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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 19 records

Students’ conceptions and problem-solving ability on topic chemical thermodynamics

The enthalpy concept and its change were introduced to describe the forms of internal energy transfer in chemical reactions. Likewise, the concepts of exothermic and endothermic reactions introduced as a consequence of heat transfer form. In the heat measurement process at constant pressure, work is often ignored. The exothermic or endothermic reactions, usually only based on the increase or decrease of the reaction temperature, without associated with the internal energy. Depictions of enthalpy and its change assumed closely related to students’ problem-solving ability. Therefore, the study to describe pre-service chemistry teacher student’s conceptions and problem-solving ability on topic chemical thermodynamics has been done. This research was a case study of chemical education course in Provinsi Lampung. The subjects of this study were 42 students who attend the chemical thermodynamics course. Questions about exothermic and endothermic reactions, enthalpy and its change, as well as internal energy and its change were given in the form of an essay exam questions. Answers related to conception qualitatively categorized, while problem solving answers were scored and assessed. The results showed that, in general, students were having problems in enthalpy and describe the changes in the form of heat and work. The highest value of problem solving ability obtained 26.67 from the maximum value of 100. The lowest value was 0, and the average value was 14.73. These results show that the problem-solving ability of pre-service chemistry teacher students was low. The results provide insight to researchers, and educators to develop learning or lab work on this concept.

42 ENGINEERING↗

The long-solved problem of the best-fit straight line: application to isotopic mixing lines

Abstract. It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introduce the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods – ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) – have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general – and convenient – solution is always the least biased.

58 GEOSCIENCES↗

Rebecca Erikson – Solving Problems with Love for Science

Rebecca Erikson’s love for science began at a young age. Today, she’s a senior scientist at PNNL trying to solve problems that address national security concerns. Through one project, she developed a sleek, simple and inexpensive way to turn a cellphone into a high-powered, high-quality microscope that helps authorities determine if white powder that falls from an envelope is anthrax or something simple like baby powder. Listen as Rebecca describes her work in this Energy Department video.

3D PRINTER↗

Exploring Professor Motivations and Implementations of a Real-World Problem-Solving Project

Engineering education literature offers a variety of theoretical and conceptual frameworks for project-based learning. This study explores the implementation of real-world problem-solving projects in engineering education. The research team analyzed the motivations and methods behind professors' adoption of such projects through exploratory qualitative interviews with seven professor participants who integrated a nation-wide student competition into their courses. We analyzed the resulting data using a constructivist grounded theory approach to identify key themes of professor practices. Findings reveal that the real-world aspect of the projects and alignment with values and research interests were primary motivators for implementation. While implementation methods varied significantly based on context (i.e., university setting, course type), we found that these projects could be effectively integrated into various classroom settings. The findings support the recommendation for non-academic institutions to develop and manage competitions that can be integrated into classrooms and which offer a point of engagement that is available to professors from a wide range of disciplines.

42 ENGINEERING↗

Exploring Professor Motivations and Implementations of a Real-World Problem-Solving Project: A Case Study in Preparing Students for the Emerging Building Science Industry: Preprint

Engineering education literature offers a variety of theoretical and conceptual frameworks for project-based learning. This study explores the implementation of real-world problem-solving projects in engineering education. The research team analyzed the motivations and methods behind professors' adoption of such projects through exploratory qualitative interviews with seven professor participants who integrated a nation-wide student competition into their courses. We analyzed the resulting data using a constructivist grounded theory approach to identify key themes of professor practices. Findings reveal that the real-world aspect of the projects and alignment with values and research interests were primary motivators for implementation. While implementation methods varied significantly based on context (i.e., university setting, course type), we found that these projects could be effectively integrated into various classroom settings. The findings support the recommendation for non-academic institutions to develop and manage competitions that can be integrated into classrooms and which offer a point of engagement that is available to professors from a wide range of disciplines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗

Pilot-Scale CFP Commissioning: Creative Problem Solving and Lessons Learned

We have commissioned a pilot-scale, ex-situ catalytic fast pyrolysis (CFP) reactor system in the Thermal and Catalytic Process Development Unit (TCPDU) at the National Renewable Energy Laboratory. The FCC-style CFP system, including a riser and continuous regeneration, was added to the existing half-ton-per-day biomass fast pyrolysis unit and was designed to run a zeolite-type catalyst. The system is unique due to its scale and catalyst flow control scheme. As the design of this system was informed by early data from a bench-scale reactor, several technical scale-up challenges had to be overcome. Additionally, physical constraints and the complexities of biomass vapors required and inspired creative solutions. This talk will discuss the specific challenges we found and addressed, including an oxygen deficiency in the regenerator and plugging in the exit streams. We explored several options for increasing oxygen availability and selected a cyclone-catalyst return design on the exit line so we could increase air flow through the regenerator. We found that hot gas filtration is essential in any exit streams containing water vapor and trace amounts of catalyst; any combination of catalyst and condensate quickly makes mud that plugs equipment and severely limits run time. Duplicate filters are also required to extend run time. Most of the equipment and solutions were designed and installed by our team of engineers and technicians, working closely together in an iterative process to design, install, operate, then redesign. Collaborations with other national laboratories with computational fluid dynamics expertise helped inform designs and identify creative solutions to these scale-up challenges. Ultimately, data from the reactor system will be used to validate a comprehensive kinetic model of CFP that can be used to better design and inform new systems at various scales.

09 BIOMASS FUELS↗