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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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DOE OSTI2020

Chemoinformatic-Guided Engineering of Polyketide Synthases

Polyketide synthase (PKS) engineering is an attractive method to generate new molecules such as commodity, fine and specialty chemicals. A significant challenge is re-engineering a partially reductive PKS module to produce a saturated β-carbon through a reductive loop (RL) exchange. In this work, we sought to establish that chemoinformatics, a field traditionally used in drug discovery, offers a viable strategy for RL exchanges. We first introduced a set of donor RLs of diverse genetic origin and chemical substrates into the first extension module of the lipomycin PKS (LipPKS1). Product titers of these engineered unimodular PKSs correlated with chemical structure similarity between the substrate of the donor RLs and recipient LipPKS1, reaching a titer of 165 mg/L of short-chain fatty acids produced by the host Streptomyces albus J1074. Finally, expanding this method to larger intermediates that require bimodular communication, we introduced RLs of divergent chemosimilarity into LipPKS2 and determined triketide lactone production. Collectively, we observed a statistically significant correlation between atom pair chemosimilarity and production, establishing a new chemoinformatic method that may aid in the engineering of PKSs to produce desired, unnatural products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Abstract Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Effect of first and second generation biodiesel blends on engine performance and emission

The biodiesel is a potential source of alternative fuel which can be used at different proportions with diesel fuel. This study experimentally investigated the effect of blend percentage on diesel engine performance and emission using first generation (soybean) and second generation (waste cooking) biodiesel. The characterization of the biodiesel was done according to ASTM and EN standards and compared with ultralow sulfur diesel (ULSD) fuel. A multi-cylinder test bed engine coupled with electromagnetic dynamometer and 5 gas analyzer were used for engine performance and emission test. The investigation was made using B5, B10 and B15 blends for both biodiesels. The study found that brake power (BP) and brake torque (BT) slightly decreases and brake specific fuel consumption (BSFC) slightly increases with an increase in biodiesel blends ratio. Besides, a significant reduction in exhaust emissions (except NO{sub x} emission) was found for both biodiesels compared to ULSD. Soybean biodiesel showed better engine performance and emissions reduction compared with waste cooking biodiesel. However, NO{sub x} emission for B5 waste cooking biodiesel was lower than soybean biodiesel.

09 BIOMASS FUELS↗

DOE OSTI2020

Operando measurement of lattice strain in internal combustion engine components by neutron diffraction

Significance Internal combustion engine components experience extreme thermomechanical cycling during operation, and the continuing need to improve engine efficiency while maintaining or improving reliability drives the development of lightweight materials with improved thermal and mechanical integrity. Understanding the behavior of new materials in dynamic operation requires operando characterization tools, but conventional in situ measurements of material behavior during real engine operation are very limited, and no practical means exist to replicate such extreme dynamics for ex situ study. In this work, we demonstrate that the penetrating power of neutrons can provide noninvasive measurement of lattice strains inside components of a firing engine, enabling the operando study of complex load states and thermal gradients throughout the solid materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Engineered mRNA–ribosome fusions for facile biosynthesis of selenoproteins

Ribosomes are often used in synthetic biology as a tool to produce desired proteins with enhanced properties or entirely new functions. However, repurposing ribosomes for producing designer proteins is challenging due to the limited number of engineering solutions available to alter the natural activity of these enzymes. In this study, we advance ribosome engineering by describing a novel strategy based on functional fusions of ribosomal RNA (rRNA) with messenger RNA (mRNA). Specifically, we create an mRNA–ribosome fusion called RiboU, where the 16S rRNA is covalently attached to selenocysteine insertion sequence (SECIS), a regulatory RNA element found in mRNAs encoding selenoproteins. When SECIS sequences are present in natural mRNAs, they instruct ribosomes to decode UGA codons as selenocysteine (Sec, U) codons instead of interpreting them as stop codons. This enables ribosomes to insert Sec into the growing polypeptide chain at the appropriate site. Our work demonstrates that the SECIS sequence maintains its functionality even when inserted into the ribosome structure. As a result, the engineered ribosomes RiboU interpret UAG codons as Sec codons, allowing easy and site-specific insertion of Sec in a protein of interest with no further modification to the natural machinery of protein synthesis. To validate this approach, we use RiboU ribosomes to produce three functional target selenoproteins in Escherichia coli by site-specifically inserting Sec into the proteins’ active sites. Overall, our work demonstrates the feasibility of creating functional mRNA–rRNA fusions as a strategy for ribosome engineering, providing a novel tool for producing Sec-containing proteins in live bacterial cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Single-atom heat engine as a sensitive thermal probe

