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Utilization of plant operating experience in new plant designs: A consultant's viewpoint
Annals oJ Nuclear Energy, Vol. 4 pp. 303-309. Pergamon Press, 1977. Printed in Great Britain.
UTILIZATION OF PLANT OPERATING EXPERIENCE IN NEW PLANT DESIGNS: A CONSULTANT'S VIEWPOINT Michael A. LINTNER* and Roger W. GRIEBE Energy Incorporated, P.O. Box 736, Idaho Falls, Idaho 83401, U.S.A.
Abstract - One specific area which should be considered in the transfer of nuclear technology to countries beginning development of a nuclear industry is the utilization and transfer of existing operating plant experience. No other single area can assist in developing a level of useful knowledge more rapidly than the systematic comparison of existing new plant designs with older plants and their associated performance data. With the advent of the Rasmussen Study (WASH-1400, 1975), a methodology now exists that can provide the systematic review of the plant design and quantify its probability of being an optimum system. Generally, the most important criteria for definition of the optimum system would be initial capital cost, projected maintenance costs, and plant availability. The fault tree analysis methodology used on the Rasmussen study allows system availability to be placed on a firm numerical footing. The area of each plant system contributing most to its unavailability is readily identifiable. Once identified, various methods for system improvement can be analyzed to determine which will provide the best results at lowest cost. The actual costs of the improvements vs the resultant savings from improved plant availability can be calculated, thus optimizing the solution (Lintner, 1976). Simple financial considerations of initial capital costs, escalation, and overall nuclear plans provide the final loop in the iteration to establish the optimum plant design. Since the most unfamiliar and most difficult part of the solution is the fault-tree construction and utilization, most attention will be paid to its discussion. 1. I N T R O D U C T I O N Within the n e x t 10 yr, the United States will have a p p r o x i m a t e l y 200 operating nuclear p o w e r e d central station electric generating units on line. Operating plants very similar in design to those in planning stages are n o w providing a wealth of practical operating experience in key areas affecting plant availability. Certain industry groups are n o w establishing programs by which operating plant experience can be collected, collated, and generally distributed to interested segments of the industry. Proper utilization o f these data for existing plants has the obvious advantage of circumventing inefficient design and plant o p e r a t i o n practices. Plants presently have data available to t h e m which can be of immense value in increasing plant p e r f o r m a n c e while simultaneously decreasing plant operating costs for the utility. Operating data should have a p r o f o u n d influence on plant availability. It has long been recognized by the reactor v e n d o r that c o n t i n u e d penetration o f the m a r k e t place can best be assured by providing a quality p r o d u c t which is continually developed and i m p r o v e d as m o r e experience becomes available. A prime example o f this p h i l o s o p h y in the nuclear industry has been in the areas of nuclear fuel. In that instance, *
Mr. Lintner is presently a private consultant residing at 1420 E, 16th St., Idaho Falls, Idaho 83401, U.S.A.
303
304
Utilization of plant operating experience in new plant designs
a continuing process of fuel design and development has been augmented not only by test reactor research but also by operating plant experience. Present fuel concepts developed by vendors have had remarkable success in performance in various reactor systems both in Europe and in the United States. Many previous problems with light water reactor fuel, such as leaking, densification, and other problems, related not only to plant operation but also to plant safety, have been resolved with contemporary fuels that have a significantly increased degree of reliability. This enhancement of nuclear plant performance has been accomplished not only by the primary reactor suppliers, but also by independent workers who have taken the wealth of data available in open literature and through utility contacts applied it to their new fuel design, thereby taking advantage of all previous experience available to date. Simultaneously, with the nuclear vendor continuing the enhancement of his product, the architect engineer and the construction engineer have been increasing their capabilities by integrating actual experience in the design, layout and construction of plants. The architect engineer, construction engineer, and consulting engineer gain through