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At least 937 records · Page 52

SULI Oral Presentation

Furthering our understanding of the prevalence and severity of issues that customers face when charging their electric vehicles (EVs) is crucial in order to improve the charging experience across the United States. This project utilizes web-scraping, machine leaning (ML), and natural language processing (NLP) techniques to analyze and categorize user-generated reviews. Selenium was used to build a data collection tool that can scrape vast amounts of user review data from the PlugShare website. Sentiment analysis was employed on this dataset in order to filter out negative reviews for further analysis. NLP techniques such as tokenization and word embedding were then used to convert user-written comments into a numerical format that a ML model can interpret. Multiple ML approaches are currently being explored in order to identify and categorize the charging issues being talked about in each review. Ultimately, the results from the ML model will be visualized and explained in a report on customer pain points to be delivered to the ChargeX Consortium, therefore revealing specific areas for improvement in the customer charging experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Flash radiotherapy accelerator

Methods, devices and systems for ultra-high dose radiotherapy are disclosed. The described techniques rely in-part on active switching control of a photoconductive switch during the time the accelerator is accelerating charged particles to produce the output radiation at the desired dose rates. One flash radiotherapy system includes an induction accelerator, and a controllable switch coupled to the induction accelerator. The switch is operable to produce a plurality of voltage pulses to drive the induction accelerator. The radiotherapy system also includes a radiation measurement device to measure output radiation produced by the radiotherapy system and provide feedback to the controllable switch. The controllable switch is operable to, based on the received feedback, modify an amplitude, shape, spacing, number or width of the voltage pulses that are supplied to the particle accelerator to deliver the desired output radiation.

Sampayan, Stephen E.↗

Multi-stage falling particle receivers

The present disclosure is directed to multi-stage falling particle receivers and methods of falling particle heating. As the particles fall through the receiver, the particles are periodically collected and released by flow retarding devices. The periodic catch-and-release of the particles falling through the receiver reduces particle flow dispersion, increases particle opacity and solar absorption, and reduces erosion and damage to surfaces caused by direct particle impingement.

Ho, Clifford K.↗