Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Engine”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A quasi-dimensional model for SI engines fueled with gasoline–alcohol blends: Knock modeling

As knock is one of the main factors limiting the efficiency of spark-ignition engines, the introduction of alcohol blends could help to mitigate knock concerns due to the elevated knock resistance of these blends. A model that can accurately predict their autoignition behavior would be of great value to engine designers. The current work aims to develop such a model for alcohol–gasoline blends. First, a mixing rule for the autoignition delay time of alcohol–gasoline blends is proposed. Subsequently, this mixing rule is used together with an autoignition delay time correlation of gasoline and an autoignition delay time cor-relation of methanol in a knock integral model that is implemented in a two-zone engine code. The pre-dictive performance of the resulting model is validated through comparison against experimental measurements on a CFR engine for a range of gasoline–methanol blends. The knock limited spark advance, the knock intensity, the knock onset crank angle and the value of the knock integral at the experimental knock onset have been simulated and compared to the experimental values derived from in-cylinder pressure measurements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen

Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗
DOE OSTI2014

Metallographic screening of grain boundary engineered type 304 austenitic stainless steel

An electrochemical etching method for the identification of grain boundary engineered type 304 austenitic stainless steel microstructures is described. The method can be applied for rapid microstructure screening to complement electron backscatter diffraction analysis. A threshold parameter to identify grain boundary engineered microstructure is proposed, and the application of metallographic etching for characterising the degree of grain boundary engineering discussed. - Highlights: • As-received (annealed) and grain boundary engineered microstructures were compared. • Electro-chemical polarisation in nitric acid solutions was carried out. • A metallographic screening method has been developed. • The screening method complements EBSD analysis for microstructure identification.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An asynchronous traversal engine for graph-based rich metadata management

Rich metadata in high-performance computing (HPC) systems contains extended information about users, jobs, data files, and their relationships. Property graphs are a promising data model to represent heterogeneous rich metadata flexibly. Specifically, a property graph can use vertices to represent different entities and edges to record the relationships between vertices with unique annotations. The high-volume HPC use case, with millions of entities and relationships, naturally requires an out-of-core distributed property graph database, which must support live updates (to ingest production information in real time), low-latency point queries (for frequent metadata operations such as permission checking), and large-scale traversals (for provenance data mining). Among these needs, large-scale property graph traversals are particularly challenging for distributed graph storage systems. Most existing graph systems implement a "level synchronous" breadth-first search algorithm that relies on global synchronization in each traversal step. This performs well in many problem domains; but a rich metadata management system is characterized by imbalanced graphs, long traversal lengths, and concurrent workloads, each of which has the potential to introduce or exacerbate stragglers (i.e., abnormally slow steps or servers in a graph traversal) that lead to low overall throughput for synchronous traversal algorithms. Previous research indicated that the straggler problem can be mitigated by using asynchronous traversal algorithms, and many graph-processing frameworks have successfully demonstrated this approach. Such systems require the graph to be loaded into a separate batch-processing framework instead of being iteratively accessed, however. In this work, we investigate a general asynchronous graph traversal engine that can operate atop a rich metadata graph in its native format. We outline a traversal-aware query language and key optimizations (traversal-affiliate caching and execution merging) necessary for efficient performance. We further explore the effect of different graph partitioning strategies on the traversal performance for both synchronous and asynchronous traversal engines. Our experiments show that the asynchronous graph traversal engine is more efficient than its synchronous counterpart in the case of HPC rich metadata processing, where more servers are involved and larger traversals are needed. Furthermore, the asynchronous traversal engine is more adaptive to different graph partitioning strategies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Cell–scaffold interaction within engineered tissue

The structure of a tissue engineering scaffold plays an important role in modulating tissue growth. A novel gelatin–chitosan (Gel–Cs) scaffold with a unique structure produced by three-dimensional printing (3DP) technology combining with vacuum freeze-drying has been developed for tissue-engineering applications. The scaffold composed of overall construction, micro-pore, surface morphology, and effective mechanical property. Such a structure meets the essential design criteria of an ideal engineered scaffold. The favorable cell–matrix interaction supports the active biocompatibility of the structure. The structure is capable of supporting cell attachment and proliferation. Cells seeded into this structure tend to maintain phenotypic shape and secreted large amounts of extracellular matrix (ECM) and the cell growth decreased the mechanical properties of scaffold. This novel biodegradable scaffold has potential applications for tissue engineering based upon its unique structure, which acts to support cell growth. - Highlights: • The scaffold is not only for providing a surface for cell residence but also for determining cell phenotype and retaining structural integrity. • The mechanical property of scaffold can be affected by activities of cell. • The scaffold provides a microenvironment for cell attachment, growth, and migration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

