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At least 487 records · Page 27

All sources NASA NTRS DOE OSTI

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↗

NASA NTRSDate not supplied

Airspace Research and Development Portfolio Assessment of Urban Air Mobility using Knowledge Graph Data Science

National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of Urban Air Mobility (UAM) operations. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. To safely support UAM operations at scale in the National Airspace System (NAS), NASA’s Air Traffic Management-Exploration (ATM-X) project has been conducting research that evolves the UAM air traffic management system towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution to accommodate the increasing tempo of UAM operations over time is managed through the UAM airspace research roadmap, which is a system engineering approach to the R&D of complex system-of-systems, where system’s interdependencies make it nearly impossible to define requirements for individual elements of the system in isolation. These interdependencies form a knowledge graph (node-link network) with a highly complex structure far beyond the human user’s ability to extract insights for project management’s research portfolio assessment. This study applies advanced data analytics in knowledge graph to the UAM knowledge graph to facilitate the portfolio assessment.

ATM↗

NASA NTRSDate not supplied

Airspace Research and Development Portfolio Assessment of Urban Air Mobility using Knowledge Graph Data Science

ATM↗

NASA NTRS1993

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 18: A comparison of the technical communication practices of aerospace engineers and scientists in India and the United States

As part of Phase 4 of the NASA/DoD Aerospace Knowledge Diffusion Research Project, two studies were conducted that investigated the technical communications practices of India and U.S. aerospace engineers and scientists. Both studies have the same seven objectives: first, to solicit the opinions of aerospace engineers and scientists regarding the importance of technical communications to their profession; second, to determine the use and production of technical communications by aerospace engineers and scientists; third, to seek their views about the appropriate content of an undergraduate course in technical communications; fourth, to determine aerospace engineers' and scientists' use of libraries, technical information centers, and on-line data bases; fifth, to determine the use and importance of computer and information technology to them; sixth, to determine their use of electronic networks; and seventh, to determine their use of foreign and domestically produced technical reports. A self-administered questionnaire was distributed to aerospace engineers and scientists at the Indian Institute of Science and the NASA Langley Research Center. The completion rates for the India and U.S. surveys were 48 and 53 percent, respectively. Responses of the India and U.S. participants to selected questions are presented in this report.

Pinelli, Thomas E.↗

NASA NTRS1993

Expanding the KATE toolbox

KATE (Knowledge-based Autonomous Test Engineer) is a model-based software system developed in the Artificial Intelligence Laboratory at the Kennedy Space Center for monitoring, fault detection, and control of launch vehicles and ground support systems. In order to bring KATE to the level of performance, functionality, and integratability needed for firing room applications, efforts are underway to implement KATE in the C++ programming language using an X-windows interface. Two programs which were designed and added to the collection of tools which comprise the KATE toolbox are described. The first tool, called the schematic viewer, gives the KATE user the capability to view digitized schematic drawings in the KATE environment. The second tool, called the model editor, gives the KATE model builder a tool for creating and editing knowledge base files. Design and implementation issues having to do with these two tools are discussed. It will be useful to anyone maintaining or extending either the schematic viewer or the model editor.

Thomas, Stan J.↗

NASA NTRS2021

Future Model-Based Systems Engineering Vision and Strategy Bridge for NASA

A vision for the future of model-based systems engineering (MBSE) at NASA in 2029 and a strategy bridge towards that future are presented. Strategic thinking and leading change concepts were used to analyze reports and presentations on global trends and visionary thinking about the future of systems and digital engineering. The context, strategic time horizon, stakeholders, strategic challenges, strategic advantages, driving forces, and opportunities were considered. The analysis resulted in a future vision of MBSE that shows what NASA systems engineers and digital machines will do to perform rapid, extraordinary, and unprecedented missions. The NASA systems engineer, in this future vision, works with a global project team in a virtual and collaborative environment, engineers the system, and uses digital approaches as the routine and default way of working. The digital machines provide data-driven and automated mission designs; have a backbone of program and project management, systems engineering, and product life-cycle management; and are a knowledge-sharing infrastructure. The NASA systems engineer and the systems engineering team are envisioned to use digital machines to plan and perform rapid exploration missions, develop a digital twin that lasts across the life cycle, and develop enduring and adaptable systems. NASA has an engineering enterprise and a life-cycle management framework that endure, adapt, and respond. A strategy bridge based on the Baldrige Criteria for Performance Excellence Framework and lessons learned from a recent MBSE initiative illuminates a way forward from today to this desired future. The bridge lays out a strategy for leaders and recommends investments of today for immediate benefits and for benefits in 2029.

model-based systems engineering, digital engineeri↗

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↗

NASA NTRS2004

F-OWL: An Inference Engine for Semantic Web

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining frame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and compare it with other description logic based approaches. We also describe TAGA, a trading agent environment that we have used as a test bed for F-OWL and to explore how multiagent systems can use semantic web concepts and technology.

Zou, Youyong↗

NASA NTRS2008

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Fitts, M. A.↗

NASA NTRS2001

Satellite Contamination and Materials Outgassing Knowledge base

Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

Minor, Jody L.↗

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↗

NASA NTRS2008

Enabling Innovation and Collaboration Across Geography and Culture: A Case Study of NASA's Systems Engineering Community of Practice

In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited personnel from sharing experiences and ideas. Mission failures and new directions for the agency demanded better collaborative tools. In addition, with the push to send astronauts back to the moon and to Mars, NASA recognized that systems engineering would have to improve across the agency. Of the ten field centers, seven had not built a spacecraft in over 30 years, and had lost systems engineering expertise. The Systems Engineering Community of Practice came together to capture the knowledge of its members using the suite of collaborative tools provided by the NASA Engineering Network (NEN.) The NEN provided a secure collaboration space for over 60 practitioners across the agency to assemble and review a NASA systems engineering handbook. Once the handbook was complete, they used the open community area to disseminate it. This case study explores both the technology and the social networking that made the community possible, describes technological approaches that facilitated rapid setup and low maintenance, provides best practices that other organizations could adopt, and discusses the vision for how this community will continue to collaborate across the field centers to benefit the agency as it continues exploring the solar system.

NEN↗

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↗