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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Development of a Composite Tailoring Procedure for Airplane Wings

The quest for finding optimum solutions to engineering problems has existed for a long time. In modern times, the development of optimization as a branch of applied mathematics is regarded to have originated in the works of Newton, Bernoulli and Euler. Venkayya has presented a historical perspective on optimization in [1]. The term 'optimization' is defined by Ashley [2] as a procedure "...which attempts to choose the variables in a design process so as formally to achieve the best value of some performance index while not violating any of the associated conditions or constraints". Ashley presented an extensive review of practical applications of optimization in the aeronautical field till about 1980 [2]. It was noted that there existed an enormous amount of published literature in the field of optimization, but its practical applications in industry were very limited. Over the past 15 years, though, optimization has been widely applied to address practical problems in aerospace design [3-5]. The design of high performance aerospace systems is a complex task. It involves the integration of several disciplines such as aerodynamics, structural analysis, dynamics, and aeroelasticity. The problem involves multiple objectives and constraints pertaining to the design criteria associated with each of these disciplines. Many important trade-offs exist between the parameters involved which are used to define the different disciplines. Therefore, the development of multidisciplinary design optimization (MDO) techniques, in which different disciplines and design parameters are coupled into a closed loop numerical procedure, seems appropriate to address such a complex problem. The importance of MDO in successful design of aerospace systems has been long recognized. Recent developments in this field have been surveyed by Sobieszczanski-Sobieski and Haftka [6].

Chattopadhyay, Aditi↗
NASA NTRS1990

Introduction to the internal fluid mechanics research session

Internal fluid mechanics research at LeRC is directed toward an improved understanding of the important flow physics affecting aerospace propulsion systems, and applying this improved understanding to formulate accurate predictive codes. To this end, research is conducted involving detailed experimentation and analysis. The following three papers summarize ongoing work and indicate future emphasis in three major research thrusts: inlets, ducts, and nozzles; turbomachinery; and chemical reacting flows. The underlying goal of the research in each of these areas is to bring internal computational fluid mechanic to a state of practical application for aerospace propulsion systems. Achievement of this goal requires that carefully planned and executed experiments be conducted in order to develop and validate useful codes. It is critical that numerical code development work and experimental work be closely coupled. The insights gained are represented by mathematical models that form the basis for code development. The resultant codes are then tested by comparing them with appropriate experiments in order to ensure their validity and determine their applicable range. The ultimate user community must be a part of this process to assure relevancy of the work and to hasten its practical application. Propulsion systems are characterized by highly complex and dynamic internal flows. Many complex, 3-D flow phenomena may be present, including unsteadiness, shocks, and chemical reactions. By focusing on specific portions of a propulsion system, it is often possible to identify the dominant phenomena that must be understood and modeled for obtaining accurate predictive capability. The three major research thrusts serve as a focus leading to greater understanding of the relevant physics and to an improvement in analytic tools. This in turn will hasten continued advancements in propulsion system performance and capability.

Miller, Brent A.↗
NASA NTRS2004

Fourth Computational Aeroacoustics (CAA) Workshop on Benchmark Problems

This publication contains the proceedings of the Fourth Computational Aeroacoustics (CAA) Workshop on Benchmark Problems. In this workshop, as in previous workshops, the problems were devised to gauge the technological advancement of computational techniques to calculate all aspects of sound generation and propagation in air directly from the fundamental governing equations. A variety of benchmark problems have been previously solved ranging from simple geometries with idealized acoustic conditions to test the accuracy and effectiveness of computational algorithms and numerical boundary conditions; to sound radiation from a duct; to gust interaction with a cascade of airfoils; to the sound generated by a separating, turbulent viscous flow. By solving these and similar problems, workshop participants have shown the technical progress from the basic challenges to accurate CAA calculations to the solution of CAA problems of increasing complexity and difficulty. The fourth CAA workshop emphasized the application of CAA methods to the solution of realistic problems. The workshop was held at the Ohio Aerospace Institute in Cleveland, Ohio, on October 20 to 22, 2003. At that time, workshop participants presented their solutions to problems in one or more of five categories. Their solutions are presented in this proceedings along with the comparisons of their solutions to the benchmark solutions or experimental data. The five categories for the benchmark problems were as follows: Category 1:Basic Methods. The numerical computation of sound is affected by, among other issues, the choice of grid used and by the boundary conditions. Category 2:Complex Geometry. The ability to compute the sound in the presence of complex geometric surfaces is important in practical applications of CAA. Category 3:Sound Generation by Interacting With a Gust. The practical application of CAA for computing noise generated by turbomachinery involves the modeling of the noise source mechanism as a vortical gust interacting with an airfoil. Category 4:Sound Transmission and Radiation. Category 5:Sound Generation in Viscous Problems. Sound is generated under certain conditions by a viscous flow as the flow passes an object or a cavity.

