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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 73 records · Page 4

Aerodynamic Limits on Large Civil Tiltrotor Sizing and Efficiency

The NASA Large Civil Tiltrotor (2nd generation, or LCTR2) has been the reference design for avariety of NASA studies of design optimization, engine and gearbox technology, handling qualities, andother areas, with contributions from NASA Ames, Glenn and Langley Centers, plus academic and industrystudies. Ongoing work includes airfoil design, 3D blade optimization, engine technology studies, andwingrotor aerodynamic interference. The proposed paper will bring the design up to date with the latestresults of such studies, then explore the limits of what aerodynamic improvements might hope toaccomplish. The purpose is two-fold: 1) determine where future technology studies might have the greatestpayoff, and 2) establish a stronger basis of comparison for studies of other vehicle configurations andmissions.

Large Civil Tiltrotor↗

Tailored Bioblendstocks With Low Environmental Impact To Optimize MCCI Engines

This project seeks to overcome impediments to expansion of algae cultivation and conversion into fuels to displace petroleum and reduce greenhouse gas (GHG) emissions. The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction relative to petroleum diesel, reduce sooting propensity, increase cetane number, improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. These objectives are being accomplished by: Applying cultivation of algae polycultures to achieve robustness and productivity, Converting whole algae to bio-hydrocarbons via Hydrothermal Liquefaction (HTL) to make a biocrude and up-grading the biocrude via hydroprocessing to obtain tailored bioblendstocks for diesel fuel, Optimizing diesel (MCCI) combustion through blending model compounds into diesel fuel to represent the tailored bioblendstocks through experiments and numerical simulation.

09 BIOMASS FUELS↗

Accelerating Engineered Microbe Optimization through Machine Learning and Multi-Omics Datasets [Abstract]

The Agile Biofoundry (ABF) is a multi-national lab consortium funded by the DOE Bioenergy Technologies Office that has developed a biofoundry enabling the rapid deployment of bioproducts into the market. The ABF is a flexible platform that can adjust to the needs of numerous government, academic and industrial partners, thus enabling them to rapidly develop and optimize the production of a wide range of bioproducts. To demonstrate this capability, three ABF labs (NTESS, LBNL, and PNNL) have collaborated with the biomanufacturer Lygos, Inc. to use the ABF to demonstrate a high-throughput Design-Build-Test-Learn (DBTL) engineering cycle incorporating multi-omics analysis and machine learning with best in industry cycle times.

60 APPLIED LIFE SCIENCES↗

Sustainable production of 2,3,5,6-Tetramethylpyrazine at high titer in engineered Corynebacterium glutamicum

The industrial amino acid production workhorse, Corynebacterium glutamicum naturally produces low levels of 2,3,5,6-tetramethylpyrazine (TMP), a valuable flavor, fragrance, and commodity chemical. Here, we demonstrate TMP production (~0.8 g L –1 ) in C. glutamicum type strain ATCC13032 via overexpression of acetolactate synthase and/or α-acetolactate decarboxylase from Lactococcus lactis in CGXII minimal medium supplemented with 40 g L –1 glucose. This engineered strain also demonstrated growth and TMP production when the minimal medium was supplemented with up to 40% (v v –1 ) hydrolysates derived from ionic liquid-pretreated sorghum biomass. Further, a key objective was to take the fully engineered strain developed in this study and interrogate medium parameters that influence the production of TMP, a critical post-strain engineering optimization. Design of experiments in a high-throughput plate format identified glucose, urea, and their ratio as significant components affecting TMP production. These two components were further optimized using response surface methodology. In the optimized CGXII medium, the engineered strain could produce up to 3.56 g L –1 TMP (4-fold enhancement in titers and 2-fold enhancement in yield, mol mol –1 ) from 80 g L –1 glucose and 11.9 g L –1 urea in shake flask batch cultivation.

