Advanced Code Research Articles

Innovations in Wave Energy: A Case Study of TALOS-WEC’s Multi-Axis Technology

The technologically advanced learning ocean system—wave energy converter (TALOS-WEC) project addresses the urgent need for sustainable and efficient energy solutions by leveraging the vast potential of wave energy. This project presents a pioneering approach to wave energy capture through its unique multi-axis and omnidirectional point absorber design. Featuring a fully enclosed power take-off (PTO) system, the TALOS-WEC harnesses energy across six degrees of freedom (DoFs) using an innovative internal reaction mass (IRM) mechanism. This configuration enables efficient energy extraction from the relative motion between the IRM and the hull, aiming for energy conversion efficiencies ranging between 75–80% under optimal conditions, while ensuring enhanced durability in harsh marine environments. The system’s adaptability is reflected in its versatile geometric configurations, including triangular, octagonal, and circular designs, customised for diverse marine conditions. Developed at Lancaster University, UK, and supported by international collaborations, the TALOS-WEC project emphasises cutting-edge advancements in hydrodynamic modelling, geometric optimisation, and control systems. Computational methodologies leverage hybrid frequency-time domain models and advanced panel codes (WAMIT, HAMS, and NEMOH) to address non-linearities in the PTO system, ensuring precise simulations and optimal performance. Structured work packages (WPs) guide the project, addressing critical aspects such as energy capture optimisation, reliability enhancement, and cost-effectiveness through innovative monitoring and control strategies. This paper provides a comprehensive overview of the TALOS-WEC, detailing its conceptual design, development, and validation. Findings demonstrate TALOS’s potential to achieve scalable, efficient, and robust wave energy conversion, contributing to the broader advancement of renewable energy technologies. The results underscore the TALOS-WEC’s role as a cutting-edge solution for harnessing oceanic energy resources, offering perspectives into its commercial viability and future scalability.

Applying multiple processes nonequilibrium model to investigate cesium transport in crushed granite

Abstract Understanding the movement of radionuclides (RN) in the subsurface environment is of paramount importance, particularly when it comes to the planning and assessment of facilities devoted to the disposal of radioactive waste. Comprehensive mathematical models serve as indispensable tools in this regard, demanding a profound and thorough understanding of the intricate mechanisms underlying radionuclide transport. The effective application of these models is contingent upon accurately determining the required input parameters. This is a critical aspect to consider given the inherent physical and chemical variations exhibited by the subsurface environment. These variations can induce significant effects on the movement of RNs below ground, potentially altering the predicted outcomes of radionuclide transport. This paper presents the findings of a comprehensive investigation that was conducted utilizing both advective-dispersive experiments (ADE) and multiple processes nonequilibrium (MPNE) inversion. These methodologies were employed using the advanced HYDRUS code, which is highly regarded in the field. The research specifically focuses on the transportation mechanisms of Cesium (Cs), a common radionuclide, in a medium of crushed granite. The study considers varying conditions, including different flow rates and column lengths, to provide a broad understanding of the behavior of Cs. The findings reveal that the transport behavior of Cs is not only influenced by the different flow rates and column lengths but is also significantly affected by the diffusive mass transfer and nonequilibrium sorption. These factors collectively contribute to our understanding of the complex processes involved in radionuclide transport.

Influence of hydrogen content in tokamak scrape-off-layer on performance of lithium divertor

Abstract Self-replenishing liquid metal coatings are considered as a perspective divertor design able to withstand challenging particle and power loads of a fusion tokamak-reactor. Numerical modeling of the scrape-of-layer (SOL) plasma with advanced 2D codes, such as SOLPS, is necessary for developing of the ‘liquid-metal’ divertor. In this work we report on upgraded version of SOLPS 4.3 code liquid metal erosion module implemented earlier in our group and present results of simulations of T-15MD tokamak with Li-covered divertor plates. The erosion model includes all main processes Li erosion, i.e. physical sputtering, thermal sputtering, evaporation, and prompt redeposition. Unlike some other available implementations, Li atoms are considered in kinetic approximation in our version. A detailed analysis of Li erosion and flow in T-15MD configuration for various powers (6–12 MW) and H content in the SOL is presented. It is shown that the most of eroded Li particles are redeposited on the divertor targets, however, in some regimes absolute Li flow from the divertor is still large and might lead to significant main plasma dilution with Li. Vapor shielding effect is pronounced on both divertor targets in the most reasonable regimes providing low peak heat flux values at the target plates, less than 10 MW m−2. The target erosion rate and surface temperatures are within limits of the most target designs. Moreover, in strongly shielded cases the target temperature can be even lower than the Li melting temperature meaning that external heating is required to keep Li flowing. Sensitivity analysis shows that our results are most sensitive to the target heat conduction parameters, i.e. the target thickness, outer surface temperature. It means that controlling the target cooling rate can be a useful tool for controlling the liquid Li divertor regime. Variation of the Li erosion rate parameters has little effect on the divertor performance.