experience of their staff in resolving operating problems of present day plants. The main question to be addressed concerns the optimum manner in which to transmit experience in operating data back to the existing plants. Plant availability will be defined as that portion of a given time span in which the plant is scheduled to be operating at a specified plant capacity. Losses in plant availability are typically the unscheduled shutdown or failure of a plant component before scheduled maintenance. Data to assess plant availability can be acquired through a variety of sources which all basically represent arrangements of data collection and collation from one source, the operating utility. The Electric Power Research Institute, the Nuclear Regulatory Commission, the Atomic Industrial Forum, the Edison Electric Institute, and others all provide some type of program by which operating data can be utilized and fed back to the industry for use. The interface between these programs can be very complicated and can range in effectiveness. In this paper, feedback effects resulting from interrelationships among the concepts of the accessing, filtering and utilizing data are discussed with the objective of optimizing plant availability. 2. GENERALIZED THEORY The key to a successful availability study is careful use of the Fault Tree Methodology, with the top events appropriately defined, in order to determine those areas of impacting systems which most influence plant availability. Once this determination is made, various methods can be explored to circumvent the exposed problem areas. The objective is to reduce forced downtime by reducing equipment failures and associated repair times. The steps required are as follows and are shown schematically in Fig. 1. (1) Define system failure. For normally operating systems this would be any failure which would render the system, and hence the plant, in a failed state. For standby systems* these would be failures for * The failure definition for standby systems used here will differ from that of WASH-1400. In WASH-1400, the emphasis was on unavailability and failure during mission time. While this is important, an unavailable safety system might allow a minor mishap to grow into a major accident, day to day operation is perhaps more concerned with accidental startings which will influence plant availability. Hence, three areas are to be considered when defining failure in standby systems which will influence plant availability: (1) failures for which repairs exceed maximum allowable downtimes; (2) accidental starting, and (3) unavailability and failure during mission.
Michael A. Linmer and Roger W. Griebe
305
which there is a maximum allowable downtime defined by the technical specifications or failures interrupting plant operation. I/ IE II II DATA BASE li II H II p L A i ~ NT [COMPONENT II
II
[ GENERAL
SPECIFIC I - ~ DATA ] l
FAILURE DATA
i SYSTEM NOTI CONTRIBUTING I TO PLANT I UNAVAILA BILITYJ
OUANT,F*, f
I FAULT TREE I J I FOR I ~ - -,UNAVAILABILITYI I CONTR;BUTIONI "~.~
li
Jl II ii
--B.
COST OF CHANGE
INCORPORATE OPTIMUM SOLUTION INTO SYSTEM
SYSTEM DOMINATING PLANT UNAVAILABILITY ISOLATE DOMINANT AREA OF SYSTEM
I INPROPOSED CORPORATE II~ [DEFINE WAY OF ] REDUCING I ~
CHANGE INTO ~ SYSTEM ~- -FAULT TREE ] [UNAVAILABILITYI
-
Fig. 1. Tasks required on system level to optimize the availability and cost of a nuclear plant.
(2) Construct fault tree of system. A detailed fault tree is constructed for each system starting with the definition of system failure from Task 1. The level of construction includes operator actions, test and maintenance acts, and is carried to the individual components level. (3) Quantify fault trees for unavailability contributions. Each fault tree is quantified using the component failure data as well as test and maintenance information in order to determine the numerical system contribution to plant unavailability. (4) Systems dominating plant unavailability. Once the fault trees are quantified each system is classified according to whether or not it contributes to plant unavailability. (5) Isolate dominant area of system. The unavailability of a system is usually dominated by 10% or less of its minimal cut sets. By using the results of the fault tree analysis, this dominant collection can easily be isolated. (6) Define way of reducing system unavailability. Once the dominating area of system unavailability is isolated various methods may be devised to circumvent the problem. These can include redesign, balancing of the spare parts inventory with expected failures, improved test and maintenance scheduling, rewriting operator procedures, or any combination of the above. (7) Incorporate change into fault trees. The changes are incorporated into the system fault tree for the purpose of determining the impact o f the change on the system unavailability.
