bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Catalysts Addition to Silicone Rubber as Pressure Transmitting Medium in the Pebble Fuel Production Process
Authors: Sutarya D , Pamungkas I R , Sukma H , A Sartono DS 
Published: October 2021

Abstract
Pebble Fuel is a spherical fuel for high temperature gas-cooled reactors (HTGR). This fuel must have a homogeneous density distribution. Hyperelastic material is used as a pressure transmitting medium (PTM) material in making Pebble fuel using the cold quasi-isostatic pressing method. PTM material properties and characteristics were predicted using the finite element analysis method. The problem is the type of material used and its suitable composition to make a pressure-transmitting medium that has the properties and characteristics of the material as predicted. This research discusses the manufacture of tensile specimens for pressure-emitting media using RTV-586 silicone rubber. The composition comprises three different variants with two major ingredients, namely RTV-586 silicone rubber and catalyst. The test results are then analyzed using the finite element method to determine the material composition that is appropriate or close to the predicted properties and characteristics of the PTM material. This initial study used the Mooney-Rivlin hyperelastic model. The Mooney-Rivlin model shows good similarity to the test result data. In future studies, it will make comparisons with other hyperelastic models to get a suitable PTM material constant.
Evaluation of PBMR-400 Core Design Steady State Condition with Serpent and AGREE
Authors: Ardiansyah H , Seker V , Downar T , Skutnik S , Wieselquist W 
Published: October 2021

Abstract
The significant recent advances in computer speed and memory have made possible an increasing fidelity and accuracy in reactor core simulation with minimal increase in the computational burden. This has been important for modeling some of the smaller advanced reactor designs for which simplified approximations such as few groups homogenized diffusion theory are not as accurate as they were for large light water reactor cores. For narrow cylindrical cores with large surface to volume ratios such the Ped Bed Modular Reactor (PBMR), neutron leakage from the core can be significant, particularly with the harder neutron spectrum and longer mean free path than a light water reactor. In this paper the core from the OECD PBMR-400 benchmark was analyzed using multigroup Monte Carlo cross sections in the HTR reactor core simulation code AGREE. Homogenized cross sections were generated for each of the discrete regions of the AGREE model using a full core SERPENT Monte Carlo model. The cross sections were generated for a variety of group structures in AGREE to assess the importance of finer group discretization on the accuracy of the core eigenvalue and flux predictions compared to the SERPENT full core Monte Carlo solution. A significant increase in the accuracy was observed by increasing the number of energy groups, with as much as a 530 pcm improvement in the eigenvalue calculation when increasing the number of energy groups from 2 to 14. Significant improvements were also observed in the AGREE neutron flux distributions compared to the SERPENT full core calculation.
Developing a Design Optimization Methodology for the Thermal-Hydraulic Evaluation for a High Temperature Reactor During a DLOCA
Authors: Atkinson Seddon , Gray Ander , Patelli Edoardo 
Published: October 2021

Abstract
Methods of implementing uncertainty within nuclear reactor modelling have traditionally been achieved via worst case scenario uncertainty quantification. This article investigates how this practice can be expanded to provide data on the driving factors behind the temperatures experienced during accident conditions via a global sensitivity analysis. The second part of the article investigates how a stochastic optimization technique can be included within the design process to provide the most cost-effective core geometry which meets the temperature constraints of the fuel and the reactor pressure vessel. The third study investigates the impact of how uncertainty reduction can be used in combination with the stochastic optimization technique to provide further design optimization.
Design of Fault Diagnosis Algorithm for Electromechanical System Based on Artificial Intelligence
Authors: Zhao Fuyou , Huo Mingying , Qi Naiming , Li Lianfeng , Cui Weiwei 
Published: October 2021