Measuring code efficiency optimization capabilities with ACEOB

As Moore’s Law gains diminish, software performance and efficiency become increasingly vital. Optimizing code efficiency is challenging, even for professional programmers. However, related research remains relatively scarce, and rigorously assessing models’ abilities to optimize code efficiency is fraught with difficulties. In response to this challenge, we first conduct an in-depth analysis of “code patterns” in the model training dataset, meticulously exploring human-written code. Secondly, we define a task for optimizing code efficiency and introduce the Automatic Code Efficiency Optimization Benchmark (ACEOB), which consists of 95,359 pairs of efficient–inefficient code aimed at assessing code efficiency optimization capabilities. To our knowledge, ACEOB is the first dataset specifically targeting Python code efficiency optimization. To evaluate models’ ability in optimizing code efficiency, we propose two new metrics: the Isomorphic Optimal Comparison CodeBLEU (IOCCB) metric and the Normalized Performance Index (NPI) metric, to assess the efficiency of model-generated code. We also evaluate several advanced code models, such as PolyCoder and CodeT5, after fine-tuning them on ACEOB and demonstrate that the efficiency of each model improves after introducing the NPI filter. However, it was observed that even ChatGPT does not perform optimally in code efficiency optimization tasks. Our dataset and models are available at: https://github.com/CodeGeneration2/ACEOB.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Advanced multicolor dynamic fluorescence anti-counterfeiting and encryption strategy based on light-induced reversible perovskite lattice distortion

Time-dynamic fluorescence encryption and anti-counterfeiting technology have garnered significant attention in the high-end information security field. However, developing tunable multicolor solid-state photoluminescent systems that are low-cost, easy to manufacture, scalable, and convenient to verify remains a considerable challenge. In this study, we finely tuned the luminescence behavior of CsCdCl3 all-inorganic perovskite crystals using a halogen doping strategy, resulting in reversible lattice distortion under UV light and endowing them with photoactivated luminescence properties to produce dynamic fluorescence. Upon the introduction of Br-, the optical properties of CsCdCl3 changed significantly, with the fluorescence emission color shifting from orange to white-green under UV irradiation. By adjusting the Br- doping ratio and UV irradiation intensity, the fluorescence color change time of CsCdCl3 can be controlled. Multiple cycle light exposure tests demonstrated that the luminescence properties of CsCdCl3 remained identical to the initial state, indicating high stability in response to UV stimulation. Consequently, we successfully realized advanced anti-counterfeiting and 4D code encryption modes based on dynamic fluorescence. The introduction of a time variable imparts extremely high security to these strategies. This work provides an exciting approach for designing information encryption materials with higher security requirements and offers a promising high-sensitivity UV detection material.

Implementation of matrix compression in the coupling of JOREK to realistic 3D conducting wall structures

Abstract JOREK is an advanced non-linear simulation code for studying MHD instabilities in magnetically confined fusion plasmas and their control and/or mitigation. A free-boundary and resistive wall extension was introduced via coupling to the STARWALL and CARIDDI codes, both able to provide dense response matrices describing the electromagnetic interactions between plasma and conducting structures. For detailed CAD representations of the conducting structures and high resolutions for the plasma region, memory and computing time limitations restrict the possibility of simulating the ITER tokamak. In the present work, the Singular Value Decomposition provided by routines from the ScaLAPACK library has been successfully applied to compress some of the dense response matrices and thus optimize memory usage. This is demonstrated for simulations of Tearing Mode and Vertical Displacement Event instabilities. An outlook to future applications on large production cases and further extensions of the method are discussed.

