scholarly journals Minimizing Power Peaking Factor of BEAVRS-based Reactor Using Polar Bear Optimization Algorithms

2021 ◽  
Vol 927 (1) ◽  
pp. 012004
Author(s):  
Amila Amatullah ◽  
Alexander Agung ◽  
Agus Arif
Keyword(s):  
Cycle Length ◽  
Polar Bear ◽  
Operating Time ◽  
Complex Problem ◽  
Fuel Loading ◽  
Loading Pattern ◽  
Maximum Value ◽  
Fuel Assemblies ◽  
The One ◽  
Optimum Solution

Abstract Fuel loading pattern optimization is a complex problem because there are so many possibilities for combinatorial solutions, and it will take time to try it one by one. Therefore, the Polar Bear Optimization Algorithm was applied to find an optimum PWR loading pattern based on BEAVRS. The desired new fuel loading pattern is the one that has the minimum Power Peaking Factor (PPF) value without compromising the operating time. Operating time is proportional to the multiplication factor (k eff ). These parameters are usually contradictive with each other and will make it hard to find the optimum solution. The reactor was modelled with the Standard Reactor Analysis Code (SRAC) 2006. Fuel pins and fuel assemblies are modelled with the PIJ module for cell calculations. One-fourth symmetry was used with the CITATION X-Y module for core calculations. The optimization was done with 200 populations and 50 iterations. The PPF value for the selected solution should never exceed 2.0 in every burn-up step. Out of 28 solutions, the best optimal fuel loading pattern had a maximum value PPF of 1.458 and a k eff of 0.916 at day 760 of calculated time (corresponding to a cycle length of 479 days). Therefore, the maximum PPF value was 27.1% lower than the safety factor, and the same operating time as the standard loading pattern has been achieved.

scholarly journals Fuel Loading Pattern Optimization with Constraint on Fuel Assembly Inventory Using Quantum-Inspired Evolutionary Algorithm

2018 ◽  
Vol 42 ◽  
pp. 01007 ◽  
Author(s):  
M. Rizki Oktavian ◽  
Alexander Agung ◽  
Andang Widi Harto
Keyword(s):  
Fuel Assembly ◽  
Evolutionary Algorithm ◽  
Cycle Length ◽  
Reactor Core ◽  
Combinatorial Problem ◽  
Weight Factor ◽  
Fuel Loading ◽  
Loading Pattern ◽  
Fitness Value ◽  
Fuel Assemblies

Nuclear fuel management was done by optimizing fuel loading pattern in a reactor core. Practically, performing fuel loading pattern optimization was difficult because of its combinatorial problem complexity which needed to be solved. Therefore, Quantum-inspired Evolutionary Algorithm (QEA) which could solve the combinatorial problem faster than conventional method was used. The main purpose of this research was to obtain an optimum fuel loading pattern of KSNP-1000 reactor core without altering fuel assembly inventories. KSNP-1000 core was modeled in SRAC code package using PIJ module for fuel pins and fuel assemblies’ lattices and CITATION module for fuel assemblies’ pattern in a quarter core symmetry. Optimization problem adaptation using QEA was made by presenting 52 fuel assemblies in Q-bit individuals with the length of 8 Q-bits. Q-bits were converted to corresponding bit values and then given weight which would be used as consideration to optimize the pattern. The optimization program was coupled with the SRAC neutronic code to obtain the values of effective multiplication factor (keff) and power peaking factor (PPF). The optimization was calculated based on fitness value which was a function of keff and PPF values with the particular weight factor. Using a rotation gate angle of Δθ=0.02π and a weight factor of w=0,041, fuel loading pattern optimization was done on 360 days burnup level. The optimization resulted in keff and PPF value of 1.11233 and 1.944 respectively. By calculating keff value on various burnup levels for the chosen core loading pattern, reactor cycle length obtained was 659 days with PPF at BOC was 2.19. Compared to the standard KSNP-1000 core which had 560 days of cycle length, the optimized core configuration increased 17.67% in cycle length.

scholarly journals Application of Evolutionary Simulated Annealing Method to Design a Small 200 MWt Reactor Core

2021 ◽  
Vol 10 (4) ◽  
pp. 16-23
Author(s):  
Tran Viet Phu ◽  
Tran Hoai Nam ◽  
Hoang Van Khanh
Keyword(s):  
Simulated Annealing ◽  
Power Plant ◽  
Nuclear Power ◽  
Cycle Length ◽  
Reactor Core ◽  
Loading Pattern ◽  
The Core ◽  
Fuel Assemblies ◽  
Full Power ◽  
Annealing Method

This paper presents the application of an evolutionary simulated annealing (ESA) method to design a small 200 MWt reactor core. The core design is based on a reference ACPR50 reactor deployed in a floating nuclear power plant. The core consists of 37 typical 17x17 PWR fuel assemblies with three different U-235 enrichments of 4.45, 3.40 and 2.35 wt%. Core loading pattern (LP) has been optimized for obtaining the cycle length of 900 effective full power days, while minimizing the average U-235 enrichment and the radial power peaking factor. The optimization process was performed by coupling the ESA method with the COREBN module of the SRAC2006 system code.

