Shuffling Pattern Research Articles

Calculation of Isotope-Specific Fission Rates for Neutrino Source Calculation in PWR Fuel Diversion Safeguarding

The emission of antineutrinos from nuclear reactors offers a potential avenue for the international enforcement of reactor safeguards. A variety of frameworks have been proposed for detecting these particles, with the objective of verifying an agreed-upon composition of fuel in the operating reactor. More specifically, these frameworks should identify the diversion of a “significant quantity” of fissile material from an agreed upon core loading. For any quantitative analysis of these frameworks, isotope-specific fission rates of a nuclear reactor are required to calculate the reactor neutrino source. Unfortunately, the calculation of isotope-specific fission rates for a realistic core is nontrivial and can require significant simulation efforts. Therefore, this work uses industry-standard simulation tools (CASMO-4/SIMULATE-3) to provide isotope-specific fission rates for a set of 15 plutonium diversion scenarios for a mixed-oxide-loaded pressure water reactor. These diversion scenarios span a wide range of diverted fuel amounts, from 2.17 to 655.19 kg of fissile plutonium. The isotope-specific fission rates reported in this paper can be combined with a neutrino emission model for the direct calculation of the reactor neutrino source. This work can be considered a dedicated effort toward the calculation of realistic isotope-specific reaction rates for use in the development and analysis of safeguarding frameworks. As such, these isotope-specific fission rates are provided over three cycles with realistic fuel loading and shuffling patterns. In this way, this work can act as a standard neutrino source reference for the development and comparison of safeguarding frameworks.

Hypermobility in patients with epidermolysis bullosa—A retrospective observational study from a national referral center

AbstractBackgroundEpidermolysis bullosa (EB) is an inherited genodermatosis of variable severity characterised by skin and mucosal fragility commonly associated with altered gait patterns and hypermobility.ObjectivesTo define the altered gait pattern and identify possible causes in patients with EB.MethodsRetrospective review of the EB database to identify children with EB with at least one physiotherapy assessment between 2009 and 2022.ResultsForty‐eight children out of 59 referrals to physiotherapy with an altered gait pattern were identified (81.3%); 23 (48%) had recessive dystrophic EB (RDEB), 17 (36%) EB simplex, five (10%) Junctional EB (JEB) and three (6%) dominant dystrophic EB (DDEB). The patho‐mechanical altered gait patterns were characterised by altered load‐bearing surface in contact with the floor (63%), short shuffling pattern with high cadence and decreased single support (42%) and equinovarus (toe walking) (6%). Hypermobility (as defined by the Beighton score) was present in 67% of patients: 43% in RDEB, 88% in EBS, 100% in JEB and 67% in DDEB.ConclusionsIn this study, we provide the first accurate data for the causes of altered gait patterns in children with EB. Healthcare professionals should be aware of joint hypermobility and its effect on gait in this patient cohort.

XCovNet: An optimized xception convolutional neural network for classification of COVID-19 from point-of-care lung ultrasound images

Global livelihoods are impacted by the novel coronavirus (COVID-19) disease, which mostly affects the respiratory system and spreads via airborne transmission. The disease has spread to almost every nation and is still widespread worldwide. Early and reliable diagnosis is essential to prevent the development of this highly risky disease. The computer-aided diagnostic model facilitates medical practitioners in obtaining a quick and accurate diagnosis. To address these limitations, this study develops an optimized Xception convolutional neural network, called "XCovNet," for recognizing COVID-19 from point-of-care ultrasound (POCUS) images. This model employs a stack of modules, each of which has a slew of feature extractors that enable it to learn richer representations with fewer parameters. The model identifies the presence of COVID-19 by classifying POCUS images containing Coronavirus samples, viral pneumonia samples, and healthy ultrasound images. We compare and evaluate the proposed network with state-of-the-art (SOTA) deep learning models such as VGG, DenseNet, Inception-V3, ResNet, and Xception Networks. By using the XCovNet model, the previous study's problems are cautiously addressed and overhauled by achieving 99.76% accuracy, 99.89% specificity, 99.87% sensitivity, and 99.75% F1-score. To understand the underlying behavior of the proposed network, different tests are performed on different shuffle patterns. Thus, the proposed "XCovNet" can, in regions where test kits are limited, be used to help radiologists detect COVID-19 patients through ultrasound images in the current COVID-19 situation.