Sligpt: A Large Language Model-Based Approach for Data Dependency Analysis on Solidity Smart Contracts

The advent of blockchain technology has revolutionized various sectors by providing transparency, immutability, and automation. Central to this revolution are smart contracts, which facilitate trustless and automated transactions across diverse domains. However, the proliferation of smart contracts has exposed significant security vulnerabilities, necessitating advanced analysis techniques. Data dependency analysis is a critical program analysis method used to enhance the testing and security of smart contracts. This paper introduces Sligpt, an innovative methodology that integrates a large language model (LLM), specifically GPT-4o, with the static analysis tool Slither, to perform data dependency analyses on Solidity smart contracts. Our approach leverages both the advanced code comprehension capabilities of GPT-4o and the advantages of a traditional analysis tool. We empirically evaluate Sligpt using a curated dataset of Ethereum smart contracts. Sligpt achieves significant improvements in precision, recall, and overall analysis depth compared with Slither and GPT-4o, providing a robust solution for data dependency analysis. This paper also discusses the challenges encountered, such as the computational resource requirements and the inherent variability in LLM outputs, while proposing future research directions to further enhance the methodology. Sligpt represents a significant advancement in the field of static analysis on smart contracts, offering a practical framework for integrating LLMs with static analysis tools.

Web-CONEXS: an inroad to theoretical X-ray absorption spectroscopy.

Accurate analysis of the rich information contained within X-ray spectra usually calls for detailed electronic structure theory simulations. However, density functional theory (DFT), time-dependent DFT and many-body perturbation theory calculations increasingly require the use of advanced codes running on high-performance computing (HPC) facilities. Consequently, many researchers who would like to augment their experimental work with such simulations are hampered by the compounding of nontrivial knowledge requirements, specialist training and significant time investment. To this end, we present Web-CONEXS, an intuitive graphical web application for democratizing electronic structure theory simulations. Web-CONEXS generates and submits simulation workflows for theoretical X-ray absorption and X-ray emission spectroscopy to a remote computing cluster. In the present form, Web-CONEXS interfaces with three software packages: ORCA, FDMNES and Quantum ESPRESSO, and an extensive materials database courtesy of the Materials Project API. These software packages have been selected to model diverse materials and properties. Web-CONEXS has been conceived with the novice user in mind; job submission is limited to a subset of simulation parameters. This ensures that much of the simulation complexity is lifted and preliminary theoretical results are generated faster. Web-CONEXS can be leveraged to support beam time proposals and serve as a platform for preliminary analysis of experimental data.

3D code for MAgneto-Thermal evolution in Isolated Neutron Stars, MATINS: thermal evolution and light curves

ABSTRACT The thermal evolution of isolated neutron stars is a key element in unravelling their internal structure and composition and establishing evolutionary connections among different observational subclasses. Previous studies have predominantly focused on one-dimensional or axisymmetric two-dimensional models. In this study, we present the thermal evolution component of the novel three-dimensional magnetothermal code MATINS (MAgneto-Thermal evolution of Isolated Neutron Star). MATINS employs a finite volume scheme and integrates a realistic background structure, along with state-of-the-art microphysical calculations for the conductivities, neutrino emissivities, heat capacity, and superfluid gap models. This paper outlines the methodology employed to solve the thermal evolution equations in MATINS, along with the microphysical implementation that is essential for the thermal component. We test the accuracy of the code and present simulations with non-evolving magnetic fields of different configurations (all with electrical currents confined to the crust and a magnetic field that does not thread the core), to produce temperature maps of the neutron star surface. Additionally, for a specific magnetic field configuration, we show one fully coupled evolution of magnetic field and temperature. Subsequently, we use a ray-tracing code to link the neutron star surface temperature maps obtained by MATINS with the phase-resolved spectra and pulsed profiles that would be detected by distant observers. This study, together with our previous article focused on the magnetic formalism, presents in detail the most advanced evolutionary code for isolated neutron stars, with the aim of comparison with their timing properties, thermal luminosities and the associated X-ray light curves.

Implementation of a Drift Flux Model into SAM with Development of a Verification and Validation Test Suite for Modeling of Noncondensable Gas Mixtures

The advanced thermal-hydraulic system code, System Analysis Module (SAM), was originally developed for the modeling of single-phase flow in advanced reactors. It has since been expanded to include a four-equation drift flux model for the modeling of two-phase flows containing a noncondensable gas. The model was expanded to support the modeling of molten salt reactor (MSR) designs in which the fuel is directly dissolved in the circulating coolant. These designs have shown that circulating gas bubbles can play an important role in the management of fission products and the operational behavior of the reactor. A drift flux model was implemented to more accurately capture the localized behavior of the void in the core and its impact on the mass transfer of fission products. A thorough assessment of the new model was performed by developing a verification and validation test suite. Verification problems were designed to test all major terms in the new governing equations. The new model converged to the correct solution at the expected order of accuracy for all verification cases. The validation cases included a wide range of flow and void conditions in different pipe geometries. Although higher void experiments show a slight underprediction of void by the drift flux model, experiments that aim to reproduce Molten Salt Reactor Experiment (MSRE) experimental conditions show good agreement with the model. The gas transport model was activated for a SAM model of the MSRE to demonstrate that it can be used in a more complex model. This gas transport model will be used along with an interfacial area transport equation being implemented in SAM for the prediction of mass transport behavior in MSR conditions.

