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At least 1,135 records · Page 63

Are We Preparing the Next Generation? K-12 Teacher Knowledge and Engagement in Teaching Core STEM Practices

Several of the recent reform efforts in K-12 STEM education (e.g. Next Generation Science Standards [NGSS and Common Core State Standards-Mathematics [CCSS-M]) have included significant emphasis on the practices of STEM. We argue that K-12 teachers’ ability to effectively engage their students in these core STEM practices is fundamental to the success of potential and current engineering students and their subsequent careers as engineers. Practices such as identifying problems, modeling using mathematics, and arguing from evidence are fundamental processes in engineering. Helping students develop their capacity to engage in these practices early in their education will increase the likelihood of the students applying the practices and developing skills aligned with the work of engineers. We contend that engaging in the practices associated with engineering may increase K-12 student interest and the successful pursuit of engineering as a career because they will find relevance in what is being taught and gain knowledge of the applications of STEM content which will help them develop talents aligned with the work of engineers.

99 GENERAL AND MISCELLANEOUS↗

Physics guided machine learning using simplified theories

Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences. In this Letter, we introduce a modular physics guided machine learning framework to improve the accuracy of such data-driven predictive engines. The chief idea in our approach is to augment the knowledge of the simplified theories with the underlying learning process. To emphasize their physical importance, our architecture consists of adding certain features at intermediate layers rather than in the input layer. To demonstrate our approach, we select a canonical airfoil aerodynamic problem with the enhancement of the potential flow theory. We include the features obtained by a panel method that can be computed efficiently for an unseen configuration in our training procedure. By addressing the generalizability concerns, our results suggest that the proposed feature enhancement approach can be effectively used in many scientific machine learning applications, especially for the systems where we can use a theoretical, empirical, or simplified model to guide the learning module.

42 ENGINEERING↗

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

The Bird project: Using Big Data tools to support Search Analytics

The Bird project explored the use of big data analytics tool to improve the findability of information within the Sandia internal network. We were able to perform query classification utilizing the supervised learning algorithms in the Apache Spark library. By relying on the distributed processing capabilities provided by the Apache Hadoop framework, we successfully processed the large query log files needed to train the models in this effort. The capabilities developed in this project are being used to enhance the effectiveness of the enterprise search engine.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Building engineering expert systems in CLIPS

This paper is intended for CLIPS developers with a working knowledge of expert systems and the CLIPS syntax. It discusses Rete pattern matching and rule-fact interaction, explains several development and debug techniques, and gives advice on compiling CLIPS and knowledge bases. The techniques apply to CLIPS versions 4.2 and 4.3, especially in the PC/DOS environment. Two examples developed by the author are analyzed and compared.

Porter, Ken↗

Action Pathways for Transforming Cities

Transformation is required for cities to fulfil their leadership potential on climate change. Five action pathways can guide them: integrate mitigation and adaptation; coordinate risk reduction and climate adaptation; cogenerate risk information; focus on disadvantaged populations; and improve governance and knowledge networks.

Civil engineering↗

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

42 ENGINEERING↗

Multi-functional genome-wide CRISPR system for high throughput genotype–phenotype mapping

Abstract Genome-scale engineering is an indispensable tool to understand genome functions due to our limited knowledge of cellular networks. Unfortunately, most existing methods for genome-wide genotype–phenotype mapping are limited to a single mode of genomic alteration, i.e. overexpression, repression, or deletion. Here we report a multi-functional genome-wide CRISPR (MAGIC) system to precisely control the expression level of defined genes to desired levels throughout the whole genome. By combining the tri-functional CRISPR system and array-synthesized oligo pools, MAGIC is used to create, to the best of our knowledge, one of the most comprehensive and diversified genomic libraries in yeast ever reported. The power of MAGIC is demonstrated by the identification of previously uncharacterized genetic determinants of complex phenotypes, particularly those having synergistic interactions when perturbed to different expression levels. MAGIC represents a powerful synthetic biology tool to investigate fundamental biological questions as well as engineer complex phenotypes for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

Progress on the J-2X Upper Stage Engine for the Ares I Crew Launch Vehicle and the Ares V Cargo Launch Vehicle

NASA's Vision for Exploration requires a safe, reliable, affordable upper stage engine to power the Ares I Crew Launch Vehicle (CLV) and the Ares V Cargo Launch Vehicle. The J-2X engine is being developed for that purpose, epitomizing NASA's philosophy of employing legacy knowledge, heritage hardware, and commonality to carry the next generation of explorers into low-Earth orbit and out into the solar system This presentation gives top-level details on accomplishments to date and discusses forward work necessary to bring the J-2X engine to the launch pad.

