RICHARD D MITCHELL
Architects in Greenville, SC
License number
Pennsylvania RA003993X
Category
Architects
Type
Registered Architect
Address
Address
2
Greenville, SC 29609
Pennsylvania
Pennsylvania
Personal information
See more information about RICHARD D MITCHELL at radaris.comName
Address
Phone
508 Pasadena Ave, Jenkintown, PA 19046
500 Hamilton Ave, Waynesboro, PA 17268
5030 Coach Hill Dr, Greenville, SC 29615
435 Cypress Ave, Murrells Inlt, SC 29576
434 Saint Charles Cir, Myrtle Beach, SC 29588
Professional information
Sr. Enterprise Systems / Solutions Architect | Develop &Amp; Drive New Technology | Pioneer In Product Design Solutions
Position:
Total Plant Optimization Principal Architect | Simulation System Integration Leader at GE Energy Engineering
Location:
Greenville, South Carolina Area
Industry:
Electrical/Electronic Manufacturing
Work:
GE Energy Engineering
- Greenville, SC since 2008
-
Total Plant Optimization Principal Architect | Simulation System Integration Leader
CAE USA
- Tampa, FL 1989 - 2008
-
Engineering Group Leader
Pratt and Whitney Aircraft
- West Palm Beach, FL 1986 - 1989
-
Control Systems Engineer
Education:
University of Florida 1999 - 2001
Master of Business Administration (MBA) University of South Florida 1984 - 1986
Bachelor of Science (BSEE), Electrical Engineering University of Miami 1979 - 1983
Bachelor of Science (BS), (major) Chemistry | (minor) Mathematics & Business Administration University of South Florida
Master of Computer Science (majority of coursework completed)
Master of Business Administration (MBA) University of South Florida 1984 - 1986
Bachelor of Science (BSEE), Electrical Engineering University of Miami 1979 - 1983
Bachelor of Science (BS), (major) Chemistry | (minor) Mathematics & Business Administration University of South Florida
Master of Computer Science (majority of coursework completed)
History Teacher At Southside Christian School
Position:
History Teacher at Southside Christian School
Location:
Greenville, South Carolina Area
Industry:
Education Management
Work:
Southside Christian School
-
History Teacher
Independent Entertainment Professional
Location:
Greenville, South Carolina Area
Industry:
Entertainment
Two-Way, Secure, Data Communication Within Critical Infrastructures
US Patent:
2013005, Feb 28, 2013
Filed:
Aug 24, 2011
Appl. No.:
13/216873
Inventors:
Robert Boring - Greenville SC, US
Richard Joseph Mitchell - Greenville SC, US
Richard Joseph Mitchell - Greenville SC, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
H04L 9/00
US Classification:
713150
Abstract:
Systems and methods for two-way, secure, data communication within critical infrastructures are usable to protect critical infrastructure information while allowing real-time monitoring and remote access. Such communication systems and methods can be used to protect critical data by, for example, providing a single point of access via unidirectional, serial, non-routable connections. Additionally, data flow may be controlled by a first server that is not accessible outside of the critical infrastructure.
Method And System To Predict Power Plant Performance
US Patent:
2012008, Apr 5, 2012
Filed:
Sep 30, 2010
Appl. No.:
12/895293
Inventors:
Rajesh Venkat Subbu - Clifton Park NY, US
Lincoln Mamoru Fujita - Roanoke VA, US
Weizhong Yan - Clifton Park NY, US
Noemie Dion Ouellet - Greenville SC, US
Richard J. Mitchell - Greenville SC, US
Piero Patrone Bonissone - Schenectady NY, US
Robert Frank Hoskin - Duluth GA, US
Lincoln Mamoru Fujita - Roanoke VA, US
Weizhong Yan - Clifton Park NY, US
Noemie Dion Ouellet - Greenville SC, US
Richard J. Mitchell - Greenville SC, US
Piero Patrone Bonissone - Schenectady NY, US
Robert Frank Hoskin - Duluth GA, US
Assignee:
General Electric Company - Schenectady NY
International Classification:
G06F 1/26, G06N 3/02, G06N 3/08
US Classification:
700291, 706 25, 706 21
Abstract:
The present disclosure relates to the use of hybrid predictive models to predict one or more of performance, availability, or degradation of a power plant or a component of the power plant. The hybrid predictive model comprises at least two model components, one based on a physics-based modeling approach and one based on an observational or data-based modeling approach. The hybrid predictive model may self-tune or self-correct as operational performance varies over time.