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal–cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. The temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code’s covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

Automated Code Review Tool

As software development undergoes continual evolution, the assurance of code quality remains paramount in the development lifecycle. This research paper introduces an innovative Automated Code Review Tool engineered to augment and streamline the code review process. The tool capitalizes on advanced static code analysis, machine learning algorithms, and industry best practices to automate the detection of code quality issues, security vulnerabilities, and compliance with coding standards. The Automated Code Review Tool addresses the inherent challenges of manual code reviews, including human error, time constraints, and inconsistencies. Through automation, developers can expedite the identification and resolution of potential issues, thereby enhancing overall code quality and software reliability. Key features of the tool encompass intelligent pattern recognition, real-time feedback, and customizable rule sets, enabling development teams to tailor the tool to their project-specific requirements. Leveraging machine learning algorithms facilitates the tool's continuous learning from past reviews, thereby adapting to evolving coding practices and emerging security threats. This paper presents the architectural framework and design principles underpinning the Automated Code Review Tool, emphasizing its capacity to foster collaboration among development teams, reduce time-to-market, and ultimately contribute to the development of more robust and secure software. A comprehensive evaluation of the tool's efficacy across diverse development environments is conducted, offering insights into the practical implications of embracing automated solutions in real-world contexts. Keywords: Automated Code Review Tool, Code quality, Static code analysis, Machine learning algorithms, Coding standards, Manual code reviews, Human error, Time constraints, etc.

DUGKS-GPU: An efficient parallel GPU code for 3D turbulent flow simulations using Discrete Unified Gas Kinetic Scheme

This paper presents a parallel implementation of the Discrete Unified Gas Kinetic Scheme (DUGKS) on the GPU system using the CUDA Fortran and CUDA C++ programming languages. Firstly, we conducted an extensive revision of our original CPU-based code, resulting in a threefold decrease in memory usage. This new implementation is also paired with a novel approach to compute cell face flux using trilinear interpolation. It is shown analytically that the interpolation-based approach to flux calculation is more accurate compared to the one used in the original DUGKS. The initial simulation results using this new approach suggest that trilinear interpolation can reduce numerical errors on a coarse mesh. For example, in the case of the decaying Taylor-Green vortex flow at a 1283 mesh resolution, the relative numerical error in the energy dissipation rate at t⁎=2, using the spectral simulation result as the benchmark, is approximately 30% lower than that of the original implementation. The improved GPU DUGKS method is applied to laminar and turbulent flows in periodic and wall-bounded boundary configurations. A performance comparison of the GPU implementation is also presented and compared to the previous CPU implementation. A maximum speedup of 7.64x was achieved on a desktop-level GPU compared to a 32-core CPU. The strong scaling test, conducted on an eight-GPU node, demonstrated the efficient utilization of available multiple GPU resources by the code. Program summaryProgram Title: DUGKS-GPUCPC Library link to program files:https://doi.org/10.17632/yykv5s9g2n.1Developer's repository link:https://github.com/kairzhan/DUGKS-GPUCode Ocean capsule:https://codeocean.com/capsule/3b1e4f74-cdd3-4781-8923-8514d5923dfb/Licensing provisions: GNU General Public License 3Programming language: CUDA C++, CUDA FortranSupplementary material:Nature of problem: DUGKS-GPU is an advanced numerical code designed to accelerate the simulation of turbulent fluid flows through the application of the kinetic method known as the Discrete Unified Gas Kinetic Scheme (DUGKS). This computational tool comprises a CUDA Fortran version, tailored for a single GPU, as well as a CUDA C++ version developed for multi-GPU platforms.Solution method: The code employs a second-order finite-volume discretization of the discrete velocity Boltzmann equation with the BGK collision model. It can be used to simulate small to medium-scale problems on modern multi-GPU platforms with CUDA architecture.