Dahl, Milo D.↗
DOE OSTI2022

Li 7 P 3 S 11 electrolyte for all-solid-state lithium-ion batteries: structure, synthesis, and applications

Because of a high ion conductivity (10 -2 S cm -1 ) comparable with liquid electrolytes at room temperature, Li 7 P 3 S 11 , one of the most important solid state electrolytes (SSEs), has attracted significant attention for applications in all-solid-state lithium batteries (ASSLBs). The development of Li 7 P 3 S 11 has progressed impressively in recent years. A fundamental understanding of Li 7 P 3 S 11 SSE from its crystal structure and ion conductivity to practical applications is critical for the development of Li 7 P 3 S 11 SSE based ASSLBs. In light of that, this review presents an overview of the Li 7 P 3 S 11 SSE. Herein, the review addresses 1) the crystal structure and Li + diffusion mechanism; 2) developed synthesis methods and corresponding crystal growth mechanisms; 3) challenges and strategies of Li 7 P 3 S 11 SSE in practical applications. Finally, remaining challenges and future perspectives are highlighted.

25 ENERGY STORAGE↗
NASA NTRS2019

Machine Learning Lifecycle for Earth Science Application: A Practical Insight into Production Deployment

Earth science domain presents unique sets of problems that are increasingly being solved using data driven approaches. The availability of big Earth science data offers immense potential for Machine learning (ML) as evident from numerous research publications lately. However, many of these publications are not ending up as production applications mainly because the data scientists who develop the ML models are now expected to complete the ML lifecycle by deploying and scaling the models in production. We introduce ML lifecycle to the Earth science community including the opportunities and challenges that lie ahead in each phase of the lifecycle. We demonstrate the lifecycle using an Earth science problem that we used ML to address and transitioned to production.

Maskey, Manil↗
DOE OSTI2025

Fusion Model for Metagenomics

This work highlights the use of an embeddings approach that can encode multiple features and create efficient contextualization of profiled metagenomes derived from microbiome samples using computer vision models and image representations of the abundance profiles. The model's embeddings can be used to cluster existing samples based on multiple conditions and interpretations, and new embeddings can be quickly created for new samples and fitted to existing clusters to characterize them. This has practical applications for unknown, unlabeled microbiome samples. The model's embeddings can be used to cluster existing samples based on multiple conditions and interpretations, and new embeddings can be quickly created for new samples and fitted to existing clusters to characterize them. This has practical applications for unknown, unlabeled microbiome samples.

Valdes, CamiloA [Lawrence Livermore National Labor↗
DOE OSTI2025

Properties and performance of lignin-based polyurethane foams from lignin and castor oil as synergistic bio-polyols

Lignin and castor oil with intrinsic hydroxyl groups are attractive green resources for polyurethane (PU) applications. However, lignin's heterogeneous and highly crosslinked structure, poor processability, as well as the feedstock variability, lead to inconsistent and poor performance of the final foam products. Castor oil-based polyurethane foam (PUF) has a relatively high price and density, which are big hurdles to its practical applications. Here, in this study, we hypothesized that synergistic bio-polyol mixtures composed of lignin and castor oil could balance the drawbacks from individual component. Castor oil could improve the dispersity of lignin, while lignin simultaneously addressed the issues caused by PUF prepared with castor oil, such as its high density and low thermal stability. For a comprehensive understanding of the effects of structural properties of lignin on its PUF processing and applications, various lignin fractions were isolated by co-solvent enhanced lignocellulosic fractionation (CELF) from different species, including hardwood, softwood, and herbaceous plants, and the processed lignins with different molecular weights were applied with castor oil. The lignin fractions with lower molecular weight showed good dispersity in castor oil with a high lignin content (up to 50 wt%) and completely replaced petroleum-based polyols. The produced foam with 50 wt% low-molecular-weight lignin fractions from woody biomass showed comparable/higher compressive strength (up to 20 psi) and thermal insulation performance (up to 5.69 R-value in −1 for 50 % L-Pine foam). In addition, this study revealed the relationship between lignin's structural properties and foam performance, providing insights for practical applications of lignin-based PUF.