Ferroelectric HfO2 and the importance of strain

Ferroelectric oxides based on ${\mathrm{HfO}}_{2}$ show tremendous promise for the next generation of memory and logic devices. The ferroelectric polymorph is one of several that can be derived from the high symmetry cubic fluorite structure of ${\mathrm{HfO}}_{2}$. A single grain of ${\mathrm{HfO}}_{2}$ may consist of a coherent mixture of multiple orientational and translational variants of different polymorphs. Here, we use symmetry-adapted strain-order parameters to elucidate the relationship between the different ${\mathrm{HfO}}_{2}$ polymorphs and their symmetrically equivalent variants. We use first-principles electronic structure methods to identify minimum energy pathways and map them in subspaces of the symmetry-adapted strain order parameters. We next investigate the atomic structure of domain boundaries that separate coexisting variants of ferroelectric ${\mathrm{HfO}}_{2}$. We rely on Gibbsian excess quantities and a precise specification of mechanical boundary conditions to describe the thermodynamic properties of domain boundaries. Our first-principles calculations show that the O and Hf shuffle arrangement within a domain boundary is closely related to the intermediate shuffle patterns of the homogeneous pathways between ferroelectric variants. Furthermore, the preferred structure within a boundary is very sensitive to local strain constraints imposed by the adjacent ferroelectric variants, leading to highly anisotropic domain boundary energies.

Toward an Agent-Based Blackboard System for Reactor Design Optimization

The field of reactor design is rich with opportunities for applications of computational optimization algorithms; these applications can range from preliminary core design to reactor shuffling patterns. Many of these schemes rely on sets of previously generated solutions (sometimes referred to as “generations”) to inform future decisions. While it is important to build upon prior knowledge, this process requires a full generation of solutions to be formed before future solutions can be examined. Rather than relying on a generational scheme to perform an optimization, we propose using an agent-based approach in conjunction with a blackboard framework for performing reactor design optimizations. Utilizing an agent-based approach allows agents to perform tasks independently, while retaining the ability to build off of previous solutions. We develop an agent-based blackboard system (ABBS) for determining the Pareto front (PF) in sodium fast reactor design optimization problems and compared this with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Our goal is to evaluate the viability of the ABBS in producing a PF that is comparable with the NSGA-II algorithm. The design space consists of the fuel height, fuel smear, and plutonium fraction in the core, and we seek to minimize the reactivity swing and plutonium mass, while maximizing the burnup. The diversity, coverage, and spread of the PFs generated by the two methods are examined, and the ABBS is able to converge to the same PF as the NSGA-II algorithm. These results show that the ABBS is able to find optimal designs that are similar to those found by the NSGA-II algorithm. We conclude our study by applying the ABBS to the design of a sodium-cooled fast reactor to dispose of weapons-grade plutonium. The ABBS finds a core design that can burn upwards of 17.5 kg of weapons-grade plutonium per year and degrade an additional 195 kg of weapons-grade plutonium per year into non-weapons-grade material.

A taxonomy of grain boundary migration mechanisms via displacement texture characterization

Atomistic simulations provide the most detailed picture of grain boundary (GB) migration currently available. Nevertheless, extracting unit mechanisms from atomistic simulation data is difficult because of the zoo of competing, geometrically complex 3D atomic rearrangement processes. In this work, we introduce the displacement texture characterization framework for analyzing atomic rearrangement events during GB migration, combining ideas from slip vector analysis, bicrystallography and optimal transportation. Two types of decompositions of displacement data are described: the shear-shuffle and min-shuffle decomposition. The former is used to extract shuffling patterns from shear coupled migration trajectories and the latter is used to analyze temperature dependent shuffling mechanisms. As an application of the displacement texture framework, we characterize the GB geometry dependence of shuffling mechanisms for a crystallographically diverse set of mobile GBs in FCC Ni bicrystals. Two scientific contributions from this analysis include 1) an explanation of the boundary plane dependence of shuffling patterns via metastable GB geometry and 2) a taxonomy of multimodal constrained GB migration mechanisms which may include multiple competing shuffling patterns, period doubling effects, distinct sliding and shear coupling events, and GB self diffusion.