Online practical education and training in nuclear engineering: A methodological framework

The education of students in the field of nuclear engineering must combine theoretical and practical teaching, this is the only way to produce quality graduates. Practical education generally includes two areas — experimental teaching and the use of advanced computational codes for the simulation of physical phenomena. The availability of practical education is not a matter of course for all students. The transfer of practical teaching to an online environment opens up a lot of possibilities even for universities that do not have a nuclear reactor, laboratories or extensive computing infrastructure at their disposal.The article deals with key aspects that must be respected when implementing online practical education and training. The listed tips and recommendations are based on the experience gained during the COVID pandemic and during the solution of the PADINE-TT project, which was a response to the development of online teaching and its inclusion in teaching at individual universities.

Large-scale kinetic simulations of colliding plasmas within a hohlraum of indirect-drive inertial confinement fusion.

The National Ignition Facility has recently achieved successful burning plasma and ignition using the inertial confinement fusion (ICF) approach. However, there are still many fundamental physics phenomena that are not well understood, including the kinetic processes in the hohlraum. Shan etal. [Phys. Rev. Lett. 120, 195001 (2018)0031-900710.1103/PhysRevLett.120.195001] utilized the energy spectra of neutrons to investigate the kinetic colliding plasma in a hohlraum of indirect drive ICF. However, due to the typical large spatial-temporal scales, this experiment could not be well simulated by using available codes at that time. Utilizing our advanced high-order implicit PIC code, LAPINS, we were able to successfully reproduce the experiment on a large scale of both spatial and temporal dimensions, in which the original computational scale was increased by approximately seven to eight orders of magnitude. Not only is the validity of the explanation of the experiment confirmed by our simulations, i.e., the abnormally large width of neutron spectra comes from beam-target nuclear fusions, but also a different physical insight into the source of energetic deuterium ions is provided. The acceleration of deuterium ions can be categorized into two components: one is propelled by a sheath electric field created by the charge separation at the onset, while the other is a result of the reflection of the potential of the shock wave. The robustness of the acceleration mechanism is analyzed with varying initial conditions, e.g., temperatures, drifting velocity, and ion components. This paper might serve as a reference for benchmark simulations of upcoming simulation codes and may be relevant for future research on mixtures and entropy increments at plasma interfaces.

Feature of the forward error correction constructions for optical transport networks

Due to the rapid increase of network traffic in the last few years, many telecommunication operators have started transitions to 100G optical networks and beyond. However, high speed optical networks need more efficient Forward Error Correction (FEC) codes to deal with the optical impairments. Forward error correction is widely used in optical communications to improve error correction and extend optical transmission distance. It is also used to reduce optical transmitter power and system costs. In response to the rapid growth of optical communications, the ITU-T has started researching FEC coding and has recommended ITU-T G.709 and G.975.1. As optical transmission systems evolve towards longer transmission distance, greater capacity, and speeds of 100G and beyond a variety of unwanted effects are seriously affecting smooth evolution. In optical transport network, FEC is getting more and more important as spectral efficiency is increasing. As 100G system is commercialized, there are some trends in the evolution of FEC, for example overhead is increased from 7% to 20% or even more. High-performance FEC codes are therefore being developed so that higher net coding gain (NCG) and better error correction can be achieved. The Optical Internetworking Forum (OIF) suggests that soft-decision forward-error correction (SD-FEC) with a redundancy of 20% and beyond be used in a 100G DWDM coherent system. The use of advanced modulation formats is a promising solution for attaining such high data rates in optical networks. However, as a signal constellation grows in size, so does the optical signal to signal-to-noise ratio it requires to achieve a certain bit error rate (BER). This will degrade the error correction capability. Decoding is moving from hard to soft. Vendors are developing their own advanced codes instead of using codes recommended by ITU-T. Because different application systems have different decoding performance, latency, power and cost requirements, FEC systems with various transmission overhead, implementation complexity, burst-error correction ability and error floor are available in today’s market. Soft-decision FEC often uses turbo product codes and low density parity check (LDPC) codes. In research area, new codes such as LDPC codes and their different varieties are introduced into optical communication. Optimized codeword structure and decoding algorithm that provides low BER. LDPC codes can be very powerful, but their practical implementation for optical communications links at ultra-high data rates remains a challenge since the decoding of the code requires soft-decision bits about the received bits. A family of structured codes known as quasi-cyclic LDPC codes, whose common structural properties can be exploited by unified encoding and decoding architectures to reduce the complexity in implementation.