Jeong, Soyeon [State Univ. of New York (SUNY), Syr↗
NASA NTRS1978

Thermal energy storage

The general scope of study on thermal energy storage development includes: (1) survey and review possible concepts for storing thermal energy; (2) evaluate the potentials of the surveyed concepts for practical applications in the low and high temperature ranges for thermal control and storage, with particular emphasis on the low temperature range, and designate the most promising concepts; and (3) determine the nature of further studies required to expeditiously convert the most promising concept(s) to practical applications. Cryogenic temperature control by means of energy storage materials was also included.

Grodzka, P. G.↗
DOE OSTI2021

Simulation-based Performance Evaluation of Model Predictive Control for Building Energy Systems

The performance of model predictive control (MPC) can be significantly affected by different choices of controller parameters such as the time intervals for model discretization and control sampling. Due to the lack of a systematic understanding on how these parameters affect control performance, they are usually selected arbitrarily in practice.In this paper, the combined impacts of selected time intervals for model discretization and control sampling on the performance of MPC are comprehensively investigated for the first time through detailed simulations. Specifically, a typical MPC strategy is first designed to improve building operations based on a reduced-order model of building dynamics. Then, the performance of the designed MPC is evaluated against different choices of time intervals for model discretization and control sampling on a simulated office building. The detailed simulation results reveal that the time interval for model discretization has a much greater influence on the performance of MPC than the time interval for control sampling. Although the time interval for control sampling usually receives more attentions in practice, it turns out that the time interval for model discretization affects the prediction performance, cost saving, and computation time simultaneously and more significantly. Therefore, the simulation-based performance evaluation presented here sheds light on the impacts of different time intervals and facilitates their selection for practical applications of MPC to building operations

Huang, Sen↗
DOE OSTI2021

Challenges and future perspectives on sodium and potassium ion batteries for grid-scale energy storage

The energy crisis and environmental pollution require the advancement of large-scale energy storage techniques. Among the various commercialized technologies, batteries have attracted enormous attention due to their relatively high energy density and long cycle life. Nevertheless, the limited supply and uneven distribution of lithium minerals, as well as their high cost, has greatly hindered the application of lithium-ion batteries in large-scale energy storage. Therefore, building next-generation alternative rechargeable batteries that feature low cost, long service life, and high safety is of the utmost importance. Over the past several years, we have witnessed many successful research outcomes for sodium and potassium ion batteries (SIBs and PIBs) in regard to electrode and electrolyte materials. In this Perspective, we summarize the current developments on SIBs/PIBs and their challenges when facing practical applications, including their cost, energy density, ion diffusivity in solids/electrolytes/interphases, cycle life, and safety concerns. Furthermore, we provide an overview of strategies to overcome the remaining challenges for achieving better electrochemical performance. Finally, we outline several possible directions for the future development of these two battery chemistries, with the hope of aiding the transition from the laboratory to next-generation practical applications for SIBs/PIBs batteries in grid-scale energy storage.

Energy Storage↗
DOE OSTI2020

A lithium-sulfur battery with a solution-mediated pathway operating under lean electrolyte conditions

Lithium-sulfur (Li-S) battery is one of the most promising candidates for the next generation energy storage systems. However, several barriers, including polysulfide shuttle effect, the slow solid-solid surface reaction pathway in the lower discharge plateau, and corrosion of Li anode still limit its practical applications, especially under the lean electrolyte condition required for high energy density applications. Here, we propose a solution-mediated sulfur reduction pathway to improve the capacity and reversibility of the sulfur cathode and suppress dendrite growth on the Li metal anode simultaneously. With this method, a high coulombic efficiency (99%) and stable cycle life over 100 cycles were achieved under application-relevant conditions (S loading: 6.2 mg cm-2; electrolyte to sulfur ratio: 3 mLE gs-1; sulfur weigh ratio: 72 wt%). This result is enabled by a specially designed Li2S4-rich electrolyte, in which Li2S is formed through a chemical disproportionation reaction instead of electrochemical routes. A diglyme solvent was used to obtain electrolytes with the optimum range of Li2S4 concentration. Operando X-ray absorption spectroscopy confirms the solution pathway in a practical Li-S cell. This solution pathway not only introduces a new electrolyte regime for practical Li-S batteries, but also provides a new perspective for bypassing the inefficient surface pathway for other electrochemical processes.