Abstract
A relatively perfect system for the fault diagnosis of mechanical and electrical products has been formed through decades of development. Nevertheless, the traditional fault diagnosis methods fail to cope with the gradual huge mechanical and electrical system. As a result, the advantages of fault diagnosis mode driven by data are increasingly prominent. Meanwhile, the effect of fault diagnosis has exceeded the traditional fault diagnosis methods in many fields. Through the use of the deep learning technology based on artificial intelligence, it carries out mapping and fitting. By fully taking advantages of neural network, it can effectively obtain the accurate classification of fault data. A fault diagnosis method based on the fault data of mechanical and electrical system is designed in this thesis. When it comes to the basic process, it is to take data sets for different mechanical and electrical products. Through the use of feature engineering method, it extracts the fault features of data. Through the use of deep learning technology, it carries out the intelligent diagnosis. According to the experimental results, it indicates that the fault diagnosis method based on deep learning technology can distinguish a variety of fault modes in mechanical and electrical system in an effective way. What’s more, good classification results in fault recognition have been achieved by a variety of deep convolutional neural network structures, so the feasibility of the method is further verified.
Passive design of buildings: A review of configuration features for natural ventilation and daylighting
Authors: Loo S-H , Lim P I , Lim B H 
Published: October 2021

Abstract
Passive design involves the utilization of natural forces such as natural ventilation and daylighting without mechanical input of energy, and is a subset of environmentally sustainable design (ESD), which offers solutions for more environmentally friendly buildings. This review is based on the premise that ESD interventions have an inherent cost on building projects. The aim is to review existing research on applications of various building configurations for facilitating the economical application of passive design, in terms of natural ventilation and daylighting. A systematic review of existing research during the previous decade (2010 – 2020) was conducted. In our findings, we compare and categorise concepts within building configuration in terms of their applicability to natural ventilation and daylighting. Our review identified seven categories of building configuration ie. building geometry, interior, context, envelope, fenestration, building plan and voids, with their associated parameters. It was discovered that building fenestration was the most frequently researched followed by building voids. The identified parameters point to the variety, diversity and trends of research in the field. The knowledge can be used in familiarising, assessing and evaluating various aspects of passive design of building configuration towards energy saving and ESD.
Stochastic type-2 fuzzy modelling on GHG emission prediction for gas-fired power plant
Authors: Zakaria Sazalina , R. Ahmad Radin Diana , Abbas Ahmad Rosly , Mohideen Batcha Mohd Faizal , Zanil Mohd Fauzi 
Published: October 2021

Abstract
This paper demonstrates the implementation of type-2 fuzzy logic model in prediction of greenhouse gas emission for gas fuelled power plant. The data collection and analysis on the GHG emission had been conducted with emphasis on the industrial scale with many uncertainty factors. The developed model will be used as a prediction tools to evaluate potential GHG emission for future study and mitigation planning. In this work, 100 sample sizes had been used as training dataset in the model framework which serve as the input information while 14 sample sizes are used for model validation to achieve model generalization. A novel Karnik-Mendel (KM) algorithm had been proposed with the Genetic Algorithm (GA) model optimization to achieve high performance and accuracy for the respective predictive model. In conclusion, the result showed that the model able to give an outstanding accuracy. On the validation analysis, the results showed developed model able to give satisfactory prediction with R2 of 0.978 and 0.84968 for training and validation, respectively.
Numerical studies of fluid flow and heat transfer in microchannel heat sink with trapezoidal cavities, ribs and secondary channel
Authors: Razali S A , Sidik N A C , Yusof S N A 
Published: October 2021

