Feature Extraction and Porosity Assessment on Thick Stainless Steel 316 Samples with Embedded Slots.
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SEARCH · Engineering Papers
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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Experiments show that when two HE materials placed adjacently, a fast-propagating detonation in one of the HE regions can sometimes initiate a detonation in the other HE. Direct numerical simulations support this phenomenon. Let A and B stand for the two HE materials. In a typical case, the driving detonation in HE A has a propagation speed faster than the CJ velocity in HE B, and the induced detonation in HE B is necessarily concave.
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Final project briefing from PingThings for FOA 1861
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A major objective of the project was to train and evaluate the effectiveness of multiple event and anomaly detection, identification and classification deep temporal learning models for processing of real-time phasor measurement unit (PMU) data streams. A vast dataset, consisting of two years of phasor measurements from all three U.S. Interconnections, was curated and released by the Department of Energy (DOE) through Pacific Northwest National Laboratory (PNNL). The dataset also included an event log that provided event times and types (e.g. generator trips, line trips, planned service events, transformer operations, etc.). Our analysis of this dataset addressed six (6) of the eleven (11) research priorities identified in Funding Opportunity Announcement (FOA) DE-FOA-0001861 “Big Data Analysis of Synchrophasor Data” (FOA 1861). Rather than being limited to pre-determined specific algorithms, this project relied on the uniquely structured, highly performant underlying time series database capabilities of the PredictiveGrid platform to assess the vast dataset utilizing a wide variety of algorithms.
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Nuclear data is ubiquitous across nuclear applications. Improved nuclear data means more accurate simulations. Past focus on k eff caused compensating error and areas of unvalidated nuclear data. Sensitivity can be used to optimize experiments to focus on specific areas. Sensitivity capabilities must be expanded and improved to design multivariate experiments focused on nuclear data needs.
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This report documents the results and conclusions of a recent project to understand the technoeconomics of utility-scale, particle-based concentrating solar power (CSP) facilities leveraging unique operational strategies. This project included two primary objectives. The first project objective was to build confidence in the modeling approaches applied to falling particle receivers (FPRs) including the effect s of wind. The second project objective was to create the necessary modeling capability to adequately predict and maximize the annual performance of utility-scale, particle-based CSP plants under anticipated conditions with and without active heliostat control. Results of an extensive model validation study provided the strongest evidence to date for the modeling strategies typically applied to FPRs, albeit at smaller receiver scales. This modeling strategy was then applied in a parametric study of candidate utility-scale FPRs, including both free-falling and multistage FPR concepts, to develop reduced order models for predicting the receiver thermal efficiency under anticipated environmental and operating conditions. Multistage FPRs were found to significantly improve receiver performance at utility-scales. These reduced order models were then leveraged in a sophisticated technoeconomic analysis to optimize utility-scale , particle-based CSP plants considering the potential of active heliostat control. In summary, active heliostat control did not show significant performance benefits to future utility-scale CSP systems though some benefit may still be realized in FPR designs with wide acceptance angles and/or with lower concentration ratios. Using the latest FPR technologies available, the levelized-cost of electricity was quantified for particle-based CSP facilities with nominal powers ranging from 5 MW e up to 100 MW e with many viable designs having costs < 0.06 $/kWh and local minimums occurring between ~25–35 MW e .
Permanent magnets are the functional component of electric motors and generators found in numerous renewable energy applications. To improve energy conversion in such applications, we require fundamentally new magnets that generate higher magnetic flux per volume while retaining the properties conferred by rare-earth elements incorporated into current technologies. We hypothesize that by engendering a covalent interaction between two elements, we can access a new regime of magnetic materials where the two components of a magnetic moment—spin and orbital angular momentum—come from two separate atoms to form a complete magnetic moment. Our previous research utilized high-pressure conditions to discover two new candidate materials ideal for assessing this hypothesis. The first material, FeBi 2 , enables the study of an unprecedented solid state metal-metal bonding interaction. The second, MnBi 2 represents the second member of the promising Mn–Bi family known for its magnetic properties. Importantly, MnBi 2 is isostructural to FeBi 2 . Together these chemically simple but magnetically rich materials provide an elegant platform for elucidating fundamental design principals of magnetic anisotropy while inspiring the synthesis of new magnetic materials. More generally, solid-state chemistry remains a synthetic black box. To fully harness the potential of such new materials, it is vital to create a window into both the structure and the properties of our high-pressure materials. One missing area of importance to energy science is high-pressure magnetometry. To this end, we assessed the magnetic structure of these materials through two objectives: (1) we performed magnetometry measurements at high-pressures, including performing high-pressure X-ray Magnetic Circular Dichroism (XMCD) experiments on these materials that are only synthesized at high-pressure and cannot be recovered to ambient conditions and (2) we targeted the recovery of these materials using dynamic compression approaches, starting with laser shock techniques. Future directions include expanding our focus to ternary phase space, employing high-throughput computational approaches to direct our search for magnetic materials across the Periodic Table. This award was originated at Northwestern, and reopened as a new grant at MIT. This is the close out for Northwestern.
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