Fatigue-related reductions in movement smoothness during a lateral shuffle and side-cutting movement

ABSTRACT Although movement smoothness is considered a hallmark of well-coordinated motor tasks, it is unknown whether markers of movement smoothness can be used to assess the quality of neuromuscular control in athletes. As a first step into this direction, the purpose of this study was to test whether movement smoothness is reduced following a fatiguing lateral shuffle protocol due to fatigue-related adaptations in neuromuscular control. Sixteen healthy adults (7 females) completed a submaximal 3-minute lateral shuffle trial and a maximal fatiguing shuffle trial until task failure. The movement of the pelvis and feet was determined using 3D motion capture at 250 Hz. Movement smoothness was quantified using the log-dimensionless jerk, which represents how often and abruptly the segment acceleration changes over time. Pelvis and foot movement smoothness along with spatiotemporal variables characterizing the shuffling pattern were compared between the beginning and end of the fatiguing shuffle trial using Wilcoxon signed-rank tests (α = 0.05). Pelvis movement smoothness was significantly reduced in all movement directions (p ≤ 0.005, strong effects) while foot movement smoothness was predominantly reduced in the shuffle direction (p ≤ 0.018, moderate to strong effects). Reductions in movement smoothness coincided with a lower peak pelvis speed in shuffle direction (p = 0.007, strong effect) and shorter contact times when changing direction (p = 0.049, moderate effect). These reductions in movement smoothness may be explained by a change in the overall shuffle pattern characterized by “harder” side-cuts as well as by a muscle fatigue-related decline in the ability to precisely plan and execute foot trajectories.

Neutronics study on small power ADS loaded with recycled inert matrix fuel for transuranic elements transmutation using Serpent code

A small power ADS design using thorium oxide and diluent matrix reprocessed fuel is proposed for a high transmutation rate, small reactivity swing, and strong safety features. Two fuel matrices (CERCER and CERMET) and different recycled fuel compositions recovered from UO2 spent fuels with 45 GWd/tU and 60 GWd/tU burnup were investigated to determine the suitable fuel for the ADS. It was found that the transmutation of each isotope depends on TRU initial loading amount. After examining the cores, the results show that CERCER fueled ADS has a negative coolant void reactivity (CVR) and a smaller radiotoxicity at discharge compared to that of CERMET core. It implies that CERCER fuel has enhanced safety features and more flavor in terms of radiotoxicity management. To increase fuel utilization and core operation efficiency, a simple assembly shuffling pattern for the CERCER fueled ADS is also proposed. Eigenvalue and burnup calculations were conducted using Serpent 2 with ENDF/B-VII.0 library in both kcode and external source modes, and it indicates that the results of transmutation analyses obtained by kcode only is reliable to discuss the transmutation potential of ADS. Burnup calculation with the fixed-source mode is essential to be used for more practical results of the transmutation by ADS.

Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques

Speech emotion recognition is one of the challenging research issues in the knowledge-based system and various methods have been recommended to reach high classification capability. In order to achieve high classification performance in speech emotion recognition, a nonlinear multi-level feature generation model is presented by using cryptographic structure. The novelty of this work is the use of cryptographic structure called shuffle box for feature generation and iterative neighborhood component analysis to select the features. The proposed method has three main stages: (i) multi-level feature generation using Tunable Q wavelet transform (TQWT), (ii) twine shuffle pattern (twine-shuf-pat) for feature generation, and (iii) discriminative features are selected using iterative neighborhood component analysis (INCA) and classified. The TQWT is a multi-level wavelet transformation method used to generate high-level, medium-level, and low-level wavelet coefficients. The proposed twine-shuf-pat technique is used to extract the features from the decomposed wavelet coefficients. INCA feature selector is employed to select the clinically significant features. The performance of the obtained model is validated using four speech emotion public databases (RAVDESS Speech, Emo-DB (Berlin), SAVEE, and EMOVO). Our developed twine-shuf-pat and INCA based method yielded 87.43%, 90.09%, 84.79%, and 79.08% classification accuracies using RAVDESS, Emo-DB (Berlin), SAVEE and EMOVO corpora respectively with 10-fold cross-validation strategy. A mixed database is created from four public speech emotion databases which yielded 80.05% classification accuracy. Our obtained speech emotion model is ready to be tested with huge database and can be used in healthcare applications.