AbstractIn order to improve reliability and prevent premature failure, heat produced by electronic devices must be transfer efficiently. The microchannel heat sink appears to be the most reliable cooling technology to improve heat transfer performance. A new Microchannel Heat Sink (MCHS) design has been proposed with trapezoidal cavities, ribs and secondary channels. Fluid flow and heat transfer characteristics for Reynold numbers from 100 to 500 are numerically studied and analysed. Four microchannel heat sinks with various related geometry have been considered in this study, for instance, microchannel with rectangular ribs (TRAC-RR) and microchannel with trapezoidal cavities (TRAC). The finite volume method (FVM) is used to solve the governing equations, and the computations are performed using the SIMPLE algorithm. The present design’s overall performance is evaluated using the friction factor, the Nusselt number, and performance evaluation criteria (PEC). The results show that the TRAC-RR-SC MCHS is the best design for the proposed design compared to the other four geometries, with a maximum PEC of 1.78. Additionally, the secondary flow field analyses visually show the hydraulic and thermal performance enhancements due to interruption, flow mixing and redevelopment of the thermal boundary layer.
Nitrogen Gas Adsorption Filter (NgAF) to enhance producer gas quality
Authors: Mohammud Mohd Mahadzir , Mohd Fohimi Nor Azirah , Hamid Pahmi Muhammad Arif Ab , Hairun Anuar Ariffatul Amirah 
Published: October 2021

Abstract
Biomass gasification is a thermochemical conversion process of solid biomass into a gaseous fuel called producer gas that can be used to generate power and electricity. The producer gas consists of around 47% of Nitrogen (N2), 24% Carbon Monoxide (CO), 16% Carbon Dioxide (CO2), 12% Hydrogen (H2), and 1% Methane (CH4). However, Nitrogen (N2) content in the producer gas reduces its heating values as N2 acts as a diluent because of the low calorific value (LCV) of gas. This study aims to design a Nitrogen gas filter for capturing nitrogen gas from producer gas to increase the heating value of producer gas as fuel in combustion. The method to increase the heating value of producer gas will increase the number of combustible gases or reduce the composition of non-combustible gases in producer gas. The use of material name zeolite with its microporous structures able to adsorb nitrogen molecules and act as catalysts to chemical reactions. Zeolites 5A have a small pore highly efficient to adsorb nitrogen gas because pore diameter is relatively similar to the size of nitrogen molecules. The quality of the producer gas depends on the design and operating parameters of the zeolite catalyst. Nitrogen Gas Adsorption Filter is a new method that has to be designed to improve the previous producer gas quality. Nitrogen Gas Adsorption Filter consists of a cylindrical shape body packed with crushed zeolites 5A. When this method of adsorption process is applied, the heating value of the producer gas is increased by observing the quantity of blue flame colour produced by NgAF.
Structural, thermal and optical studies of Eu3+ ion doped Ge22As20Se58 glass
Authors: Singh Amarendra Kumar , Mehta Neeraj , Mishra Hirdeysh , Mishra S K 
Published: October 2021

Abstract
The effect of Eu3+ doping on improving the amorphous nature of commercial chalcogenide glass/ChG (Ge22As20Se58), which is typically used as a molded lens for mid-infrared imaging, has been investigated. The observed absence of bright spots in Transmission Electron Microscope-Selected area (electron) diffraction (TEM-SAED) pattern confirmed the doping-induced amorphous nature of Eu-Ge22As20Se58 glass. The thermal studies over glass transition temperature (Tg) using DSC technique also revealed that Eu doping has increased the amorphous nature along with the thermal stability of Ge22As20Se58 glass. The optical analysis using UV–vis absorption spectroscopy showed that the activity of Eu-doped ChG has been extended across the UV-visible region. Tauc plot derived band gap energy of Eu-doped and undoped ChG is found to be 2.2 and 2.6 eV, respectively.
Hot filament chemical vapor deposition temperature field optimization for diamond films deposited on silicon nitride substrates
Authors: Wu Yuhou , Zhang Huisen , Yan Guangyu , Liu Lusheng , Cristea Daniel , Wang He , Yang Yumiao , Shen Jianhui 
Published: October 2021