We propose employing a quantum heat engine as a sensitive probe for thermal baths. In particular, we study a single-atom Otto engine operating in an open thermodynamic cycle. Owing to its cyclic nature, the engine is capable of translating small temperature differences between two baths into a macroscopic oscillation in a flywheel. We present analytical and numerical modeling of the quantum dynamics of the engine and estimate it to be capable of detecting temperature differences as small as 2 μK. This sensitivity can be further improved by utilizing quantum resources such as squeezing of the ion motion. The proposed scheme does not require quantum state initialization and is able to detect small temperature differences in a wide range of base temperatures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering

Lidar-assisted control is a promising technology for reducing the levelized cost of energy from wind turbines, but quantifying its impact at the overall system level requires sophisticated systems engineering analysis and optimization frameworks. The joint workshop on Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering was held by the International Energy Agency Wind Task 32 (Lidar) and Task 37 (Systems Engineering) in October 2019 to address this challenge. This paper summarizes the outcome of the workshop and presents a road map for further research. The most promising applications of lidar-assisted control identified at the workshop and discussed here include 1) increasing annual energy production, 2) decreasing capital expenditure costs by reducing design loads, 3) extending turbine lifetime by reducing operating loads, and 4) enabling wind turbine class upgrades. For each application, we review the state of the art and highlight remaining research needs. Finally, we discuss strategies for addressing these research needs by conducting high-fidelity systems engineering optimizations.

17 WIND ENERGY↗

DOE OSTI2026

Dressed-State Hamiltonian Engineering in a Strongly Interacting Solid-State Spin Ensemble

In quantum science applications, ranging from many-body physics to quantum metrology, dipolar interactions in spin ensembles are often controlled via Floquet engineering. However, this technique typically reduces the interaction strength between spins and effectively weakens the coupling to a target sensing field, limiting the metrological sensitivity. In this Letter, we develop and demonstrate an alternative method that directly tunes the native dipolar interaction in an ensemble of nitrogen-vacancy (NV) centers in diamond, thereby overcoming these limitations inherent to Floquet engineering. Our approach utilizes dressed-state qubit encoding under a bias magnetic field applied perpendicular to the crystal lattice orientation. This method leads to a 3.2× enhancement of the dimensionless coherence parameter JT 2 compared to state-of-the-art Floquet engineering and a 2.6× (8.3 dB) enhanced sensitivity in ac magnetometry. Furthermore, our results provide a powerful Hamiltonian engineering tool for future studies with NV ensembles and other interacting higher-spin (S > $\frac{1}{2}$) systems.

Quantum control↗

DOE OSTI2021

Quantum Engineering With Hybrid Magnonic Systems and Materials (Invited Paper)

Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitations or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and exibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization.

42 ENGINEERING↗

DOE OSTI2023

Environmental microbiome engineering for the mitigation of climate change

Abstract Environmental microbiome engineering is emerging as a potential avenue for climate change mitigation. In this process, microbial inocula are introduced to natural microbial communities to tune activities that regulate the long‐term stabilization of carbon in ecosystems. In this review, we outline the process of environmental engineering and synthesize key considerations about ecosystem functions to target, means of sourcing microorganisms, strategies for designing microbial inocula, methods to deliver inocula, and the factors that enable inocula to establish within a resident community and modify an ecosystem function target. Recent work, enabled by high‐throughput technologies and modeling approaches, indicate that microbial inocula designed from the top‐down, particularly through directed evolution, may generally have a higher chance of establishing within existing microbial communities than other historical approaches to microbiome engineering. We address outstanding questions about the determinants of inocula establishment and provide suggestions for further research about the possibilities and challenges of environmental microbiome engineering as a tool to combat climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Cooled Spray Technology for Particulate Reduction in a Heavy-Duty Engine