PWR Fuel Management Optimization Using a New Integer Coded Genetic Algorithm

2009 ◽  
Author(s):  
Ahmad Zolfaghari ◽  
Hamid Minuchehr ◽  
Ali Noroozy ◽  
Peymaan Makarachi
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Reactor Core ◽  
Complex Problem ◽  
Huge Number ◽  
Pressurized Water ◽  
Fuel Assemblies ◽  
Water Reactors ◽  
Management Optimization ◽  
Optimum Solution

The objective of this paper is to develop a new genetic algorithm (GA) for designing the loading pattern (LP) for pressurized water reactors (PWR). Because of huge number of possible combinations for the fuel assemblies (FA’s) loading in a core, finding the optimum solution is truly a complex problem. In common genetic algorithm the mutation and crossover techniques are used to optimize an objective function but in this paper a new modified crossover along a unique technique is presented. In this study flattening of power inside a reactor core is chosen as an objective function. To obtain optimal FA arrangement, a core reload package code, MAKGA, is developed. This code is applicable for all types of PWR core having different geometries and designs with an unlimited number of FA types. The result is well improved in comparison with pattern proposed by designer.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

scholarly journals Electret Filters—From the Influence of Discharging Methods to Optimization Potential

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 65
Author(s):  
Maximilian Kerner ◽  
Kilian Schmidt ◽  
Stefan Schumacher ◽  
Christof Asbach ◽  
Sergiy Antonyuk
Keyword(s):  
Fine Particles ◽  
Operating Time ◽  
Filtration Efficiency ◽  
Long Term Stability ◽  
Aerosol Filtration ◽  
Charge Decay ◽  
The One ◽  
Testing Standards ◽  
Discharge Efficiency

Electret filters are electrostatically charged nonwovens which are commonly used in aerosol filtration to remove fine particles from gases. It is known that the charge and thus also the filtration efficiency can degrade over time. Thus, many testing standards require to remove the charge by treatment with liquid isopropanol (IPA) or IPA-saturated air. However, the parameters influencing this discharge have not been completely clarified yet. The aim of this work was, on the one hand, to experimentally investigate the influence of the IPA treatment on different electret filters and, on the other hand, to show the optimization potential of electret filters with respect to efficiency and long-term stability by numerical simulations. The experiments revealed that the air permeability is a central influencing parameter. Small pores lead to a reduced discharge efficiency using liquid IPA, while both treatment methods are suitable for larger pores. The simulations showed that a homogeneous charge distribution within the filter depth is advantageous for the initial performance. In contrast, charge penetrating deeper in the filter medium delays the charge decay and thus increases the operating time, with the trade-off of a lower initial performance.

Advanced First Core Design for the Westinghouse AP1000

2009 ◽  
Author(s):  
Robert J. Fetterman
Keyword(s):  
Fuel Cycle ◽  
The United States ◽  
Pressurized Water ◽  
Loading Pattern ◽  
The Core ◽  
Low Leakage ◽  
Fuel Assemblies ◽  
Cycle Loading ◽  
Water Reactors ◽  
Under Construction

As the nuclear renaissance is now upon us and new plants are either under construction or being ordered, a considerable amount of attention has also turned to the design of the first fuel cycle. Requirements for core designs originate in the Utilities Requirements Document (URD) for the United States and the European Utilities Requirements (EUR) for Europe. First core designs created during the development of these documents were based on core design technology dating back to the 1970’s, where the first cycle core loading pattern placed the highest enrichment fuel on the core periphery and two other lower enrichments in the core interior. While this sort of core design provided acceptable performance, it underutilized the higher enriched fuel assemblies and tended to make transition to the first reload cycle challenging, especially considering that reload core designs are now almost entirely of the Low Leakage Loading Pattern (LLLP) design. The demands placed on today’s existing fleet of pressurized water reactors for improved fuel performance and economy are also desired for the upcoming Generation III+ fleet of plants. As a result of these demands, Westinghouse has developed an Advanced First Core (AFCPP) design for the initial cycle loading pattern. This loading pattern design simulates the reactivity distribution of an 18 month low leakage reload cycle design by placing the higher enriched assemblies in the core interior which results in improved uranium utilization for those fuel assemblies carried through the first and second reload cycles. Another feature of the advanced first core design is radial zoning of the high enriched assemblies, which allows these assemblies to be located in the core interior while still maintaining margin to peaking factor limits throughout the cycle. Finally, the advanced first core loading pattern also employs a variety of burnable absorber designs and lengths to yield radial and axial power distributions very similar to those found in typical low leakage reload cycle designs. This paper will describe each of these key features and demonstrate the operating margins of the AFC design and the ability of the AFC design to allow easy transition into 18 month low leakage reload cycles. The fuel economics of the AFC design will also be compared to those of a more traditional first core loading pattern.

