Jane Huang

US Patent:

8333070, Dec 18, 2012

Filed:

May 4, 2011

Appl. No.:

13/100492

Inventors:

Henry C. Huang - Cambridge MA, US
Jane Huang - Cambridge MA, US

International Classification:

F03B 13/18
F03B 17/02

US Classification:

60497, 60495, 60507

Abstract:

Provided is an energy storage system configured to accumulate energy for subsequent discharge. One embodiment includes an indirect energy storage assembly configured to accept energy input from a direct storage assembly. The indirect energy storage assembly includes a converter for lifting a mass, a speed reducer coupled to the converter for increasing torque provided, and a mass coupled to the speed reducer for generating potential energy when raised. In one embodiment, the direct energy storage assembly produces energy based on descent of a mass, the descent controlled by operation of a speed increaser coupled to a generator. In one example, the speed increaser provides an input:output ratio of at least 1:100. The speed increaser can be configured based on parameters of the generator (e. g. , speed and torque).

US Patent:

20130085971, Apr 4, 2013

Filed:

Sep 20, 2012

Appl. No.:

13/623196

Inventors:

SIEMENS AKTIENGESELLSCHAFT - Munich, DE
Jane Cleland Huang - Flossmoor IL, US
Marek Gibiec - Chicago IL, US
Yonghee Shin - Chicago IL, US
Yubin Li - Carpentersville IL, US

Assignee:

SIEMENS AKTIENGESELLSCHAFT - Munich

International Classification:

G06F 15/18

US Classification:

706 12

Abstract:

A method for performing automatic trace retrieval includes receiving a first and second model for a system or service (S). The first model includes a first plurality of model artifacts at least partially represented by a first semantic style and the second model includes a second plurality of artifacts at least partially represented by a second semantic style. Training data including one or more correspondences between artifacts of the first plurality of model artifacts and artifacts of the second plurality of artifacts is collected. A semantic transformation table is generated for converting between the first and second semantic styles using the collected training data (S). The generated semantic transformation table is used in tracing associations between artifacts of the first plurality of artifacts and artifacts of the second plurality of artifacts (S).