Wang, Hui↗
DOE OSTI2023

Sub-100 mA/cm 2 CO 2 -to-CO Reduction Current Densities in Hierarchical Porous Gold Electrocatalysts Made by Direct Ink Writing and Dealloying

While most research efforts on CO 2 -to-CO reduction electrocatalysts focus on boosting their selectivity, the reduction rate, directly proportional to the reduction current density, is another critical parameter to be considered in practical applications. This is because mass transport associated with the diffusion of reactant/product species becomes a major concern at a high reduction rate. Nanostructured Au is a promising CO 2 -to-CO reduction electrocatalyst for its very high selectivity. However, the CO 2 -to-CO reduction current density commonly achieved in conventional nanostructured Au electrocatalysts is relatively low (in the range of 1–10 mA/cm 2 ) for practical applications. In this work, we combine direct ink writing-based additive manufacturing and dealloying to design a robust hierarchical porous Au electrocatalyst to improve the mass transport and achieve high CO 2 -to-CO reduction current densities on the order of 64.9 mA/cm 2 with CO partial current density of 33.8 mA/cm 2 at 0.55 V overpotential using an H-cell configuration. Although the current density achieved in our robust hierarchical porous Au electrocatalyst is one order of magnitude higher than the one achieved in conventional nanostructured electrocatalysts, we found that the selectivity of our system is relatively low, namely 52%, which suggests that mass transport remains a critical issue despite the hierarchical porous architecture. We further show that the bulk dimension of our electrocatalyst is a critical parameter governing the interplay between selectivity and reduction rate. In conclusion, the insights gained in this work shed new light on the design of electrocatalysts toward scale-up CO 2 reduction and beyond.

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

Possible Topological Hall Effect above Room Temperature in Layered Cr 1.2 Te 2 Ferromagnet

Topological Hall effect (THE) has been used as a powerful tool to unlock spin chirality in novel magnetic materials. Recent focus has been widely paid to THE and possible chiral spin textures in two-dimensional (2D) layered magnetic materials. However, the room-temperature THE has been barely reported in 2D materials, which hinders its practical applications in 2D spintronics. In this paper, we report a possible THE signal featuring antisymmetric peaks in a wide temperature window up to 320 K in Cr 1.2 Te 2 , a new quasi-2D ferromagnetic material. The temperature, thickness, and magnetic field dependences of the THE lead to potential spin chirality origin that is associated with the spin canting under external magnetic fields. Furthermore, our work holds promise for practical applications in future chiral spin-based vdW spintronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Driver Distraction Behavior Detection using a Vision Transformer Model based on Transfer Learning Strategy

Driver distraction behavior is one of the critical factors in traffic accidents. Thus, advanced driver state detection system has become the focus in the field of intelligent vehicle. However, in practical applications, insufficient samples of driving distraction behaviors bring great challenges to training a personalized behavior distraction detection model for a specific driver. To this end, a novel transformer model based on a transfer learning strategy is proposed in this paper to accurately recognize driver distraction behavior. Inspired by the effect of the transformer network in visual recognition, we firstly present a transformer behavior distraction detection system to identify the behavior categories that cause driver distraction. Then, for the specific driving dataset in practical application scenarios, the transfer learning strategy is introduced into the driver distraction detection model to further train the general transformer network. The effectiveness of the transformer based on the transfer learning strategy is validated compared with other traditional deep learning methods. The results show that the proposed detection method has better generalization ability and higher accuracy.