Cooled spray (CS) technology passively reduces particulate matter (PM) emissions from diesel engines compared to non-CS-equipped diesel engines. CS inserts are mounted near the injector nozzle and control mixing so that the fuel and air can premix while limiting combustion near fuel-rich zones, thereby reducing the formation of particulate matter. CS components contain no moving parts and could be installed as a retrofit or built into new engines. However, CS technology is early in its development, and further investigations are needed to understand the overall performance implications and practicality of the technology. In this paper, we investigate several important aspects of CS, providing a clearer picture of some challenges and potential benefits of CS. Two alignment techniques are used to characterize measurement ease and bias, namely, an optical alignment and spray-plug impact alignment. While the optical technique facilitates alignment more easily, a bias was measured between the optical and spray-plug techniques, suggesting the optical technique may have insufficient accuracy without additional corrections. We also evaluate the engine performance of a well-aligned and poorly aligned CS insert, compared to the baseline configuration. The poorly aligned insert shows slower combustion than the baseline and mixed overall performance. However, the well-aligned insert shows faster combustion than the baseline and PM emission reduction at most operating conditions, with some conditions showing PM reduction up to 80%. Furthermore, the results of this paper highlight the alignment challenges of CS technology as well as the potential PM reduction benefit of the technology.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2018

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments— including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers—is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.

computational science and engineering↗

DOE OSTI2015

Invited Review. Combustion instability in spray-guided stratified-charge engines. A review

Our article reviews systematic research on combustion instabilities (principally rare, random misfires and partial burns) in spray-guided stratified-charge (SGSC) engines operated at part load with highly stratified fuel -air -residual mixtures. Results from high-speed optical imaging diagnostics and numerical simulation provide a conceptual framework and quantify the sensitivity of ignition and flame propagation to strong, cyclically varying temporal and spatial gradients in the flow field and in the fuel -air -residual distribution. For SGSC engines using multi-hole injectors, spark stretching and locally rich ignition are beneficial. Moreover, combustion instability is dominated by convective flow fluctuations that impede motion of the spark or flame kernel toward the bulk of the fuel, coupled with low flame speeds due to locally lean mixtures surrounding the kernel. In SGSC engines using outwardly opening piezo-electric injectors, ignition and early flame growth are strongly influenced by the spray's characteristic recirculation vortex. For both injection systems, the spray and the intake/compression-generated flow field influence each other. Factors underlying the benefits of multi-pulse injection are identified. Finally, some unresolved questions include (1) the extent to which piezo-SGSC misfires are caused by failure to form a flame kernel rather than by flame-kernel extinction (as in multi-hole SGSC engines); (2) the relative contributions of partially premixed flame propagation and mixing-controlled combustion under the exceptionally late-injection conditions that permit SGSC operation on E85-like fuels with very low NO x and soot emissions; and (3) the effects of flow-field variability on later combustion, where fuel-air-residual mixing within the piston bowl becomes important.

42 ENGINEERING↗

DOE OSTI2017

An assessment of thermodynamic merits for current and potential future engine operating strategies

The present work compares the fundamental thermodynamic underpinnings (i.e., working fluid properties and heat release profile) of various combustion strategies with engine measurements. The approach employs a model that separately tracks the impacts on efficiency due to differences in rate of heat addition, volume change, mass addition, and molecular weight change for a given combination of working fluid, heat release profile, and engine geometry. Comparative analysis between measured and modeled efficiencies illustrates fundamental sources of efficiency reductions or opportunities inherent to various combustion regimes. Engine operating regimes chosen for analysis include stoichiometric spark-ignited combustion and lean compression-ignited combustion including HCCI, SA-HCCI, RCCI, GCI, and CDC. Within each combustion regime, effects such as engine load, combustion duration, combustion phasing, combustion chamber geometry, fuel properties, and charge dilution are explored. Model findings illustrate that even in the absence of losses such as heat transfer or incomplete combustion, the maximum possible thermal efficiency inherent to each operating strategy varies to a significant degree. Additionally, the experimentally measured losses are observed to be unique within a given operating strategy. The findings highlight the fact that in order to create a roadmap for future directions in ICE technologies, it is important to not only compare the absolute real-world efficiency of a given combustion strategy, but to also examine the measured efficiency in context of what is thermodynamically possible with the working fluid and boundary conditions prescribed by a strategy.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2017

Examining the role of flame topologies and in-cylinder flow fields on cyclic variability in spark-ignited engines using large-eddy simulation