Byrd, Thomas D.↗

Understanding, inhibiting, and engineering membrane transporters with high-throughput mutational screens

Promiscuous membrane transporters play vital roles across domains of life, mediating the uptake and efflux of structurally and chemically diverse substrates. Although many transporter structures have been solved, the fundamental rules of polyspecific transport remain inscrutable. In recent years, high-throughput genetic screens have solidified as powerful tools for comprehensive, unbiased measurements of variant function and hypothesis generation, but have had infrequent application and limited impact in the transporter field. In this primer, we describe the principles of high-throughput screening methods available for studying polyspecific transporters and comment on the necessity and potential of high-throughput methods for deciphering these transporters in particular. We present several screening approaches which could provide a fundamental understanding of the molecular basis of function and promiscuity in transporters. Here, we further posit how this knowledge can be leveraged to design inhibitors that combat multidrug resistance and engineer transporters as needed tools for synthetic biology and biotechnology applications.

EPIs↗

NASA/DoD Aerospace Knowledge Diffusion Research Project. Paper 30: The electronic transfer of information and aerospace knowledge diffusion

Increasing reliance on and investment in information technology and electronic networking systems presupposes that computing and information technology will play a major role in the diffusion of aerospace knowledge. Little is known, however, about actual information technology needs, uses, and problems within the aerospace knowledge diffusion process. The authors state that the potential contributions of information technology to increased productivity and competitiveness will be diminished unless empirically derived knowledge regarding the information-seeking behavior of the members of the social system - those who are producing, transferring, and using scientific and technical information - is incorporated into a new technology policy framework. Research into the use of information technology and electronic networks by U.S. aerospace engineers and scientists, collected as part of a research project designed to study aerospace knowledge diffusion, is presented in support of this assertion.

Pinelli, Thomas E.↗

The electronic transfer of information and aerospace knowledge diffusion

Increasing reliance on and investment in information technology and electronic networking systems presupposes that computing and information technology will play a motor role in the diffusion of aerospace knowledge. Little is known, however, about actual information technology needs, uses, and problems within the aerospace knowledge diffusion process. The authors state that the potential contributions of information technology to increased productivity and competitiveness will be diminished unless empirically derived knowledge regarding the information-seeking behavior of the members of the social system - those who are producing, transferring, and using scientific and technical information - is incorporated into a new technology policy framework. Research into the use of information technology and electronic networks by U.S. aerospace engineers and scientists, collected as part of a research project designed to study aerospace knowledge diffusion, is presented in support of this assertion.

Pinelli, Thomas E.↗

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

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

59 BASIC BIOLOGICAL SCIENCES↗

Materials Engineering for High Performance and Durability Proton Exchange Membrane Water Electrolyzers

Proton exchange membrane water electrolyzers (PEMWEs) are expected to play a crucial role in the global green energy transition during the 21st century. They provide a versatile and sustainable solution for generating hydrogen with very high purity in combination with renewable energies, such as solar and wind. Despite their promise, PEMWEs face several critical problems, including high costs, performance limitations, and durability challenges, particularly at low iridium (Ir) loading on the anode. Advancing next-generation PEMWEs requires extensive work on materials engineering of all cell components, including the catalyst layer (CL), membrane, porous transport layer (PTL), bipolar plate (BPP), and gasket. This task must be performed with the complementary contribution of different modeling and characterization techniques. This review presents a critical perspective from academia, research centers, and industry, mapping main developments, remaining gaps, and strategic pathways to advance PEMWE technology. A focus is devoted to key aspects, such as operation at low Ir loading, membrane durability, multiscale transport layers, porous and non-porous flow fields, multiphysics modeling, and multipurpose characterization techniques, which are thoroughly discussed. By unifying these topics, this review provides readers with the essential knowledge to grasp current developments and tackle tomorrow's challenges in PEMWE engineering.

36 MATERIALS SCIENCE↗

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 1: The value of scientific and technical information (STI), its relationship to Research and Development (R/D), and its use by US aerospace engineers and scientists

This paper is based on the premise that scientific and technical information (STI), its use by aerospace engineers and scientists, and the aerospace research and development (R&D) process are related. We intend to support this premise with data gathered from numerous studies concerned with STI, the relationship of STI to the performance and management of R&D activities, and the information use and seeking behavior of engineers in general and aerospace engineers and scientists in particular. We intend to develop and present a synthesized appreciation of how aerospace R&D managers can improve the efficacy of the R&D process by understanding the role and value of STI in this process.

Pinelli, Thomas E.↗