Greenhouse environment modeling and simulation for microclimate control

Greenhouse plant science assays have been impacted by microclimates which causes significant level of noise to plant growth measurement data. Researchers and scientist have been randomizing pots locations, which helps to re-distribute the noise, but does not remove the noise. The impacts from microclimates can be eliminated by shuffling plants, but there has been no study on the optimization of shuffling pattern, such as the frequency and moving distance for the pots. It is important to quantitatively study the microclimates in the greenhouse, so we can optimize the shuffling pattern accordingly. The aim of this study was to propose a computer modeling approach for simulating microclimate in the greenhouse, and then use the simulation result to optimize pot movement distance and frequency. A computational greenhouse model was developed using inputs from real design, materials and location of a Purdue Lily greenhouse in West Lafayette, Indiana. Microclimate variables, including ambient temperature and lighting radiation over 24 h and 7 days were predicted with the simulation model. Thermometers and lighting sensors were also distributed in the greenhouse for the ground-truth measurements over a seven-day period. Comparison of measured microclimate variables with predicted variables obtained from the computational model demonstrated that the simulation model could precisely predict temperatures and light radiation at any time, and at different positions in the greenhouse. Optimized pot movement frequency and distance were then determined with the simulation result. The new shuffling pattern can remove over 90% of the microclimate variance but could save more than 95% shuffling efforts compared with non-stop movement.

Flexible core design of Super FBR with multi-axial fuel shuffling

To utilize the merit of supercritical water cooling, the Super FBR core concept, which is compatible with both the high breeding and the high enthalpy rise needs to be developed. One possible solution to meet such requirements may be to compose an axially heterogeneous core with MOX and blanket layers, with consideration of the large density change and specific heat of supercritical water at vicinity of the pseudocritical point. A new design concept of Super FBR has been proposed with “with multi-axial fuel shuffling”, which has flexibility in designing fuel shuffling schemes in the lower part and upper part of the core independently. Fully coupled neutronics and thermal-hydraulics core calculations were carried out to investigate impact of designing independent number of fuel batches and shuffling patterns in the upper and the lower parts of the core. Promising results were obtained, showing possibility of improving the core breeding performance with respect to the compound system doubling time (CSDT) by reducing the reactor doubling time (RDT) with designing of the independent fuel shuffling. Moreover, reduction in the ex-core factor (EF) was shown to be possible with such independent fuel shuffling. The combined effects of reductions in RDT and EF showed significant reduction in CSDT. It is the first design concept of Super FBR with coolant enthalpy rise, which covers from the liquid like state (below the pseudo-critical point) to the gas-like state (above the pseudo-critical point) of supercritical water. Further design investigations may be necessary to reduce CSDT and increase the average core outlet temperature.

Vectorizable Design and Implementation of FFT Based on Fused Multiply-add Architectures

This paper proposed a high efficient method by using fused multiply-add instruction to map FFT algorithms based on vector processors. According to the architecture feature of YHFT-Matrix, combing shuffle needs with memory access requests to reduce shuffling pattern, and also the method which utilizes software pipelining to fully exploit instruction-level and data-level parallelism of FFT algorithms. Then the calculating performance is improved. Experimental results show that FFT algorithms achieve high computing performance and speedups. For instance, after adopting FMA instruction optimization, the chip’s computational efficiency of 1024-point double-precision floating-point FFT algorithm is about 10% higher than before.