306
Utilization of plant operating experience in new plant designs
(8) Quantify fault tree for unavailability contributions. The fault tree with each proposed change is quantified to determine the resultant impact to plant unavailability. (9) Determine cost of change. With the determination made in Task 8 the cost of change implementation versus the savings from improved plant availability can be calculated. (10) Incorporate optimum solution into system. The cost versus savings calculation from Task 9 for each change now gives a firm basis for incorporating the optimum solution into the system. (11) Plant specific data. This collection of data is an ongoing effort and is used to upgrade the general data base for improved analysis. In addition, failure data that are observed to fall outside the error bounds given for the general data may indicate potential common mode failure problems which have gone undetected. 3. COST OPTIMIZATION SCHEME 3.1. System level The cost optimization for each system is an iterative exercise on the impact of potential system changes once the area dominating system unavailability has been isolated. The steps involved are as follows: (1) incorporate potential change into system fault tree; (2) quantify fault tree to determine impact on plant availability; (3) determine cost of proposed change. (4) determine savings in increased plant availability, and (5) return to step 1 with next potential change. The potential changes will incorporate one or more of the following areas depending upon how system unavailability is dominated: (1) redesign; (2) spare parts inventory balancing with expected component failure frequencies; (3) improved test and maintenance scheduling; (4)improved operator procedures; (5) changes in technical specifications. As the impact of each potential change is calculated it is tabulated. Once the tabulation is complete (one or more changes depending on the type of area dominating system unavailability), the change reflecting the largest net savings is the one chosen. 3.2. Plant level optimization Spare parts inventory balancing. While spare parts inventory balancing impacts system availability, it is best done on a plant-wide basis. In the course of the fault tree analysis a tabulation is made of the numbers and type of each component. From this the component hours and/or demands can be compiled so the failure frequency of each component type can be calculated. The failure frequences provide the ratio of spare parts kept in inventory. The actual level of inventory is that level which minimizes inventory cost and maximizes savings from improved plant availability and is shown as the intersection of the two curves in Fig. 2. The curves are calculated by first making a determination of the optimum level of inventory which will maximize availability (relative to downtime due to waiting for spare parts delivery). The level of inventory is then dropped and by utilizing the failure frequency and average back order time for each component type the new savings in plant availability is computed. Maintenance crew balancing. The component failure frequencies computed in the course of the inventory balancing optimization are also the maintenance demand frequencies. The makeup of the
Michael A. Linmer and Roger W. Griebe
307
INVENTORY
AVAILABILITY
COST
SAVINGS
INVENTORY COST
Fig. 2. Availability vs inventory for some level of maintenance.
MAINTENANCE
AVAILABILITY
COST
SAVINGS
MAINTENANCE COST
Fig. 3. Availability vs maintenance for some level of inventory.
T Z <~
÷ >-
I
Fig. 4. Availability, inventory and maintenance optimization.
308
Utilization of plant operating experience in new plant designs
t.)
Z
_q J
Fig. 5. Availability, inventory and maintenance cost optimization. maintenance crews (maintenance functions) is the ratio of spare parts in inventory. The optimum crew size can be found by a simulation similar to that used for inventory balancing. The solution would be the intersection of the two curves in Fig. 3. Spare parts inventory and maintenance crew balancing. It should be noted that the spare parts inventory balancing previously mentioned was with respect to a particular maintenance crew size and the maintenance crew balancing was done in a similar fashion. To find the optimum level for both of these items they must be balanced together. The form of the solution is shown in Figs. 4 and 5. Ongoing effort. The major effort after the completion of the analysis is the continued gathering of plant specific data. The reason for this is threefold. First, the changes incorporated as a result of the analysis will probably impact the nature of the data being collected. Secondly, by comparing the plant specific data to the general data base any gross deviation in the data collected will likely indicate undetected common mode failures. Thirdly, the spare parts inventory can be continually upgraded to reflect actual conditions in the plant and further increase savings in availability. 4. SUMMARY The use of available plant operating experience can be transferred to existing plants designs in an orderly and systematic application of fault tree methodology. While the methodology presented in this paper covers all aspects of plant operation including maintenance and spare parrs inventories, initial use of the scheme on plant designs still in final blueprint stages can result in uncovering the obvious availability problems. In addition, changes in the system can be evaluated from a theoretical availability viewpoint using existing data bases. Most important, however, would be the recognition that a technique to improve plant availability does exist which can be implemented very early in the plant design, and a group
Michael A. Lintner and Roger W. Griebe
309
established, as part of the plant design and operating team, to factor plant availability into the design and construction before actual operation begins. Once plant operation begins, the final loop can be closed, and actual plant operating data used for the actual availability optimization task. Spare part inventories and maintenance schemes can be initially specified and defined well in advance of plant operation, and then improved as actual experience is gained. 5. REFERENCES WAHS-1400 (NUREG-75/O14), Reactor Safety Study, An Assessment of Accident Risks in U.S. Commerical Nuclear Power Plants, October, 1975, United States Regulatory Commission. Linmer M.A., A Discussion on Optimizing the Availability and Cost of Operating Nuclear Generating Plants, 1976, Energy Incorporated Report.