The importance of sourcing enzymes from non-conventional fungi for metabolic engineering and biomass breakdown

A wealth of fungal enzymes has been identified from nature, which continue to drive strain engineering and bioprocessing for a range of industries. However, while a number of clades have been investigated, the vast majority of the fungal kingdom remains unexplored for industrial applications. In this study, we discuss selected classes of fungal enzymes that are currently in biotechnological use, and explore more basal, non-conventional fungi and their underexploited biomass-degrading mechanisms as promising agents in the transition towards a bio-based society. Of special interest are anaerobic fungi like the Neocallimastigomycota, which were recently found to harbor the largest diversity of biomass-degrading enzymes among the fungal kingdom. Enzymes sourced from these basal fungi have been used to metabolically engineer substrate utilization in yeast, and may offer new paths to lignin breakdown and tunneled biocatalysis. We also contrast classic enzymology approaches with emerging ‘omics’-based tools to decipher function within novel fungal isolates and identify new promising enzymes. Recent developments in genome editing are expected to accelerate discovery and metabolic engineering within these systems, yet are still limited by a lack of high-resolution genomes, gene regulatory regions, and even appropriate culture conditions. Lastly, we present new opportunities to harness the biomass-degrading potential of undercharacterized fungi via heterologous expression and engineered microbial consortia.

09 BIOMASS FUELS↗
DOE OSTI2020

Enhanced 2'-Fucosyllactose production by engineered Saccharomyces cerevisiae using xylose as a co-substrate

2'-Fucosyllactose (2'-FL), a human milk oligosaccharide with confirmed benefits for infant health, is a promising infant formula ingredient. Although Escherichia coli, Saccharomyces cerevisiae, Corynebacterium glutamicum, and Bacillus subtilis have been engineered to produce 2'-FL, their titers and productivities need be improved for economic production. Glucose along with lactose have been used as substrates for producing 2'-FL, but accu- mulation of by-products due to overflow metabolism of glucose hampered efficient production of 2' -FL regardless of a host strain. To circumvent this problem, we used xylose, which is the second most abundant sugar in plant cell wall hydrolysates and is metabolized through oxidative metabolism, for the production of 2'-FL by engi- neered yeast. Specifically, we modified an engineered S. cerevisiae strain capable of assimilating xylose to pro- duce 2' -FL from a mixture of xylose and lactose. First, a lactose transporter (Lac12) from Kluyveromyces lactis was introduced. Second, a heterologous 2'-FL biosynthetic pathway consisting of enzymes Gmd, WcaG, and WbgL from Escherichia coli was introduced. Third, we adjusted expression levels of the heterologous genes to maximize 2'-FL production. The resulting engineered yeast produced 25.5 g/L of 2'-FL with a volumetric productivity of 0.35 g/L∙h in a fed-batch fermentation with lactose and xylose feeding to mitigate the glucose repression. Interestingly, the major location of produced 2'-FL by the engineered yeast can be changed using different culture media. While 72% of the produced 2'-FL was secreted when a complex medium was used, 82% of the produced 2'-FL remained inside the cells when a minimal medium was used. In conclusion, as yeast extract is already used as food and animal feed ingredients, 2'-FL enriched yeast extract can be produced cost-effectively using the 2'-FL-accumu- lating yeast cells.

2′ -fucosyllactose↗
DOE OSTI2018

Structural Control of Nonnative Ligand Binding in Engineered Mutants of Phosphoenolpyruvate Carboxykinase

Protein engineering to alter recognition underlying ligand binding and activity has enormous potential. Here, ligand binding for Escherichia coli phosphoenolpyruvate carboxykinase (PEPCK), which converts oxaloacetate into CO 2 and phosphoenolpyruvate as the first committed step in gluconeogenesis, was engineered to accommodate alternative ligands as an exemplary system with structural information. From our identification of bicarbonate binding in the PEPCK active site at the supposed CO 2 binding site, we probed binding of nonnative ligands with three oxygen atoms arranged to resemble the bicarbonate geometry. Crystal structures of PEPCK and point mutants with bound nonnative ligands thiosulfate and methanesulfonate along with strained ATP and reoriented oxaloacetate intermediates and unexpected bicarbonate were determined and analyzed. The mutations successfully altered the bound ligand position and orientation and its specificity: mutated PEPCKs bound either thiosulfate or methanesulfonate but never both. Computational calculations predicted a methanesulfonate binding mutant and revealed that release of the active site ordered solvent exerts a strong influence on ligand binding. Besides nonnative ligand binding, one mutant altered the Mn 2+ coordination sphere: instead of the canonical octahedral ligand arrangement, the mutant in question had an only five-coordinate arrangement. From this work, critical features of ligand binding, position, and metal ion cofactor geometry required for all downstream events can be engineered with small numbers of mutations to provide insights into fundamental underpinnings of protein–ligand recognition. Finally, through structural and computational knowledge, the combination of designed and random mutations aids in the robust design of predetermined changes to ligand binding and activity to engineer protein function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Embracing the Intersections of Environmental Science, Engineering, and Geosciences to Solve Grand Challenges of the 21st Century