Enhancing Authentication Schemes for Multi-Level Graphical Password in Cloud Environment

The graphical password patterns are in the rising trend in world with the abundance of the touch screen devices. A variety of touch screen devices are present for the users such as mobile phones, tables, touch-enabled laptops, touchenabled notebooks, etc. The graphical password has evolved with the invention of the touch-screen devices. The popular graphical schemes known as Pass-Go Pattern, Pass-point pattern and other similar schemes has been studied for the development of the new graphical password scheme. The existing models based upon pass-go and pass-point model stays as the basic model for our research for the development of the effective and secure graphical password scheme. It becomes difficult to input the alphanumeric passwords on the touch screens. The alphanumeric input lacks the high order accuracy as well as requires more focus to input the password. Most of the popular schemes have used the 3x3, 3x4 or 4x3 point-grid method for prompting the patterns to the users. The clue-point method is another popular method to display the graphical grid for the password input. In the proposed graphical model, graphical authentication model based upon the images has been aimed at to resolve the issues persisting in the existing models. In this model, the shuffling pattern based method has been used for the mitigation of the shoulder surfing attacks. The shuffling pattern scheme changes the primary display for password input every-time, which also restructure the input grid to overcome the threat caused by the shoulder surfing attacks.The proposed model has been designed to offer the robust graphical password scheme with the face images randomly collected by the users. The random point module for the visualization of the password input module plays the key role in the proposed graphical password scheme. The proposed model is a circular point model where the points are placed on the circle and the images are drawn on the given points. The user has to input the graphical pattern by joining the images with each other in the certain sequence. The proposed model requires less focus and highly accurate and easy to use. The experimental results have been evaluated in the factors associated with the study of the usability, memorabiltiy and difficulty in password creation. The proposed model has been compared against the existing models on the basis of the latter factors, where the proposed model has outperformed the existing models.

3D in-core fuel management optimization for breed-and-burn reactors

Breed-and-burn (B&B) reactors are a special class of fast reactors that are designed to utilize low grade fuel such as depleted uranium without fuel reprocessing. One of the most challenging practical design feasibility issues faced by B&B reactors is the high level of radiation damage their fuel cladding has to withstand in order to sustain the B&B mode of operation – more than twice the maximum radiation damage cladding materials were exposed to so far in fast reactors. This study explores the possibility of reducing the minimum required peak radiation damage by employment of 3-dimensional (3D) fuel shuffling that enables a significant reduction in the peak-to-average axial burnup, that is, more uniform fuel utilization. A new conceptual design of a B&B core made of axially segmented fuel assemblies was adopted to facilitate the 3D shuffling. Also developed is a Simulated Annealing (SA) algorithm to automate the search for the optimal 3D shuffling pattern (SP). The primary objective of the SA optimization is to minimize the peak radiation damage while its secondary objective is to minimize the burnup reactivity swing, radial power peaking factor and maximum change of fuel assembly power over the cycle. Also studied is the sensitivity of the 3D shuffled core performance to the number of axially stacked sub-assemblies, core height and power level.It was found that compared with the optimal 2-dimensional (2D) shuffled core, the optimal 3D shuffled B&B core made of four 70 cm long axially stacked sub-assemblies and 12 radial shuffling batches offers a 1/3 reduction of the peak radiation damage level – from 534 down to 351 displacements per atom (dpa), along with a 45% increase in the average fuel discharge burnup, and hence, the depleted uranium utilization, while satisfying all major neutronics and thermal-hydraulics design constraints. For the same peak dpa level, the 3D shuffling offers more than double the uranium utilization and the cycle length relative to 2D shuffling. The minimum peak radiation damage is increased to 360 or to 403 dpa if the core is made of, respectively, three – 70 cm or two – 140 cm long axially stacked subassemblies. Reducing the length of the subassemblies of B&B cores made of three-segment assemblies from 70 cm to 60 or 50 cm results in an increase in the peak radiation damage from 360 dpa to, respectively, 368 and 397 dpa.

