sir@PacBell.COM (Sheldon Rothenberg) (06/09/90)
I am looking for pointers to systems in place or under development that address the domain of energy and resource conservation. I know this domain is large. It could cover efficiencies in drilling ( e.g. greater wellhead production), transportation (e.g. shipping or pipe lines), use in industry (e.g. cogeneration, operating efficiencies?), or usage in products which without one of these hypothetical systems, might consume greater resources, or housing or transportation for that matter. Since I have not heard much about such systems, i am casting a wide net. If you have any ideas or pointers, I'ld be happy to hear them. Thanks Shelley (415) 867-5708
leff@dept.csci.unt.edu (Dr. Laurence L. Leff) (06/11/90)
In article <2136@pbhyg.PacBell.COM> sir@PacBell.COM (Sheldon Rothenberg) writes: >I am looking for pointers to systems in place or under development >that address the domain of energy and resource conservation. I know >this domain is large. I think the following information, extracted from my next submittal to the International Journal for AI in Engineering newsletter section will prove helpful. I will also advise you to scan the engineering sections of the INSPEC Computers and Control Abstracts regularly. This has the most complete coverage of any abstracting service. However, it is a little slow, i.e., stuff published in 1988 may appear in 1990 issues. Also, some of the stuff is so obscure it will drive your Interlibrary Loan Librarian crazy-- i.e., there won't be a copy of it anywhere in the U.S. .LP An expert system does fault detection and management for power systems on planes. The system also provides for management of a degraded electrical power system. This work was done on the Boeing Aerospace autonomous power system (R. J. Spier, M.E. Liffring, Boeing Aerospace) [11]. Another system for aerospace power systems was developed for the space station. This system uses a simulation based on solar radiation, orbital parameters, initial launch data and time of theyear. Aslo, it takes intoa ccount crew activities for performing estimations. Then, it can do load management (S. Rahman, M. Bouzguenda, Virginia Polytechnic) [11]. .LP Another expert system does online monitoring, statusing and trend analysis of the Hubble Space Telescope electrical power system. It was built with the L*STAR expert system. It does multiorbit health history tracking; real-time warning of approaching limits and graphics that assist the operator in interpreting information (J.K.McDermott, J.R. Stroll, Martin Marietta Astronaut. Group, Denver, Colorado) [11]. STARR is a system designed for managing power on space-based power systems. It is modeled on the Autonomously Managed Power System (AMPS) breadboard at NASA's Marshall Space Flight Center. It takes information directly from the controllers on the AMPS breadboard (B. Walls, NASA Marshall Space Flight Center) [11]. .LP Yet another expert system diagnoses feeder systems for railways. It uses information from accident reports and helps define countermeasures against these accidents [30]. .LP There is an expert system that assists in choosing cogeneration options. This one takes as input electrical and thermal needs, fuel price and electric bases. It is derived from cogeneration energy systems for naval bases (G.C. Birur, Jet Propulsion Lab) [11]. .LP The walking beam reheating furnace at the Fifth Rolling Mill of Tienjing is controlled by AI techniques. Fuzzy rules are used. Examples of some of the rules, given in linguistic form, follow: .QP If one of the transmission bands has stopped for a given time, then reduce the fuel rate to a certain extent. .QP If both transmission bands are at the same stepping rate, and the temperature covariance of output slabs is big, then even the fuel rate of the soak zone. .LP The system is implemented in a microcomputer. It obtains data from a YEWPACK, 8-loop controller. The system has reduced the covariance of the slab temperature at the outlet, and has saved 5 percent of the fuel consumption and 0.295 per cent of the steel consumption (Jiang Jiong, Zhejiang University, China) [4]. .LP An expert system was developed to generate job specifications and bids for the retrofitting of energy management systems onto existing buildings. The system has a database of manufacturers' products. The system developed plans for lighting control, roof misting and automated building controls. The system took into account tax benefits and depreciation (R. R. Goforth, University of Arkansas, R. E. Tolander, Energy Techniques, Fayetteville, Arkansas) [8]. .LP REZES is a system to assist in the management of water reservoirs. The system incorporates and assists in the use of the following algorithmic codes: .IP a) RESER, an optimization system for sizing a multipurpose reservoir storage. .IP b) ILP, a linear programming system for planning hydropower production. .IP c) a chance-constrained system for planning reservoir operation. .IP d) RPORC, a reliability system for planning reservoir operation. .IP e) PROFEXY, a real-time system with a daily time step. .LP .LP An expert system simulates the current practice of log bucking and allocation in a three-mill wood-product manufacturing facility (C.M. Chang, F.L. Cristomo, Jr., Y. L. Chan, Louisiana Technical University) [9]. Another system for the lumber industry plans for rough-end milling. This involves use of crosscut and rip saws to remove defects and then matching and sizing panels. The system classifies the defects and determines tolerable limits for each board, depending on the grade specified. The determination of the cuts used is done based on a dynamic programming method. The system uses heuristic rules to determine the value of strips that can be glued together (C.L. Moodie, P. F. Kacha, Purdue University) [19]. .LP .LP .LP [4] \fIComputers in Industry\fR, Vol. 13, 1990 .LP [8] \fI1989 American Control Conference\fR .LP [9] \fIProceedings SPIE- International Society of Optical Engineers\fR, Vol. 1095, part 1, Applications of Artificial Intelligence .LP [11] \fIProceedings of the 23rd Intersociety Energy Conversion Engineering Conference\fR, Denver, Co, USA, .LP .LP [19] \fIArtificial Intelligence: Manufacturing Theory and Practice\fR, (S. T. Kumara, R. L. Kashyap, A. L. Soyster, eds.)