Abstract
The influence of some key parameters of hot filament chemical vapor deposition (HFCVD) on the temperature distribution during the deposition of diamond coatings on silicon nitride (Si3N4) substrates was assessed with the help of the finite element method. Solid heat transfer, fluid heat transfer and surface radiation heat transfer mechanisms were used to calculate the substrate temperature in the steady state during the deposition process. The accuracy of the model was verified by comparing the simulation model with experimental measurements. The comparison shows that the deviation between the model and the actual substrate temperature measurements is within 3%. Furthermore, a Taguchi orthogonal experiment was designed (3 factors, 3 levels, L9). By changing the number of hot filaments, the distance between the filaments and the substrate, and the separation between two adjacent hot filaments, the influence trend of these parameters on the substrate temperature was assessed, leading to an optimal hot filament arrangement. A deposition experiment was carried out using the optimized parameters, and the results showed that the substrate surface temperature obtained by numerical simulation is highly consistent with the temperature measured by the infrared thermometer. The optimized deposition parameters contributed to a more suitable temperature range and more uniform temperature distribution on the Si3N4 ceramic substrate. The deposited diamond film exhibited uniform crystal quality and grain morphology, thus verifying the validity of the simulation results.
Effect of laser power and scanning speed on the characteristics of laser metal deposition of Ti6Al4V + W composite powder on Ti6Al4V substrate
Authors: Ndou Ndivhuwo , Mubiayi Mukuna Patrick 
Published: October 2021

Abstract
The usage of different powders to enhance the surface properties of base materials has an impact on the cost. Laser Metal Deposition (LMD) of Ti6Al4V + W composite was used and the effect of laser power and scanning speed was investigated. The microstructure, microhardness, and x-ray diffraction analyses, and wear tests were conducted. The microstructure of the samples fabricated using higher laser power (1400W) displayed larger grains when compared to the ones fabricated using lower laser power (800 W). The Full Width at Half Maximum (FWHM) values showed some changes with the variation of scanning speeds. Furthermore, the x-ray diffraction patterns did not show the formation of new phases. A similar trend on the microhardness profiles for all the fabricated samples was observed. Higher microhardness values were observed in the top part of the deposited material. The microhardness profile showed similar trends for all the analysed samples. Higher microhardness values were measured at the top of deposition and decreased progressively. On the other hand, the scanning speed did not affect the wear volume, though the highest wear volume of 0.144 mm was observed for the sample fabricated using 800 W laser power and 0.7 m min−1. This shows that process parameters such as laser power and scanning have an impact on the resulting properties of deposited composite material.
A review of printable, flexible and tissue equivalent materials for ionizing radiation detection
Authors: Posar Jessie A , Petasecca Marco , Griffith Matthew J 
Published: October 2021

Abstract
Advances in flexible and printable electronics have paved the way for large-area, and low-cost wearable electronics that will revolutionize the way we detect and monitor ionizing radiation. The improvements to early detection and widespread use of treatment procedures of tumors and other illnesses using ionizing radiation have led to the rapid increase in the yearly dose exposure to the public. Therefore, safety organizations must introduce stricter quality assurance measures to ensure the safe delivery of the total dose to the patient—only achievable using live monitoring systems, named in-vivo dosimetry. Such systems would also benefit the safety of professional personnel employed in areas that encounter higher exposures of ionizing radiation including nuclear plants, space exploration, flight staff, and research beamline facilities. However, the current real-time detectors employ expensive and rigid high-Z materials including silicon, germanium, and cadmium telluride, that suffer substantial limitations in monitoring the dose deposited in biological tissue and conforming to the complex contours of the human body over large areas. We provide insights into the innovative materials capable of solution-based device fabrication onto flexible substrates with foreseeable avenues towards low-cost large-area printing techniques. This discussion will also review and identify the advantages and existing capabilities of tissue-equivalent materials in the detection of ionizing radiation as the ideal materials for in-vivo dosimetry. Finally, the radiation tolerance of organic materials is outlined to demonstrate that extensive investigations are still required before their utilization as radiation detectors.
Markov modelling of treatment response in a 30-year cohort study of newly diagnosed epilepsy
Authors: Simpson Hugh D , Foster Emma , Ademi Zanfina , Lawn Nicholas , Brodie Martin J , Chen Zhibin , Kwan Patrick 
Published: October 2021