Shuffle up and deal: accelerating GPGPU Monte Carlo simulation with application to option pricing

SummaryIn this paper, we demonstrate some speedup opportunity regarding Monte Carlo simulation on graphic processing unit architecture, with financial application. We leverage on the possibility of reducing the volume of actually generated random numbers, by replacing the generation phase with some shuffling using Compute Unified Device Architecture's built‐in shuffle instructions. We will study various shuffling patterns and duration, elect the best among them with regard to induced correlation, using Granger causality test. We will then study the accuracy and variance of results actually achieved by our general‐purpose computing on graphic processing unit shuffled Monte‐Carlo, exhibiting a computational time reduced by half while error remains marginal. Copyright © 2015 John Wiley & Sons, Ltd.

Integrated Nondestructive Assay Systems to Estimate Plutonium in Spent Fuel Assemblies

An integrated nondestructive assay (NDA) system combining active (neutron generator) and passive neutron detection and passive gamma (PG) detection is being analyzed in order to estimate the amount of plutonium, verify initial enrichment, burnup, and cooling time, and detect partial defects in a spent fuel assembly (SFA). Active signals are measured using the differential die-away (DDA), delayed neutron (DN), and delayed gamma (DG) techniques. Passive signals are measured using total neutron (TN) counts and both gross and spectral resolved gamma counts. To quantify how a system of several NDA techniques is expected to perform, all of the relevant NDA techniques listed above were simulated as a function of various reactor conditions such as initial enrichment, burnup, cooling time, assembly shuffling pattern, reactor operating conditions (including temperature, pressure, and the presence of burnable poisons) by simulating the NDA response for five sets of light water reactor assemblies. This paper compares the performance of several exploratory model-fitting options (including neural networks, adaptive regression with splines, iterative bias reduction smoothing, projection pursuit regression, and regression with quadratic terms and interaction terms) to relate data simulated with measurement and model error effects from various subsets of the NDA techniques to the total Pu mass. Isotope masses for SFAs and expected detector responses (DRs) for several NDA techniques are simulated using MCNP, and the DRs become inputs to the fitting process. Such responses include eight signals from DDA, one from DN, one from TN, and up to seven from PG; the DG signal will be examined separately. Results are summarized using the root-mean-squared estimation error for plutonium mass in held-out subsets of the data for a range of model and measurement error variances. Different simulation assumptions lead to different spent fuel libraries relating DRs to Pu mass. Some results for training with one library and testing with another library are also given.

Total neutron emission generation and characterization for a Next Generation Safeguards Initiative spent fuel library

In March of 2009 the Next Generation Safeguards Initiative of the U.S. Department of Energy began a nominal five year spent fuel research effort with the goal of: (1) quantifying plutonium content in spent nuclear fuel through the use of non-destructive assay (NDA) techniques; (2) quantifying the capability of these NDA techniques to quantify burnup, cooling time, and initial enrichment, as well as detect pin diversions, for spent fuel assemblies. These NDA techniques were first scoped in computation space in order to understand detection limitations and down select for further testing. Multiple Monte Carlo based spent fuel libraries (SFL's) were developed to be used as source terms for assessing the detection limitations of each of these techniques. The characterization of the SFL's provide an analysis of different burn strategies used for spent fuel, functional fits for state point analysis, and the components of the neutron signal.This paper details both a methodology for generating the spatially dependent gross neutron emission (GNE) as well as a characterization of the GNE for a particular NGSI SFL for two different shuffle patterns. The GNE was characterized by examining three major components: (1) the total neutron emission; (2) the (α, n) and spontaneous fission emissions; and (3) the main contributors to the spontaneous fission and (α, n) emission signals. The total neutron emission was characterized by looking at two different shuffle patterns and using three different pin analysis techniques. The pin analysis techniques used were: (1) sum all the pins in the assembly; (2) create four pin zones to be summed; and (3) examine specific pins. These characterizations provide a large set of data with integral values (cooling time vs emission and burnup vs emission) and derivative values (isotopic percent composition) with visual depiction and detailed explanation. The characterizations also provide a comparison of the effects of shuffle schemes on the neutron emission signal for two different shuffle patterns. This data can be used in the development of time and burnup dependent normalized functions to describe the trends displayed in the data. This study also shows that the information which can be obtained from the GNE depends upon how the information is grouped and analyzed. Summing all the pins of the assembly or assuming a uniform burnup results in the loss of valuable neutron emission information. By splitting the pins into zones, trends such as the total emissions across the assembly become evident. By evaluating individual pins trends such as the effect of water rods on the neutron emission become evident. This type of analysis can be of great use to safeguards. Evaluating the GNE on a pin by pin basis leads to a much clearer picture of the constituents of the assembly.