In this work we have studied cycle-to-cycle variation (CCV) in a spark-ignited (SI) engine using large-eddy simulation (LES) in conjunction with the G-equation combustion model. A single cylinder of a four-cylinder port-fueled SI engine was simulated. 49 consecutive full cycles were computed. The operating condition studied in this work is stoichiometric and stable, and represents a load of 16 bar brake mean effective pressure (BMEP), and an engine speed of 2500 revolutions per minute (r/min). The CFD simulation shows good agreement in terms of in-cylinder pressure prediction with respect to the experiments, and is also able to capture the range of CCV observed in experiments. Further, neither the simulation, nor the experiments show any distinguishable pattern in the sequence of high and low cycles. We numerically decoupled the effects of variations in equivalence ratio fields and velocity fields to isolate the effects of differences in the velocity field and differences in the equivalence ratio field on flame development and propagation. Based on this study we inferred that for this engine, under the operating conditions studied, the differences in burn rates can be attributed to the differences in the velocity flow-field in the region around the spark gap during ignition. We then performed an analysis to identify the correlation between peak cylinder pressure (PCP) and flame topologies over all the simulated cycles. We found that high cycles (higher PCP values) are strongly correlated to flatter flame volume shapes (flattened in the piston-to-head direction), and volumes that are more symmetric about the ignition axis. In addition, these kinds of flame volumes were found to correlate well with lower values of prior-to-ignition velocity going from the intake to the exhaust side (mean flow caused by tumble) at the spark, and also higher values of prior-to-ignition velocity in the piston-to-head direction.

CCV↗

DOE OSTI2018

Correlation of nanoparticle size distribution features to spatiotemporal flame luminosity in gasoline direct injection engines

Particle size distribution measured by mobility instruments is a common diagnostic used to characterize ultrafine and nanoparticle emissions in engine exhaust; however, some features of particle size distribution data are poorly correlated to in-cylinder combustion phenomena. In this work, in-cylinder spatiotemporal flame luminosity is quantitatively correlated to features in the solid particle size distribution measured in the exhaust of a gasoline direct injection engine operating in lean and stoichiometric combustion modes. A multi-channel optical sensor was used to measure diffusion flame light intensity in different areas of the combustion chamber. Furthermore, total solid particle number and particle size distribution in the exhaust were measured using a scanning mobility particle sizer after a catalytic stripper that removed semi-volatile compounds. Results of the experiments showed that different flame phenomenon resulted in distinct particle size distribution characteristics. A large accumulation mode (particles with diameter of 50–100 nm) in the particle size distribution from stoichiometric engine operation with early injection resulted from anomalous diffusion flames like piston-top pool fires. In lean operation incorporating a secondary fuel injection, particle emissions were dominated by flame propagation through fuel-rich regions of the combustion chamber resulting in a comparatively broad particle size distribution. More generally, this work illustrates how particle size distribution data can be more accurately used to diagnose soot formation in gasoline direct injection engines.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines

Conventional compression-ignition (CI) engines have long offered high thermal efficiencies and torque across a wide range of loads, but often require extensive exhaust gas treatment that decreases efficiency to meet ever-increasing emissions regulations. One strategy to decrease emissions is to split the fuel injection into a series of smaller injections. In this paper, we explore a new way of discovering optimal control strategies for the next generation of CI engines using deep reinforcement learning (DRL). We outline a DRL procedure to maximize the weighted reward of engine work while minimizing end-of-cycle NO x emissions. Through the procedure outlined in this paper, we show that the DRL agent is able to reduce NO x emissions threefold while only decreasing network by 2%. We demonstrate the use of transfer learning (TL) across hierarchies of physical models to accelerate the learning process, making this approach feasible for a range of control problems within this space. This paper presents a framework and demonstration for using DRL to design control systems in technology areas such as multi-pulse engine control where a hierarchy of models combined with multi-objective rewards are used for optimal operation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Fuel-air mixing in motored CFR engine at research octane number (RON) relevant condition

This paper presents a three-dimensional (3-D) computational fluid dynamics (CFD) study of a motored cooperative fuel research (CFR) engine at research octane number (RON) relevant condition. The boundary conditions for 3-D simulations were generated with a one-dimensional GT-Power model. For the first time in literature, a carburetor was added to a virtual CFR engine model with 3-D CFD. Therefore, the proposed setup can simulate the fuel and thermal stratifications inside the engine cylinder with realistic detail. The transient simulations in this work were performed within the Reynolds-averaged Navier-Stokes (RANS) framework with a Realizable k-ε turbulence model. Major conclusions from the present work are: (1) The in-cylinder flow of the CFR engine is swirl-dominated due to the existence of the intake valve shroud. (2) There is a significant amount of liquid droplets entering the cylinder during the intake stroke. The maximum instantaneous amount of liquid for 50% PRF 87 (containing 87% iso-octane and 13% n-heptane (v/v)) and 50% ethanol mixture is indicated to be around 26% of total injected fuel mass. (3) The heat of vaporization (HoV) of the fuel is responsible for creating both temperature and charge stratification inside the cylinder.

33 ADVANCED PROPULSION SYSTEMS↗