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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Modular design: Implementing proven engineering principles in biotechnology

Modular design resides at the foundation of contemporary engineering, enabling rapid, efficient, and reproducible construction and maintenance of complex systems across applications. Remarkably, modularity has recently been discovered as a governing principle in natural biological systems from genes to proteins to complex networks within a cell and organism communities. The convergent knowledge of natural and engineered modular systems provides a key to drive modern biotechnology to address emergent challenges associated with health, food, energy, and the environment. Here, we first present the theory and application of modular design in traditional engineering fields. We further discuss the significance and impact of modular architectures on systems biology and biotechnology. Next, we focus on the very recent theoretical and experimental advances in modular cell engineering that seeks to enable rapid and systematic development of microbial catalysts capable of efficiently synthesizing a large space of useful chemicals. We conclude with an outlook towards theoretical and practical opportunities for a more systematic and effective application of modular engineering in biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Utilizing the Shift Technical Engineer Pipeline to Develop the Next Generation of Engineers - 17354

As the liquid waste contractor for the U.S. Department of Energy's (DOE) Savannah River Site (SRS), Savannah River Remediation (SRR) is responsible for safely treating and dispositioning approximately 35 million gallons of liquid waste stored at SRS. To achieve this mission, SRR manages and operates several complex nuclear facilities. These nuclear facilities include the H and F Tank Farms, the Defense Waste Processing Facility (DWPF), and the Saltstone Processing and Disposal Facility. To support the operations of these complex nuclear facilities, a Shift Technical Engineer (STE) is stationed for every shift. The STE is the sole Engineering Organization representative on-shift and serves as a direct technical resource for operations, including safety basis interpretation, process monitoring and prompt troubleshooting support. The training and qualification for an STE is more intensive than for typical technical staff personnel at SRR, involving additional classes, under-instruction watches, demonstration of practical factors, and culminating in an intense oral board examination. Like many other contractors in the DOE complex, SRR faces the challenge of preparing a significant number of new generation engineers to take the place of an aging workforce. Beyond the traditional training to establish minimum technical qualifications, SRR has established a number of initiatives aimed at accelerating the process of preparing early career engineers to replace experienced senior engineers. These initiatives include an internal rotational program, technical exchange activities with companies at other DOE sites, and an STE pipeline. The STE role provides a unique mechanism for select, early career engineers to gain in-depth knowledge and significant responsibility normally not achieved until much later in their careers. Once qualification is complete, the engineers perform the STE duties, providing technical support for nuclear facility operations. In addition, creating an STE pipeline, where promising young engineers are continually being qualified to replace the on-shift STEs, provides the company with a source of experienced engineers with in-depth technical knowledge as well as valuable experience interfacing with operations and other facility support groups. This paper will discuss the STE position, the qualification process, and how SRR is using the STE qualification pipeline to benefit both the company and the individual engineer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Applying Cyber-Informed Engineering to Power System Operations

This presentation covers the interaction of the discipline of system operations with the growing body of knowledge around Cyber-Informed Engineering (CIE). First is discussion of a number of fundamental concepts for system operators - organizational division of responsibilities, human and machine cooperation, goals, and priorities. The next section covers the reasons why CIE was developed, what it is, and the key design and operational, and organizational principles of CIE. Finally, some thoughts on how CIE can be applied to power system operations are offered, along with some examples of how an organization can approach applying CIE principles in their particular circumstances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Heavy Duty Natural Gas Single Cylinder Research Engine Installation, Commissioning, and Baseline Testing

Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.