UTILIZATION OF PLANT OPERATING EXPERIENCE IN NEW PLANT DESIGNS: A CONSULTANT'S VIEWPOINT Michael A. LINTNER* and Roger W. GRIEBE Energy Incorporated, P.O. Box 736, Idaho Falls, Idaho 83401, U.S.A.
Abstract - One specific area which should be considered in the transfer of nuclear technology to countries beginning development of a nuclear industry is the utilization and transfer of existing operating plant experience. No other single area can assist in developing a level of useful knowledge more rapidly than the systematic comparison of existing new plant designs with older plants and their associated performance data. With the advent of the Rasmussen Study (WASH-1400, 1975), a methodology now exists that can provide the systematic review of the plant design and quantify its probability of being an optimum system. Generally, the most important criteria for definition of the optimum system would be initial capital cost, projected maintenance costs, and plant availability. The fault tree analysis methodology used on the Rasmussen study allows system availability to be placed on a firm numerical footing. The area of each plant system contributing most to its unavailability is readily identifiable. Once identified, various methods for system improvement can be analyzed to determine which will provide the best results at lowest cost. The actual costs of the improvements vs the resultant savings from improved plant availability can be calculated, thus optimizing the solution (Lintner, 1976). Simple financial considerations of initial capital costs, escalation, and overall nuclear plans provide the final loop in the iteration to establish the optimum plant design. Since the most unfamiliar and most difficult part of the solution is the fault-tree construction and utilization, most attention will be paid to its discussion. 1. I N T R O D U C T I O N Within the n e x t 10 yr, the United States will have a p p r o x i m a t e l y 200 operating nuclear p o w e r e d central station electric generating units on line. Operating plants very similar in design to those in planning stages are n o w providing a wealth of practical operating experience in key areas affecting plant availability. Certain industry groups are n o w establishing programs by which operating plant experience can be collected, collated, and generally distributed to interested segments of the industry. Proper utilization o f these data for existing plants has the obvious advantage of circumventing inefficient design and plant o p e r a t i o n practices. Plants presently have data available to t h e m which can be of immense value in increasing plant p e r f o r m a n c e while simultaneously decreasing plant operating costs for the utility. Operating data should have a p r o f o u n d influence on plant availability. It has long been recognized by the reactor v e n d o r that c o n t i n u e d penetration o f the m a r k e t place can best be assured by providing a quality p r o d u c t which is continually developed and i m p r o v e d as m o r e experience becomes available. A prime example o f this p h i l o s o p h y in the nuclear industry has been in the areas of nuclear fuel. In that instance, *
Mr. Lintner is presently a private consultant residing at 1420 E, 16th St., Idaho Falls, Idaho 83401, U.S.A.
303
304
Utilization of plant operating experience in new plant designs
a continuing process of fuel design and development has been augmented not only by test reactor research but also by operating plant experience. Present fuel concepts developed by vendors have had remarkable success in performance in various reactor systems both in Europe and in the United States. Many previous problems with light water reactor fuel, such as leaking, densification, and other problems, related not only to plant operation but also to plant safety, have been resolved with contemporary fuels that have a significantly increased degree of reliability. This enhancement of nuclear plant performance has been accomplished not only by the primary reactor suppliers, but also by independent workers who have taken the wealth of data available in open literature and through utility contacts applied it to their new fuel design, thereby taking advantage of all previous experience available to date. Simultaneously, with the nuclear vendor continuing the enhancement of his product, the architect engineer and the construction engineer have been increasing their capabilities by integrating actual experience in the design, layout and construction of plants. The architect engineer, construction engineer, and consulting engineer gain through experience of their staff in resolving operating problems of present day plants. The main question to be addressed concerns the optimum manner in which to transmit experience in operating data back to the existing plants. Plant availability will be defined as that portion of a given time span in which the plant is scheduled to be operating at a specified plant capacity. Losses in plant availability are typically the unscheduled shutdown or failure of a plant component before scheduled maintenance. Data to assess plant availability can be acquired through a variety of sources which all basically represent arrangements of data collection and collation from one source, the operating utility. The Electric Power Research Institute, the Nuclear Regulatory Commission, the Atomic Industrial Forum, the Edison Electric Institute, and others all provide some type of program by which operating data can be utilized and fed back to the industry for use. The interface between these programs can be very complicated and can range in effectiveness. In this paper, feedback effects resulting from interrelationships among the concepts of the accessing, filtering and utilizing data are discussed with the objective of optimizing plant availability. 2. GENERALIZED THEORY The key to a successful availability study is careful use of the Fault Tree Methodology, with the top events appropriately defined, in order to determine those areas of impacting systems which most influence plant availability. Once this determination is made, various methods can be explored to circumvent the exposed problem areas. The objective is to reduce forced downtime by reducing equipment failures and associated repair times. The steps required are as follows and are shown schematically in Fig. 1. (1) Define system failure. For normally operating systems this would be any failure which would render the system, and hence the plant, in a failed state. For standby systems* these would be failures for * The failure definition for standby systems used here will differ from that of WASH-1400. In WASH-1400, the emphasis was on unavailability and failure during mission time. While this is important, an unavailable safety system might allow a minor mishap to grow into a major accident, day to day operation is perhaps more concerned with accidental startings which will influence plant availability. Hence, three areas are to be considered when defining failure in standby systems which will influence plant availability: (1) failures for which repairs exceed maximum allowable downtimes; (2) accidental starting, and (3) unavailability and failure during mission.