59 BASIC BIOLOGICAL SCIENCES↗

Active Site Engineering via Optimizing the Heterogeneous Support Structure for Single-Atom Catalysis

Supported single-atom catalysts show a large range of activities and selectivities that depend on the local environment of the catalytic sites. Here a theory-based optimization strategy is presented that is based on a density functional theory determination of the transition states and intermediates for a low-dimensional coordinate representation of the heterogeneity of the active sites. The approach is applied to a vanadium catalyst on an amorphous SiO 2 support that involves a large kinetic network described using a full chemistry model. Without assuming a priori scaling relations or mechanism reduction, the optimal state of heterogeneity is found to lie at atomic configurations where the activation energies for two distinct key chemical processes are equal. It is found a posteriori that the behavior of the system is consistent with linear free energy scaling relations in the randomness parameters. The energetic span theory proves quite useful in reducing the full chemistry model to a small number of key reactions. The use of a nonlinear optimization algorithm in combination with energetic span theory provides significant simplification in treating disordered systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.

59 BASIC BIOLOGICAL SCIENCES↗

Tailored Bioblendstocks With Low Environmental Impact To Optimize MCCI Engines

The prohect goal is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel.

09 BIOMASS FUELS↗

Accelerating engineered microbe optimization through machine learning and multi-omics datasets

This project demonstrated the use of a combination of multi-omics data with deep learning and a high-throughput Design- Build-Test-Learn (DBTL) cycle to improve the production of malonic acid, a versatile product with a large market. The project leveraged the unique capabilities of both Lygos and the Agile BioFoundry (ABF): Lygos provided its expertise efficiently designing, building, and cultivating P. kudriavzevii strains; LBNL, PNNL, and NTESS provided multi-omics analysis in the Test phase, LBNL provided machine learning techniques in the Learn phase to analyze the -omics datasets and make recommendations so as to increase malonic acid production in the next DBTL cycle. This project is the first to use large amounts of multi-omics time-series data to feed deep learning models, creating around 80,000 data points in a single DBTL cycle. This project has 1) demonstrated the utility of combining deep learning and multi-omics data sets by improving the production of malonic acid two fold, 2) created a large time-series datasets to be released publicly for external development of new machine learning algorithms, and 3) shown that supply chain problems, strain building bottlenecks, and adaptation times for new ML approaches are key obstacles for fast DBTL cycle times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization of engines for a commercial Mach 0.98 transport using advanced turbine cooling methods

A study was made of an advanced technology airplane using supercritical aerodynamics. Cruise Mach number was 0.98 at 40,000 feet altitude with a payload of 60,000 pounds and a range of 3000 nautical miles. Separate-flow turbofans were examined parametrically to determine the effect of sea-level-static design turbine-inlet-temperature and noise on takeoff gross weight (TOGW) assuming full-film turbine cooling. The optimum turbine inlet temperature was 2650 F. Two-stage-fan engines, with cruise fan pressure ratio of 2.25, achieved a noise goal of 103.5 EPNdB with todays noise technology while one-stage-fan engines, achieved a noise goal of 98 EPNdB. The take-off gross weight penalty to use the one-stage fan was 6.2 percent.

Kraft, G. A.↗

Optimization of engines for a commercial Mach 0.85 transport using advanced turbine cooling methods

A parametric study was made of a group of separate-flow-turbofan engines for use in advanced technology airplanes designed for a cruise Mach number of 0.85 at 40,000 feet. The three-engined airplanes were sized to carry 200 passengers 3000 nautical miles. Supercritical aerodynamics were assumed. Film-cooled turbines were used and sea-level-static turbine-rotor-inlet temperature was always 2600 F. The optimum cycle depends on the noise goal assumed. Without a noise goal the best fan pressure ratio (FPR) is about 1.90. At noise goals of FAR 36, -10 EPNdb, and -20 EPNdb, the best FPR's are 1.85, 1.76, and 1.70, respectively, at cruise. The take-off FPR's are progressively less than the cruise value as the noise goal approaches -20 EPNdb. The penalties in take-off gross weight incurred were 8.5, 19, and 64 percent at goals of FAR 36, -10 EPNdb, and -20 EPNdb, respectively.

Kraft, G. A.↗

Approximate simulation model for analysis and optimization in engineering system design

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.

Sobieszczanski-Sobieski, Jaroslaw↗