The U.S. National Academies report on Environmental Engineering for the 21st Century identified five grand challenges of sustainably supplying food, water, and energy; curbing climate change and adapting to its impacts; designing a future without pollution and waste; creating efficient, healthy, resilient cities; and fostering informed decisions and actions. (1) Addressing many of the grand challenges will require embracing the intersections of environmental science, engineering, and geosciences. These three fields are inherently interdisciplinary, and they naturally intersect with each other (Figure 1). Geosciences, or Earth sciences, study the dynamics of different spheres of Earth. One of its missions is to detect the availability of mineral, water, and fuel resources, for sustainable development, and new research opportunities were identified in “coevolution of life, environment, and climate” and “biogeochemical and water cycles in terrestrial environments and impacts of global change” by the U.S. National Research Council. (2) Environmental science and engineering focus on the spheres that intersect with human activities. Environmental science puts an emphasis on understanding the migration of naturally occurring and anthropogenic contaminants in the environment and their impact on ecosystem and human health, and environmental engineering centers on developing technologies for water supply, mineral exploration, and environmental remediation to mitigate adverse impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Deactivation of three-way catalysts coated within gasoline particulate filters by engine oil-derived chemicals

Three-way catalysts (TWC) coated within gasoline particulate filter (GPF) walls (TWC/GPF) were tested in a gasoline direct injection (GDI) engine to investigate the impact of engine oil-derived chemicals on TWC performance and possible deactivation factors. Catalyst performance of the lab-aged TWC/GPFs was retarded with ash loading, especially NOx conversions under 300 °C. Characterization results from the lab-aging condition show that while the disruption of oxygen storage capacity (OSC) materials was found to be minor or negligible, Pd particle growth and weakened Pd–OSC interaction were observed. In comparison, the field-aged TWC/GPF showed more apparent degradation of TWC components due to engine-oil-derived chemicals; the formation of CePO 4 and Ce 2 (SO 4 ) 4 results in decreasing OSC that lowers oxygen release capability, in addition to more noticeable Pd particle growth and weakened Pd–OSC interaction. Different from the lab-aged TWC/GPF, the degree of deactivation in the field-aged TWC/GPF appeared to increase along the direction of the flow path in the order of outlet > mid > inlet, proposing that engine-oil-derived chemicals accelerated TWC deactivation when combined with increased exhaust temperatures.

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

Boron Doping and Defect Engineering of Graphene Aerogels for Ultrasensitive NO 2 Detection

In this study, boron-doped and defect-engineered graphene aerogels are prepared using triphenyl boron as a boron precursor and subsequent heat treatments. The boron chemistry and concentration in the graphene lattice are found to be highly dependent on the temperature used to activate boron. At 1500 °C, boron is incorporated at 3.2 atom % through a combination of B–C, B–N, and B–O bonds. At 1750 °C, the boron concentration decreases to 0.7 atom % and is predominantly incorporated through B–N bonding. Higher temperatures result in complete expulsion of boron from the lattice, leaving behind defects that are found to be beneficial for NO 2 gas detection. The gas sensing properties are explored to gain insight into the impact of boron chemistry on the sensing performance. A highly sensitive and selective conductometric NO 2 sensor is fabricated on a low-power microheater. Defect-engineered graphene aerogels with no boron remaining have superior gas detection properties. At an optimum sensing temperature of 240 °C, the defect-engineered aerogel has a theoretical detection limit of 7 ppb for NO 2 and response and recovery times of 100 and 300 s, respectively, with excellent selectivity over ammonia and hydrogen. Lastly, the superior gas sensing performance of defect-engineered graphene aerogels has remarkable implications for their performance in catalysis and energy storage applications.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Engineering a Full Gamut of Structural Colors in All-Dielectric Mesoporous Network Metamaterials