Roma and Constantinopolis in Late-Antique Art From 312 to 365

1947 ◽  
Vol 37 (1-2) ◽  
pp. 135-144 ◽  
Author(s):  
J. M. C. Toynbee
Keyword(s):  
Religious Belief ◽  
Great Majority ◽  
Complex Problem ◽  
The Other ◽  
Late Antique ◽  
Public Monuments ◽  
The One ◽  
Independent Existence ◽  
Res Publica

Little more than a decade after Constantine's conversion to Christianity the ancient gods and goddesses of the Graeco-Roman pantheon ceased to appear upon the official coinage and public monuments of the Empire. The personifications—Victoria, Virtus, Pax, Libertas, Securitas, etc., and the ‘geographical’ figures of Res Publica, Roma, Tellus, cities, countries, and tribes—remained. Yet some of these had, up to that very time, received, like the Olympians, their shrines and altars and other honours associated with pagan cultus; and we ask ourselves how it was that a Christian State, while rejecting the one, could retain and ‘baptize’ the other. The answer to this question, which involves the whole complex problem of the nature of pagan religious belief under the later Empire, can only be tentatively suggested here. The pantheon had eventually to go because its denizens had possessed, for the great majority of pagans, a real, objective, and independent existence.

Towards Optimal In-Core Fuel Management of Thorium-Plutonium-Fuelled PWR Cores

2013 ◽  
Author(s):  
Nurjuanis Z. Zainuddin ◽  
Benjamin A. Lindley ◽  
Geoffrey T. Parks
Keyword(s):  
Nuclear Waste ◽  
Cycle Length ◽  
Feasibility Studies ◽  
Fuel Management ◽  
Loading Pattern ◽  
Burnable Poison ◽  
The Core ◽  
Mox Fuel ◽  
Operational Characteristics

Plutonium is a significant proliferation concern as well as a major contributor to the long-term toxicity of nuclear waste. Partial incineration in PWRs with uranium-MOX fuel is often considered to mitigate these concerns. Thorium-MOX is an alternative fuel with superior material properties and higher plutonium destruction rates, as shown in multiple feasibility studies. However, the core performance and operational characteristics (e.g. discharge burn-up, feasibility of controlling the core) are ultimately dependent on the core loading pattern (LP) and burnable poison (BP) design. In this paper, the LP for Th-Pu fuel of various compositions is optimized for (1) discharge burn-up, (2) radial form factor (RFF), (3) cycle length, (4) moderator temperature coefficient (MTC), and (5) reactivity swing over cycle. Maximizing the cycle length makes the discharge burn-up and reactivity swing worse due to placement of once- and twice-burnt fuel near the core periphery. It also makes the MTC less negative. The harder neutron spectrum of Th-Pu fuel compared to conventional U fuel favours the use of distributed integral burnable poisons to control the reactivity swing over the cycle. This leads to a significant amount of dissimilarity between LPs with relatively similar performance measures, and between optimal LPs for different Pu loadings in the fuel. The RFF can vary throughout the cycle but a careful placement of the assemblies can mitigate this. The cycle reactivity swing is controlled using enriched soluble boron, which makes the MTC worse, and this constrains feasibility for high Pu loading in the fuel.

scholarly journals Method for a cloud based remaining-service-life-prediction for vehicle-gearboxes based on big-data-analysis and machine learning

2020 ◽  
Vol 84 (4) ◽  
pp. 305-314
Author(s):  
Daniel Vietze ◽  
Michael Hein ◽  
Karsten Stahl
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Service Life ◽  
Operating Time ◽  
The Other ◽  
Learning Approaches ◽  
State Of Health ◽  
Remaining Service Life ◽  
Other Hand ◽  
The One

AbstractMost vehicle-gearboxes operating today are designed for a limited service-life. On the one hand, this creates significant potential for decreasing cost and mass as well as reduction of the carbon-footprint. On the other hand, this causes a rising risk of failure with increasing operating time of the machine. Especially if a failure can result in a high economic loss, this fact creates a conflict of goals. On the one hand, the machine should only be maintained or replaced when necessary and, on the other hand, the probability of a failure increases with longer operating times. Therefore, a method is desirable, making it possible to predict the remaining service-life and state of health with as little effort as possible.Centerpiece of gearboxes are the gears. A failure of these components usually causes the whole gearbox to fail. The fatigue life analysis deals with the dimensioning of gears according to the expected loads and the required service-life. Unfortunately, there is very little possibility to validate the technical design during operation, today. Hence, the goal of this paper is to present a method, enabling the prediction of the remaining-service-life and state-of-health of gears during operation. Within this method big-data and machine-learning approaches are used. The method is designed in a way, enabling an easy transfer to other machine elements and kinds of machinery.

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