Michael A. Linmer and Roger W. Griebe
305
which there is a maximum allowable downtime defined by the technical specifications or failures interrupting plant operation. I/ IE II II DATA BASE li II H II p L A i ~ NT [COMPONENT II
II
[ GENERAL
SPECIFIC I - ~ DATA ] l
FAILURE DATA
i SYSTEM NOTI CONTRIBUTING I TO PLANT I UNAVAILA BILITYJ
OUANT,F*, f
I FAULT TREE I J I FOR I ~ - -,UNAVAILABILITYI I CONTR;BUTIONI "~.~
li
Jl II ii
--B.
COST OF CHANGE
INCORPORATE OPTIMUM SOLUTION INTO SYSTEM
SYSTEM DOMINATING PLANT UNAVAILABILITY ISOLATE DOMINANT AREA OF SYSTEM
I INPROPOSED CORPORATE II~ [DEFINE WAY OF ] REDUCING I ~
CHANGE INTO ~ SYSTEM ~- -FAULT TREE ] [UNAVAILABILITYI
-
Fig. 1. Tasks required on system level to optimize the availability and cost of a nuclear plant.
(2) Construct fault tree of system. A detailed fault tree is constructed for each system starting with the definition of system failure from Task 1. The level of construction includes operator actions, test and maintenance acts, and is carried to the individual components level. (3) Quantify fault trees for unavailability contributions. Each fault tree is quantified using the component failure data as well as test and maintenance information in order to determine the numerical system contribution to plant unavailability. (4) Systems dominating plant unavailability. Once the fault trees are quantified each system is classified according to whether or not it contributes to plant unavailability. (5) Isolate dominant area of system. The unavailability of a system is usually dominated by 10% or less of its minimal cut sets. By using the results of the fault tree analysis, this dominant collection can easily be isolated. (6) Define way of reducing system unavailability. Once the dominating area of system unavailability is isolated various methods may be devised to circumvent the problem. These can include redesign, balancing of the spare parts inventory with expected failures, improved test and maintenance scheduling, rewriting operator procedures, or any combination of the above. (7) Incorporate change into fault trees. The changes are incorporated into the system fault tree for the purpose of determining the impact o f the change on the system unavailability.
