expression of ICAM-1 augmented myoblast fusion, myotube alignment, myotube–myotube fusion, and myotube size. • ICAM-1 augmented myogenic processes through mechanisms involving its adhesive and signaling functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Cyber-Informed Engineering

Briefings provided to Duke Energy during their visit to INL on January 25, 2023. This is following the process to release the slides to Duke Energy.

42 ENGINEERING↗
DOE OSTI2022

Solvent-driven fractional crystallization for atom-efficient separation of metal salts from permanent magnet leachates

Abstract This work reports a dimethyl ether-driven fractional crystallization process for separating rare earth elements and transition metals. The process has been successfully applied in the treatment of rare earth element-bearing permanent magnet leachates as an atom-efficient, reagent-free separation method. Using ~5 bar pressure, the solvent was dissolved into the aqueous system to displace the contained metal salts as solid precipitates. Treatments at distinct temperatures ranging from 20–31 °C enable crystallization of either lanthanide-rich or transition metal-rich products, with single-stage solute recovery of up to 95.9% and a separation factor as high as 704. Separation factors increase with solution purity, suggesting feasibility for eco-friendly solution treatments in series and parallel to purify aqueous material streams. Staged treatments are demonstrated as capable of further improving the separation factor and purity of crystallized products. Upon completion of a crystallization, the solvent can be recovered with high efficiency at ambient pressure. This separation process involves low energy and reagent requirements and does not contribute to waste generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Lignin Valorization: Two Hybrid Biochemical Routes for the Conversion of Polymeric Lignin into Value-added Chemicals

Naturally, many aerobic organisms degrade lignin-derived aromatics through conserved intermediates including protocatechuate and catechol. Employing this microbial approach offers a potential solution for valorizing lignin into valuable chemicals for a potential lignocellulosic biorefinery and enabling bioeconomy. In this study, two hybrid biochemical routes combining lignin chemical depolymerization, plant metabolic engineering, and synthetic pathway reconstruction were demonstrated for valorizing lignin into value-added products. In the biochemical route 1, alkali lignin was chemically depolymerized into vanillin and syringate as major products, which were further bio-converted into cis, cis-muconic acid (ccMA) and pyrogallol, respectively, using engineered Escherichia coli strains. In the second biochemical route, the shikimate pathway of Tobacco plant was engineered to accumulate protocatechuate (PCA) as a soluble intermediate compound. The PCA extracted from the engineered Tobacco was further converted into ccMA using the engineered E. coli strain. This study reports a direct process for converting lignin into ccMA and pyrogallol as value-added chemicals, and more importantly demonstrates benign methods for valorization of polymeric lignin that is inherently heterogeneous and recalcitrant. Our approach also validates the promising combination of plant engineering with microbial chassis development for the production of value added and speciality chemicals.

Science & Technology - Other Topics↗