Structural colors are a result of the scattering of certain frequencies of the incident light on micro- or nanoscale features in a material. This is a quite different phenomenon from that of colors produced by absorption of different frequencies of the visible spectrum by pigments or dyes, which is the most common way of coloring used in our daily life. However, structural colors are more robust and can be engineered to span most of the visible spectrum without changing the base material, only its internal structure. They are abundant in nature, with examples as colorful as beetle shells and butterfly wings, but there are few ways of preparing them for large-scale commercial applications for real-world uses. In this work, we present a technique to create a full gamut of structural colors based on a low-cost, robust, and scalable fabrication of periodic network structures in porous alumina as well as the strategy to theoretically predict and engineer different colors on demand. We experimentally demonstrate mesoporous network metamaterial structures with engineered colors spanning the whole optical spectrum and discuss their applications in sensing, environmental monitoring, biomimetic tissues engineering, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Engineering Bacteria to Catabolize the Carbonaceous Component of Sarin: Teaching E. coli to Eat Isopropanol

In this paper, we report an engineered strain of Escherichia coli that catabolizes the carbonaceous component of the extremely toxic chemical warfare agent sarin. Enzymatic decomposition of sarin generates isopropanol waste that, with this engineered strain, is then transformed into acetyl-CoA by enzymatic conversion with a key reaction performed by the acetone carboxylase complex (ACX). We engineered the heterologous expression of the ACX complex from Xanthobacter autotrophicus PY2 to match the naturally occurring subunit stoichiometry and purified the recombinant complex from E. coli for biochemical analysis. Incorporating this ACX complex and enzymes from diverse organisms, we introduced an isopropanol degradation pathway in E. coli, optimized induction conditions, and decoupled enzyme expression to probe pathway bottlenecks. Our engineered E. coli consumed 65% of isopropanol compared to no-cell controls and was able to grow on isopropanol as a sole carbon source. Finally, in the process, reconstitution of this large ACX complex (370 kDa) in a system naïve to its structural and mechanistic requirements allowed us to study this otherwise cryptic enzyme in more detail than would have been possible in the less genetically tractable native Xanthobacter system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Engineering glucose metabolism of Escherichia coli under nitrogen starvation

A major aspect of microbial metabolic engineering is the development of chassis hosts that have favorable global metabolic phenotypes, and can be further engineered to produce a variety of compounds. In this work, we focus on the problem of decoupling growth and production in the model bacterium Escherichia coli, and in particular on the maintenance of active metabolism during nitrogen-limited stationary phase. We find that by overexpressing the enzyme PtsI, a component of the glucose uptake system that is inhibited by α-ketoglutarate during nitrogen limitation, we are able to achieve a fourfold increase in metabolic rates. Alternative systems were also tested: chimeric PtsI proteins hypothesized to be insensitive to α-ketoglutarate did not improve metabolic rates under the conditions tested, whereas systems based on the galactose permease GalP suffered from energy stress and extreme sensitivity to expression level. Overexpression of PtsI is likely to be a useful arrow in the metabolic engineer’s quiver as productivity of engineered pathways becomes limited by central metabolic rates during stationary phase production processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Solutions in microbiome engineering: prioritizing barriers to organism establishment

Abstract Microbiome engineering is increasingly being employed as a solution to challenges in health, agriculture, and climate. Often manipulation involves inoculation of new microbes designed to improve function into a preexisting microbial community. Despite, increased efforts in microbiome engineering inoculants frequently fail to establish and/or confer long-lasting modifications on ecosystem function. We posit that one underlying cause of these shortfalls is the failure to consider barriers to organism establishment. This is a key challenge and focus of macroecology research, specifically invasion biology and restoration ecology. We adopt a framework from invasion biology that summarizes establishment barriers in three categories: (1) propagule pressure, (2) environmental filtering, and (3) biotic interactions factors. We suggest that biotic interactions is the most neglected factor in microbiome engineering research, and we recommend a number of actions to accelerate engineering solutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Atomically engineering activation sites onto metallic 1T-MoS 2 catalysts for enhanced electrochemical hydrogen evolution

Engineering catalytic sites at the atomic level provides an opportunity to understand the catalyst’s active sites, which is vital to the development of improved catalysts. Here we show a reliable and tunable polyoxometalate template-based synthetic strategy to atomically engineer metal doping sites onto metallic 1T-MoS 2 , using Anderson-type polyoxometalates as precursors. Benefiting from engineering nickel and oxygen atoms, the optimized electrocatalyst shows great enhancement in the hydrogen evolution reaction with a positive onset potential of ~ 0 V and a low overpotential of –46 mV in alkaline electrolyte, comparable to platinum-based catalysts. First-principles calculations reveal co-doping nickel and oxygen into 1T-MoS 2 assists the process of water dissociation and hydrogen generation from their intermediate states. This research will expand on the ability to improve the activities of various catalysts by precisely engineering atomic activation sites to achieve significant electronic modulations and improve atomic utilization efficiencies.

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

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