306
Utilization of plant operating experience in new plant designs
(8) Quantify fault tree for unavailability contributions. The fault tree with each proposed change is quantified to determine the resultant impact to plant unavailability. (9) Determine cost of change. With the determination made in Task 8 the cost of change implementation versus the savings from improved plant availability can be calculated. (10) Incorporate optimum solution into system. The cost versus savings calculation from Task 9 for each change now gives a firm basis for incorporating the optimum solution into the system. (11) Plant specific data. This collection of data is an ongoing effort and is used to upgrade the general data base for improved analysis. In addition, failure data that are observed to fall outside the error bounds given for the general data may indicate potential common mode failure problems which have gone undetected. 3. COST OPTIMIZATION SCHEME 3.1. System level The cost optimization for each system is an iterative exercise on the impact of potential system changes once the area dominating system unavailability has been isolated. The steps involved are as follows: (1) incorporate potential change into system fault tree; (2) quantify fault tree to determine impact on plant availability; (3) determine cost of proposed change. (4) determine savings in increased plant availability, and (5) return to step 1 with next potential change. The potential changes will incorporate one or more of the following areas depending upon how system unavailability is dominated: (1) redesign; (2) spare parts inventory balancing with expected component failure frequencies; (3) improved test and maintenance scheduling; (4)improved operator procedures; (5) changes in technical specifications. As the impact of each potential change is calculated it is tabulated. Once the tabulation is complete (one or more changes depending on the type of area dominating system unavailability), the change reflecting the largest net savings is the one chosen. 3.2. Plant level optimization Spare parts inventory balancing. While spare parts inventory balancing impacts system availability, it is best done on a plant-wide basis. In the course of the fault tree analysis a tabulation is made of the numbers and type of each component. From this the component hours and/or demands can be compiled so the failure frequency of each component type can be calculated. The failure frequences provide the ratio of spare parts kept in inventory. The actual level of inventory is that level which minimizes inventory cost and maximizes savings from improved plant availability and is shown as the intersection of the two curves in Fig. 2. The curves are calculated by first making a determination of the optimum level of inventory which will maximize availability (relative to downtime due to waiting for spare parts delivery). The level of inventory is then dropped and by utilizing the failure frequency and average back order time for each component type the new savings in plant availability is computed. Maintenance crew balancing. The component failure frequencies computed in the course of the inventory balancing optimization are also the maintenance demand frequencies. The makeup of the
Michael A. Linmer and Roger W. Griebe
307
INVENTORY
AVAILABILITY
COST
SAVINGS
INVENTORY COST
Fig. 2. Availability vs inventory for some level of maintenance.
MAINTENANCE
AVAILABILITY
COST
SAVINGS
MAINTENANCE COST
Fig. 3. Availability vs maintenance for some level of inventory.
T Z <~
÷ >-
I
Fig. 4. Availability, inventory and maintenance optimization.
308
Utilization of plant operating experience in new plant designs
t.)
Z
_q J
Fig. 5. Availability, inventory and maintenance cost optimization. maintenance crews (maintenance functions) is the ratio of spare parts in inventory. The optimum crew size can be found by a simulation similar to that used for inventory balancing. The solution would be the intersection of the two curves in Fig. 3. Spare parts inventory and maintenance crew balancing. It should be noted that the spare parts inventory balancing previously mentioned was with respect to a particular maintenance crew size and the maintenance crew balancing was done in a similar fashion. To find the optimum level for both of these items they must be balanced together. The form of the solution is shown in Figs. 4 and 5. Ongoing effort. The major effort after the completion of the analysis is the continued gathering of plant specific data. The reason for this is threefold. First, the changes incorporated as a result of the analysis will probably impact the nature of the data being collected. Secondly, by comparing the plant specific data to the general data base any gross deviation in the data collected will likely indicate undetected common mode failures. Thirdly, the spare parts inventory can be continually upgraded to reflect actual conditions in the plant and further increase savings in availability. 4. SUMMARY The use of available plant operating experience can be transferred to existing plants designs in an orderly and systematic application of fault tree methodology. While the methodology presented in this paper covers all aspects of plant operation including maintenance and spare parrs inventories, initial use of the scheme on plant designs still in final blueprint stages can result in uncovering the obvious availability problems. In addition, changes in the system can be evaluated from a theoretical availability viewpoint using existing data bases. Most important, however, would be the recognition that a technique to improve plant availability does exist which can be implemented very early in the plant design, and a group
Michael A. Lintner and Roger W. Griebe
309
established, as part of the plant design and operating team, to factor plant availability into the design and construction before actual operation begins. Once plant operation begins, the final loop can be closed, and actual plant operating data used for the actual availability optimization task. Spare part inventories and maintenance schemes can be initially specified and defined well in advance of plant operation, and then improved as actual experience is gained. 5. REFERENCES WAHS-1400 (NUREG-75/O14), Reactor Safety Study, An Assessment of Accident Risks in U.S. Commerical Nuclear Power Plants, October, 1975, United States Regulatory Commission. Linmer M.A., A Discussion on Optimizing the Availability and Cost of Operating Nuclear Generating Plants, 1976, Energy Incorporated Report.