03 NATURAL GAS↗
DOE OSTI2022

Characterization of the structure and chemistry of the solid–electrolyte interface by cryo-EM leads to high-performance solid-state Li-metal batteries

Solid-state lithium-metal (Li 0 ) batteries are gaining traction for electric vehicle applications because they replace flammable liquid electrolytes with a safer, solid-form electrolyte that also offers higher energy density and better resistance against Li dendrite formation. Solid polymer electrolytes (SPEs) are highly promising candidates because of their tunable mechanical properties and easy manufacturability; however, their electrochemical instability against lithium metal (Li 0 ), mediocre conductivity, and poorly understood Li 0 /SPE interphases have prevented extensive application in real batteries. In particular, the origin of the low Coulombic efficiency (CE) associated with SPEs remains elusive, as the debate continues as to whether it originates from unfavored interfacial reactions or lithium dendritic growth and dead lithium formation. In this work, we use state-of-the-art cryo-electromicroscopy (cryoEM) imaging and spectroscopic techniques to characterize the structure and chemistry of the interface between Li 0 and a polyacrylate-based SPE. Contradicting the conventional knowledge, we find that no protective interphase forms, owing to the sustained reactions between deposited Li dendrites and polyacrylic backbones and succinonitrile plasticizer. Due to the reaction induced volume change, large amounts of cracks form inside the Li dendrites with a stress corrosion-cracking behavior, indicating that Li0cannot be passivated in this SPE system. Based on this observation, we then introduce additive engineering leveraging on the knowledge of liquid electrolytes, and demonstrate that the Li 0 surface can be effectively protected against corrosion using fluoroethylene carbonate (FEC), leading to densely packed Li 0 domes with conformal and stable solid-electrolyte interphases (SEIs) films. Owing to the high room temperature ionic conductivity of 1.01 mS/cm -1 , the high transference number of 0.57 and the stabilized lithium electrolyte interface, this improved new SPE delivers an excellent lithium plating/stripping CE of 99% and 1800 hours of stable cycling in Li||Li symmetric cells (0.2 mA/cm -2 , 1mAh/cm -2 ). Furthermore, this improved cathodic stability along with the high anodic stability enables record high cycle life of >2000 cycles for Li||LiFePO 4 and >400 cycles for Li||LiCoO 2 full cells.

25 ENERGY STORAGE↗
DOE OSTI2022

A Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering

Many subsurface engineering applications require accurate knowledge of the in-situ state of stress for their safe design and operation. Existing methods to meet this need primarily include field measurements for estimating one or more of the principal stresses from a borehole, or optimization methods for constructing a 3D geomechanical model in terms of geophysical measurements. These methods, however, often contain considerable uncertainty in estimating the state of stress. Here, in this paper, we build on a Bayesian approach to quantify uncertainty in stress estimations for subsurface engineering applications. This approach can provide an estimate of the 3D distribution of stress throughout the volume of interest and provide an estimate of the uncertainty arising from the stress measurement, the rheology parameters, and a paucity of measurements. The value of this approach is demonstrated using stress measurements from the In Salah carbon storage site, which was one of the world’s first industrial carbon capture and storage projects. This demonstration shows the application of this Bayesian approach for estimating the initial state of stress for In Salah and quantifying the uncertainty in the estimated stress. Also, an assessment of a maximum injection pressure to prevent geomechanical risks from CO 2 injection pressures is provided in terms of the probability distribution of the minimum principal stress quantified by the approach. With the In Salah case study, this paper demonstrates that using the Bayesian approach can provide additional insights for site explorations and/or project operations to make informed-site decisions for subsurface engineering applications.