Abstract
People with epilepsy have variable and dynamic trajectories in response to antiseizure medications. Accurately modelling long-term treatment response will aid prognostication at the individual level and health resource planning at the societal level. Unfortunately, a robust model is lacking. We aimed to develop a Markov model to predict the probability of future seizure-freedom based on current seizure state and number of antiseizure medication regimens trialled.
We included 1795 people with newly diagnosed epilepsy who attended a specialist clinic in Glasgow, Scotland, between July 1982 and October 2012. They were followed up until October 2014 or death. We developed a simple Markov model, based on current seizure state only, and a more detailed model, based on both current seizure state and number of antiseizure medication regimens trialled. Sensitivity analyses were performed for the regimen-based states model to examine the effect of regimen changes due to adverse effects. The model was externally validated in a separate cohort of 455 newly diagnosis epilepsy patients seen in Perth, Australia, between May 1999 and May 2016.
Our models suggested that once seizure-freedom was achieved, it was likely to persist, regardless of the number of antiseizure medications trialled to reach that point. The likelihood of achieving long-term seizure-freedom was highest with the first antiseizure medication regimen, at approximately 50%. The chance of achieving seizure-freedom fell with subsequent regimens. Fluctuations between seizure-free and not seizure-free states were highest earlier on but decreased with chronicity of epilepsy. Seizure-freedom/recurrence risk tables were constructed with these probability data, similar to cardiovascular risk tables. Sensitivity analyses showed that the general trends and conclusions from the base model were maintained despite perturbing the model and input data with regimen changes due to adverse effects. Quantitative comparison with the external validation cohort showed excellent consistency at Year 1, good at Year 3 and moderate at Year 5.
Quantitative models, as used in this study, can provide pertinent clinical insights that are not apparent from simple statistical analysis alone. Attaining seizure freedom at any time in a patient’s epilepsy journey will confer durable benefit. Seizure-freedom risk tables may be used to individualize the prediction of future seizure control trajectory.
Studies on pathways to carbon neutrality for indirect coal liquefaction in China
Authors: Li Chufu , Li Yonglong , Xu Ming , Gong Yan , Gong Siqi , Wang Peng , Li Pingping , Dong Binqi , Men Zhuowu 
Published: October 2021

Abstract
The production capacity of indirect coal liquefaction (ICL) in use in China has reached a level of 8 million t/a, which corresponds to a carbon footprint of &gt;60 million t/a. ICL is facing mountainous pressure to reduce its carbon emissions when its development is planned with carbon neutrality as a background objective. This paper studies the pathways that can lead to carbon neutrality for ICL in China, constructing four carbon-neutral pathways for ICL systems with the introduction of green hydrogen, biomass as feedstock and with CCS (carbon capture and storage), which can reduce significant carbon emissions from coal-gasification and water–gas shift processes. The carbon-neutral biomass is used to replace some coal as co-feed to gasification and combustion, leading to reduced carbon emissions as well. Calculations and economic analyses are performed on different carbon-reduction pathways using a carbon-neutral ICL system on a 1 million t/a scale as an example. The results are that the pathway of direct coal substitution with biomass is the lowest carbon-reduction route at RMB 31~125/t CO2, substitution with green hydrogen costs the highest at RMB 84~422/t CO2 and CCS costs are in the middle at RMB 96~148/t CO2. Each pathway has its pros and cons, and a combination of the three may be used for the best outcome. Furthermore, a comprehensive study and systematic summation of the critical technological processes and their underlying challenges for carbon-neutral ICL together with direction for a technological breakthrough are presented. These ICL carbon-reduction pathways presented in this paper are capable of realizing an integrated development between fossil and renewable energy sources, helping the carbon-intense coal-chemical industries to achieve their goals of carbon peak and carbon neutrality.