Automatic loading pattern optimization tool for Loviisa VVER-440 reactors

Abstract An automatic loading pattern optimization tool called ALPOT has been developed for Loviisa VVER-440 reactors. The ALPOT code utilizes combination of three different optimization methods. The first method is the imitation of the equilibrium pattern that is the optimized pattern in case the cycle length and the operation conditions are constant and the same shuffling pattern is repeated from cycle to cycle. In practice, the algorithm imitates assemblies’ operation year distribution of the equilibrium pattern stochastically. The function of the imitation algorithm is to provide initial patterns quickly for the next optimization phase, which is performed either with the stochastic guided binary search algorithm or the deterministic burnup kernel method depending on the choice of the user. The former is a modified version of the standard binary search. The standard version goes through all possible swaps of the assemblies and chooses the best swap at each iteration round. The guided version chooses one assembly, tries to swap it with every other possible assembly and performs the best swap at each iteration round. The search is guided so that the algorithm chooses the assemblies at or near the most restrictive fuel assembly first. The kernel method creates burnup kernel functions to estimate burnup variations that are required to achieve desired changes in the power distribution of the reactor. The idea of the kernel method is first determine the optimal burnup distribution that minimizes the maximum relative assembly power using the created kernel functions and a common solver routine. Then, the burnups of the available fuel assemblies are matched with the obtained burnup distribution.

Modified Multi-Chaotic Systems that are Based on Pixel Shuffle for Image Encryption

Recently, a pixel-chaotic-shuffling (PCS) method has been proposed by Huang et al. for encrypting color images using multiple chaotic systems like the Henon, the Lorenz, the Chua, and the Rossler systems. All of which have great encryption performance. The authors claimed that their pixel-chaotic-shuffle (PCS) encryption method has high confidential security. However, the security analysis of the PCS method against the chosen-plaintext attack (CPA) and known-plaintext attack (KPA) performed by Solak et al. successfully breaks the PCS encryption scheme without knowing the secret key. In this paper we present an improved shuffling pattern for the plaintext image bits to make the cryptosystem proposed by Huang et al. resistant to chosen-plaintext attack and known-plaintext attack. The modifications in the existing PCS encryption method are proposed to improve its security performance against the potential attacks described above. The Number of Pixel Change Rate (NPCR), Unified Average Changed Intensity (UACI), information entropy, and correlation coefficient analysis are performed to evaluate the statistical performance of the modified PCS method. The simulation analysis reveals that the modified PCS method has better statistical features and is more resistant to attacks than Huang et al.'s PCS method.

Finding the best fuel assemblies shuffling scheme of ADS for MA transmutation using Dynamic Programming

Dynamic Programming is applied to find the best shuffling scheme of ADS, which consists of 54 fuel assemblies and a spallation target of Pb–Bi, and the best scheme is successfully found under different constraints of power peaking factor. In the present problem the average transmutation ratio of MA is maximized under the constraints for effective neutron multiplication factor, discharged fuel burn-up, and power peaking factor. The obtained results show the best fuel shuffling scheme consists of initial unique shuffling pattern and succeeding repetitive patterns for all cases. The repetitive pattern is unique for each constraint of power peaking factor, the best shuffling scheme changes sensitively for the change of constraints. For most best shuffling schemes, fresh fuel is loaded into the 2nd inner row of fuel region, and finally discharged from the inner or outer region because of the constraint of power peaking factor.