58 GEOSCIENCES↗
DOE OSTI2026

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗
DOE OSTI2015

Breaking the silos: The art documentation suite

The art event-processing framework is used by almost all new experiments at Fermilab, and by several outside of Fermilab. All use art as an external product in the same sense that the compiler, ROOT, Geant4, CLHEP and boost are external products. The art team has embarked on a campaign to document art and develop training materials for new users. Many new users of art have little or no knowledge of C++, software engineering, build systems or the many external packages used by art or their experiments, such as ROOT, CLHEP, HEPPDT, and boost. To effectively teach art requires that the training materials include appropriate introductions to these topics as they are encountered. Experience has shown that simply referring readers to the existing native documentation does not work, too often a simple idea that they need to understand is described in a context that presumes prerequisites that are unimportant for a beginning user of art. There is the additional complication that the training materials must be presented in a way that does not presume knowledge of any of the experiments using art. Finally, new users of art arrive at random times throughout the year and the training materials must allow them to start to learn art at any time. This presentation will explain the strategies adopted by the art team to develop a documentation suite that complies with these boundary conditions. It will also show the present status of the documentation suite, including feedback the art team has received from pilot users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data for Glucose Assimilation Rate Determines the Partition of Flux at Pyruvate Between Lactic Acid and Ethanol in Saccharomyces cerevisiae

Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metabolize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endogenous PDCs will eliminate ethanol production, but the resulting strain suffers from C2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product without the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae expressing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L−1 from the 12 g L−1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.

Conversion↗
DOE OSTI2023

Glucose assimilation rate determines the partition of flux at pyruvate between lactic acid and ethanol in Saccharomyces cerevisiae

Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metab- olize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endoge- nous PDCs will eliminate ethanol production, but the resulting strain suffers from C 2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product with- out the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae express- ing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L –1 from the 12 g L –1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci↗
DOE OSTI2014

Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Towards a Robust Sampling Approach: A Computational Review and Design

As pointed out in several other works, the estimation of the reliability of the electrical grid can not be conducted without the estimation of the stochastic phenomena of electicity demand and electricity production by variable renewable sources. Therefore, sampling procedures have become integral in the design of engineering structures and analysis. Commonly referred to as Monte Carlo uncertainty analysis or integration, the general objective of these procedures is to establish specifics about the uncertainty of an output characteristic of such an engineering system, given uncertainty about its input characteristics. These sampling procedures are applied in a context in which establishing such specifics cannot be performed through other means. Variance-reduction techniques are designed to lessen the variability among estimators to estimate statistics of those output uncertainties. Importance-sampling techniques, on the other hand, are designed to reduce the number of samples needed to estimate a particular statistic—e.g., a tail probability. The combination of these approaches can reduce the computational burden considerably for a particular estimator and statistic. Importance sampling—geared and designed as it is toward improving a particular estimator—suffers, unfortunately, from the unintended consequence of reducing the performance of other estimators in terms of their variance. The objective of this paper is to offer an alternative sampling procedure where this variance does not grow unacceptably large for a suite of estimators. Moreover, it is anticipated that, with additional knowledge of how an engineering output characteristic responds to its input characteristics, tuning parameters of the input’s sampling procedure can be set to improve the output characteristic’s estimation. This work proves the effectiveness of the suggested alternative approach. Such positive outcome will lead to a decrease of the computational burden of performing stochastic optimization of integrated energy systems (e.g., components dispatch, and portfolio composition). In particular, capturing the contribution to the overall system cost of rare and unlikely events and patterns of the electricity demand and production will become less computationally expensive. This is due to the fact that the approach demonstrated here will allow the sampling of those rare occurrences more frequently without misrepresenting their probabilistic impacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Design for Remanufacturing

The objective of this project was to develop relationships between published scholarship, industry experience, and remanufacturing design rules and identify a clear path for integrating remanufacturing design rules into CAD tools and design practices. To accomplish this, remanufacturing knowledge was compiled, and then the relationships between this knowledge and a prioritized set of product design guidelines was developed. Next, a process to create rules out of guidelines was developed by first defining life extension as a primary function, and remanufacturing as effective tasks to control the failure modes that would restrict the product life. The reliability centered maintenance (RCM) process was used to identify proactive tasks and default actions to mitigate the effects of failure modes. These tasks were developed into expert system rules. The impact of design on remanufacturing was then validated through implementing a prioritized set of design rules for a Heavy Duty Off-Road (HDOR) techno-economic case study. Finally, detailed steps on how to define, develop, and integrate these rules into CAD were created.