Fang, Zhenwu↗
NASA NTRS1997

Soot Formation in Freely-Propagating Laminar Premixed Flames

Soot formation within hydrocarbon-fueled flames is an important unresolved problem of combustion science. Thus, the present study is considering soot formation in freely-propagating laminar premixed flames, exploiting the microgravity environment to simplify measurements at the high-pressure conditions of interest for many practical applications. The findings of the investigation are relevant to reducing emissions of soot and continuum radiation from combustion processes, to improving terrestrial and spacecraft fire safety, and to developing methods of computational combustion, among others. Laminar premixed flames are attractive for studying soot formation because they are simple one-dimensional flows that are computationally tractable for detailed numerical simulations. Nevertheless, studying soot-containing burner-stabilized laminar premixed flames is problematical: spatial resolution and residence times are limited at the pressures of interest for practical applications, flame structure is sensitive to minor burner construction details so that experimental reproducibility is not very good, consistent burner behavior over the lengthy test programs needed to measure soot formation properties is hard to achieve, and burners have poor durability. Fortunately, many of these problems are mitigated for soot-containing, freely-propagating laminar premixed flames. The present investigation seeks to extend work in this laboratory for various soot processes in flames by observing soot formation in freely-propagating laminar premixed flames. Measurements are being made at both Normal Gravity (NG) and MicroGravity (MG), using a short-drop free-fall facility to provide MG conditions.

Lin, K.-C.↗
NASA NTRS1999

Combustion of Metals in Reduced-Gravity and Extra Terrestrial Environments

The combustion of metals is a field with important practical applications in rocket propellants, high-temperature flames, and material synthesis. Also, the safe operation of metal containers in high-pressure oxygen systems and with cryogenic fuels and oxidizers remains an important concern in industry. The increasing use of metallic components in spacecraft and space structures has also raised concerns about their flammability properties and fire suppression mechanisms. In addition, recent efforts to embark on unmanned and manned planetary exploration, such as on Mars, have also renewed the interest in metal/carbon-dioxide combustion as an effective in situ resource utilization technology. In spite of these practical applications, the understanding of the combustion properties of metals remains far behind that of the most commonly used fuels such as hydrocarbons. The lack of understanding is due to the many problems unique to metal- oxidizer reactions such as: low-temperature surface oxidation prior to ignition, heterogeneous reactions, very high combustion temperatures, product condensation, high emissivity of products, and multi-phase interactions. Very few analytical models (all neglecting the influence of gravity) have been developed to predict the burning characteristics and the flame structure details. Several experimental studies attempting to validate these models have used small metal particles to recreate gravity-free conditions. The high emissivity of the flames, rapid reaction, and intermittent explosions experienced by these particles have made the gathering of any useful information on burning rates and flame structure very difficult. The use of a reduced gravity environment is needed to clarify some of the complex interactions among the phenomena described above. First, the elimination of the intrusive buoyant flows that plague all combustion phenomena is of paramount importance in metal reactions due to the much higher temperatures reached during combustion. Second, a low-gravity environment is absolutely essential to remove the destructive effect of gravity on the shape of a molten metal droplet in order to study a spherically symmetric condition with large bulk samples. The larger size of the spherical metal droplet and the longer burning times available in reduced gravity extend the spatial and temporal dimensions to permit careful probing of the flame structure and dynamics. Third, the influence of the radiative heat transfer from the solid oxides can be studied more carefully by generating a stagnant spherical shell of condensed products undisturbed by buoyancy.

Branch, M.C.↗
DOE OSTI2021

Electrolyte Regulating toward Stabilization of Cobalt-Free Ultrahigh-Nickel Layered Oxide Cathode in Lithium-Ion Batteries

Cobalt (Co)-free ultrahigh-nickel (Ni) layered oxides exhibit a double-edged competitive advantages in reducing the cathode cost and boosting the energy density, promising the sustainable development of batteries for electric vehicles. However, the increased Ni content, resultantly more highly oxidative Ni 4+ , potentially induces severe capacity fading due to the aggravated side reactions, limiting the practical applications. Here, we evaluate the compatibility of two localized high-concentration electrolytes (LHCEs) with LiNi 0.96 Mg 0.02 Ti 0.02 O 2 (NMT) cathode under a high charging voltage of 4.4 V in lithium ion batteries. The LHCE with EC additive enables the formation of stable interfacial layers on both NMT cathode and graphite anode, thus realizing a capacity retention of 97.2% over 200 cycles at 25 °C and high reversible capacities of ~180.2 and ~185.8 mAh g -1 , respectively, at 5C charge rate and 5C discharge rate. This study offers a promising approach to enable Co-free ultrahigh-Ni layered oxides for practical applications.

25 ENERGY STORAGE↗
DOE OSTI2022

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