| LDR | | 01970nmm uu200445 4500 |
| 001 | | 000000333748 |
| 005 | | 20240805174451 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438050600 |
| 035 | |
▼a (MiAaPQ)AAI10824718 |
| 035 | |
▼a (MiAaPQ)princeton:12642 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 082 | 0 |
▼a 621 |
| 100 | 1 |
▼a Davies, Gregory. |
| 245 | 10 |
▼a Characterization of Batteries Using Ultrasound: Applications for Battery Management and Structural Determination. |
| 260 | |
▼a [S.l.] :
▼b Princeton University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 206 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Daniel Steingart. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Princeton University, 2018. |
| 506 | |
▼a This item is not available from ProQuest Dissertations & Theses. |
| 520 | |
▼a Ultrasound has been an invaluable and widely used tool in the medical and non-destructive testing (NDT) sectors. Much of its success is attributable to its low-cost, compact size, the speed and ease of its application, and the useful qualitative |
| 520 | |
▼a More specifically, in Chapter 2 ultrasonic measurements were combined with a supervised machine-learning technique, which was used to predict the SOC and SOH of lithium-ion cells that had been operated for several hundred cycles. Excellent resul |
| 590 | |
▼a School code: 0181. |
| 650 | 4 |
▼a Mechanical engineering. |
| 650 | 4 |
▼a Energy. |
| 650 | 4 |
▼a Acoustics. |
| 690 | |
▼a 0548 |
| 690 | |
▼a 0791 |
| 690 | |
▼a 0986 |
| 710 | 20 |
▼a Princeton University.
▼b Mechanical and Aerospace Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0181 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998697
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자 |