42 ENGINEERING↗
DOE OSTI2020

Co-op at Sandia National Laboratories (July - December 2019, Final Report)

This co-op was performed at Sandia National Laboratories (SNL) within the Weapon Surety Engineering 11 Department (9435), which is a customer-focused organization that provides engineering and system analysis expertise to ensure a safe deterrent throughout the entire weapon lifecycle. Engineers in 9435 develop a deep knowledge in both component and system function to support rigorous evaluation and mitigation of potential failure modes. They operate across multiple engineering disciplines (mechanical, electrical, computer, materials and systems engineering) with opportunities to develop crossdisciplinary capability. The team supports a variety of stockpile systems and is part of the product teams during development, design and production, as well as advanced concept and exploratory efforts. 9435 engineers use their extensive component and system knowledge, as well as experimental data and modeling, to ensure products function as intended with assured safety. Members of the department learn the function of multiple components, how those components integrate within the system and apply surety principles and processes to ensure a safe, secure, reliable, and effective U.S. nuclear deterrent.

42 ENGINEERING↗
DOE OSTI2023

Visual Brick model authoring tool for building metadata standardization

In this study, the Brick ontology is a unified semantic metadata standard for building assets and their relationships, serving as a key enabler for effective interoperability and automation of building systems and analytics. However, creating a Brick model, in other words, standard semantic metadata based on the Brick ontology for a building dataset, can be a complex task. This paper presents two case studies of the creation of Brick models for real-world residential and commercial building datasets, highlighting the challenges during the Brick model creation process. Additionally, the paper introduces VizBrick, an interactive authoring tool for creating semantic building metadata. VizBrick facilitates the creation of Brick models by providing an intuitive visual interface and interactive capabilities, such as keyword search, automatic mapping suggestions, and recommendations. The use of VizBrick is shown to significantly reduce the time and effort required during the Brick model creation process.

42 ENGINEERING↗
DOE OSTI2018

Avoiding Fracture in a Conversion Battery Material through Reaction with Larger Ions

Conversion and alloying electrode materials offer high specific capacity for emerging sodium- and potassium-ion batteries, but the larger volume changes compared to reaction with lithium are thought to limit cyclability. The reaction mechanisms of many materials with Na + and K + are unknown, however, and this knowledge is key for engineering mechanically resilient materials. Here, in situ transmission electron microscopy is used to uncover the nanoscale transformations during the reaction of FeS 2 electrode materials with Li + , Na + , and K + . Surprisingly, despite larger volume changes during the conversion reaction with Na + and K + , the FeS 2 crystals only fracture during lithiation. Modeling of reaction-induced deformation shows that the shape of the two-phase reaction front influences stress evolution, and unique behavior during lithiation causes stress concentrations and fracture. The larger volume changes in Na- and K-ion battery materials may therefore be managed through understanding and control of reaction mechanisms, ultimately leading to better alkali-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Dynamics of disordered intermediates during the two-electron alkaline MnO 2 conversion reaction for grid-scale batteries

Battery technologies beyond Li-ion are likely needed for extensive integration of grid-scale storage. The rechargeable Zn-MnO 2 chemistry has the potential for high sustainability, high safety, and low cost, using Earth-abundant basis materials. In an alkaline electrolyte, the MnO 2 cathode can cycle reversibly if modified by including a Bi-containing additive, although the cycling mechanism remains mostly unknown. This work presents an account of the intermediate species involved in the electrochemical transformation from layered δ-MnO 2 to Mn(OH) 2 and back. During charge, a disordered intermediate with a structure resembling layered β-MnOOH exists stably for an extended period, corresponding to a regime known to have unexpected electrochemical activity of Bi. During discharge, β-MnOOH exists only briefly and is never the majority material, revealing that the cycling mechanism is asymmetric. In conclusion, these findings represent a significant advance in mechanistic knowledge and can enable engineering to develop the system for commercial use.

36 MATERIALS SCIENCE↗