Automated shape and thickness optimization for non-matching isogeometric shells using free-form deformation

Isogeometric analysis (IGA) has emerged as a promising approach in the field of structural optimization, benefiting from the seamless integration between the computer-aided design (CAD) geometry and the analysis model by employing non-uniform rational B-splines (NURBS) as basis functions. However, structural optimization for real-world CAD geometries consisting of multiple non-matching NURBS patches remains a challenging task. In this work, we propose a unified formulation for shape and thickness optimization of separately parametrized shell structures by adopting the free-form deformation (FFD) technique, so that continuity with respect to design variables is preserved at patch intersections during optimization. Shell patches are modeled with isogeometric Kirchhoff–Love theory and coupled using a penalty-based method in the analysis. We use Lagrange extraction to link the control points associated with the B-spline FFD block and shell patches, and we perform IGA using the same extraction matrices by taking advantage of existing finite element assembly procedures in the FEniCS partial differential equation (PDE) solution library. Moreover, we enable automated analytical derivative computation by leveraging advanced code generation in FEniCS, thereby facilitating efficient gradient-based optimization algorithms. The framework is validated using a collection of benchmark problems, demonstrating its applications to shape and thickness optimization of aircraft wings with complex shell layouts.

Integration of Latex Formula in Computer-Based Test Application for Academic Purposes

LaTeX is a free document preparation system that handles the typesetting of mathematical expressions smoothly and elegantly. It has become the standard format for creating and publishing research articles in mathematics and many scientific fields. Computer-based testing (CBT) has become widespread in recent years. Most establishments now use it to deliver assessments as an alternative to using the pen- paper method. To deliver an assessment, the examiner would first add a new exam or edit an existing exam using a CBT editor. Thus, the implementation of CBT should comprise both support for setting and administering questions. Existing CBT applications used in the academic space lacks the capacity to handle advanced formulas, programming codes, and tables, thereby resorting to converting them into images which takes a lot of time and storage space. In this paper, we discuss how we solvde this problem by integrating latex technology into our CBT applications. This enables seamless manipulation and accurate rendering of tables, programming codes, and equations to increase readability and clarity on both the setting and administering of questions platforms. Furthermore, this implementation has reduced drastically the sizes of system resources allocated to converting tables, codes, and equations to images. Those in mathematics, statistics, computer science, engineering, chemistry, etc. will find this application useful.

Iodine source term assessment under DBA SGTR accident scenario

In the framework of the European project denominated Reduction of Radiological Consequences of design basis and design extension Accidents (R2CA), application of Best Estimate advanced codes for evaluating the radiological release under Design Basis Accident and Design Extended Conditions was considered. The aim is to assess the current modelling capabilities and to propose new calculation methodologies in order to produce more realistic evaluations of radioactive releases resulting from such accidents.In this paper, the studies are conducted for a reference Design Basis Accident Steam Generator Tube Rupture scenario in a 3-loop PWR-1000 reactor in terms of key thermal–hydraulic and radiological variables that condition and characterize the fission product release to the environment. The assessment includes a comparative study of the results performed by three organisations using three different computational tools and approaches. The outcomes highlighted issues considered for the design basis evaluation, modelling differences as well as some challenges and limitations in carrying out such analysis.

Interactions between X-/gamma rays and alloys used in dental braces: A study on theory and simulations

In the field of dentistry, the utilization of dental X-rays plays a pivotal role in ensuring accurate diagnoses for various dental conditions. A crucial aspect of this practice involves understanding how these X-ray emissions interact with dental braces. In the presented study, the details of how X-rays and gamma rays interact with different materials used in dental braces, namely stainless steel, nitinol, elgiloy, and beta-titanium alloys, were examined. This investigation was carried out through a combination of advanced simulation codes such as FLUKA and GEANT4, alongside theoretical calculations using the WinXCOM approach. A comprehensive analysis was conducted at fourteen distinct energy levels, ranging from 20 to 150 keV with 10 keV increments. The primary focus of this study revolves around quantifying the shielding characteristics of gamma and X rays as they traverse through these dental brace materials. To achieve this, some gamma/X-ray shielding parameters, buildup-factors, and kerma relative to air were meticulously simulated and calculated. Additionally, the energy deposits within these materials and the subsequent generation of secondary radiations are thoroughly explored. Significantly, these results highlight that elgiloy alloy demonstrates the highest attenuation of X-ray and gamma ray intensities compared to the other considered materials. This comprehensive study thus offers valuable insights into the behavior of dental braces when subjected to ionizing radiation, with potential implications for patient safety and diagnostic accuracy in dental radiology.