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Kim, Doyoung

Publications and source records attributed to Kim, Doyoung.

4 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Metathesis, molecular redistribution of alkanes, and the chemical upgrading of low-density polyethylene

Here, a new strategy for polyethylene (PE) deconstruction via alkane metathesis is presented, in which WO x /SiO 2 catalyzes the olefin metathesis reaction step. Zeolite 4 A is an essential component to protect the metathesis active sites from poisoning by in-situ-generated oxygenates in a batch reaction system. High conversion of 1-hexadecene (96%) and n-hexadecane (92%)—surrogates of long-chain molecules—demonstrates the high reactivity of WO x /SiO 2 metathesis catalyst for olefin and alkane metathesis reactions, respectively, at moderate reaction temperatures of 300 °C for 2–3 h. Pretreatment temperature and length of the short n-alkane-chain solvent significantly affect the metathesis reactivity and selectivity. Results for the deconstruction of low-density PE (LDPE) in n-decane demonstrate a remarkable potential for PE upgrading with the advantages of short reaction times (3 h), the low mass ratio of solvent to LDPE, and the production of solid products with narrow molecular weight distributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Small target detection for search and rescue operations using distributed deep learning and synthetic data generation

It is important to find the target as soon as possible for search and rescue operations. Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support search and rescue. Automatic object detection is important because a person cannot monitor multiple surveillance screens simultaneously for 24 hours. Also, the object is often too small to be recognized by the human eye on the surveillance screen. This study used UAVs around the Port of Houston and fixed surveillance cameras to build an automatic target detection system that supports the US Coast Guard (USCG) to help find targets (e.g., person overboard). We combined image segmentation, enhancement, and convolution neural networks to reduce detection time to detect small targets. We compared the performance between the auto-detection system and the human eye. Our system detected the target within 8 seconds, but the human eye detected the target within 25 seconds. Our systems also used synthetic data generation and data augmentation techniques to improve target detection accuracy. This solution may help the search and rescue operations of the first responders in a timely manner.

Chow, Edward↗