bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Use of Polycarbonate as Dosimeter of High Doses
Authors: Zoul David , Koplová Markéta , Rosnecký Vít , Košťál Michal , Vinš Miroslav , Šimon Jan , Schulc Martin , Cabalka Martin , Kučera Jan , Strunga Vladimír 
Published: January 2021

Abstract
Dosimetry of high doses of ionizing radiation is a method widely used not only in the field of basic and applied research but also in various industries. High-dose irradiation is used in the sterilization of foodstuffs and prolongation of their shelf life, sterilization of tools, materials and wastewater, treatment of antiquities attacked by woodworm organisms, biological and genetic research, inhibition of seed germination, and retardation of fruit ripening. Furthermore, it has been applied in radiation resistance testing of materials, defectoscopy, industrial irradiation of materials (e.g., crosslinking and grafting of polymers or gemstone coloring by ionizing radiation), and last but not least, of course, nuclear energetics. In this work, the dosimetric properties of polycarbonate are studied. They are compared with a standardized and certified method using alanine dosimeters. In the case of gammas, the testing was realized for 60Co and neutron radiation was studied in the light water research nuclear reactor (LVR-15).
Comparison of Corrosion Behavior of the Austenitic Stainless Steel 316 L in Static and Flowing Liquid Lead
Authors: Rozumová Lucia , Košek Lukáš , Vít Jan , Hojná Anna , Halodová Patricie 
Published: January 2021

Abstract
Development of liquid lead cooled nuclear systems requires consideration of compatibility issues with the construction materials. In order to understand the corrosion or passivation behavior of the 316 L austenitic stainless steel, the steel specimens were exposed for 1000 h in liquid lead with 1 × 10−7 wt % oxygen level at 480 °C in static and flowing (velocity 1.6 m/s) conditions. Post-test microscopy investigation using scanning electron microscope with focused ion beam (FIB) was performed and it demonstrated significant differences in the formation of thin oxide layers in the two conditions. Maximum oxide thickness was 2 μm in the static lead (Pb) and less than 0.1 μm in the flowing Pb. In the static condition, oxide scale was not continuous and local corrosion attack was indicated; but in flowing condition the oxide layer was continuous without any corrosion attacks.
Metallic Fast Reactor Separate Effect Studies for Fuel Safety
Authors: Di Lemma Fidelma G. , Jensen Colby B. , Kane Joshua J. , Chen Wei-Ying , Liu Xiang , Capriotti Luca , Adkins Cynthia A. , Kombaiah Boopathy , Winston Alexander J. , He Lingfeng , Wachs Daniel 
Published: January 2021

Abstract
Sodium-cooled Fast Reactors (SFR) are one of the advanced nuclear reactor concepts to be commercially applied for electricity production. The benefits of SFR are well-known and include: the possibility of a closed fuel cycle, proliferation resistance, nuclear waste minimization via actinides burning, and fissile breeding capabilities. Metallic fuel used in SFR has well demonstrated irradiation performance. However, more studies are necessary to optimize and extend operational and safety limits for their commercialization and licensing. This could be achieved through a better understanding of fuel behaviors during transient and of fuel failure thresholds. This paper describes the experimental Research and Development (R&D) program aimed at providing the necessary data to support the development of SFR-optimized safety limits. This program integrates separate effects testing and integral effects testing, combined with advanced Modeling and Simulation (M&S). This R&D program, finally, focuses on delivering the science-based information necessary for supporting the licensing and utilization of SFR based on metallic fuel. In this paper we will describe the three research areas centered on fuel development and focused on separate effect testing, namely: (1) microstructural, chemistry, and material properties; (2) thermo-mechanical behavior; and (3) source term and fission product behavior. Preliminary results from these Separate Effect Tests (SET) studies and the current instruments and experimental plan are also presented.
Developing and Implementing Artificial Intelligence-Based Classifier for Requirements Engineering
Authors: Myllynen Santeri , Suominen Ilpo , Raunio Tapani , Karell Rasmus , Lahtinen Jussi 
Published: January 2021

Abstract
In nuclear power plant (NPP) projects, requirements engineering manages the sheer volume of requirements, typically characterized by descriptive and nonharmonized requirements. Large projects may have tens of thousands to hundreds of thousands of requirements to be managed and fulfilled. Two main issues impede requirements analysis: tortuous requirements to be interpreted; and humans' very limited ability to concentrate on a specific task. It has therefore been recognized that artificial intelligence (AI) algorithms have the potential to support designers' decision making in classifying and allocating NPP requirements into predefined classes. This paper presents our work on developing an AI-based requirements classifier utilizing natural language processing (NLP) and supervised machine-learning (ML). In addition, the paper presents the integration of the classifier with the requirements management system. The focus is on the classification of nuclear power industry-specific requirements utilizing deep-learning-based NLP. Three classifiers are compared, and the corresponding results are presented. The results include predetermined requirement classes, manually gathered and classified data, a comparison of three models and their classification accuracies, microservice system architecture, and integration of the established classifier with the requirements management system. As the performance of the requirements classifier and related system has been successfully demonstrated, future AI-specific development and studies are suggested to focus on atomizing multiclass requirements, combining similar requirements into one, checking requirements syntax, and utilizing unsupervised learning for clustering. Furthermore, new and advantageous requirement classes and hierarchies are suggested for development while improving current datasets both quantitatively and qualitatively.
Neutron Field Shaping Using Graphite for Reaction Rate Measurements
Authors: Sobaleu Mikita , Košťál Michal , Šimon Jan , Losa Evžen 
Published: January 2021

Abstract
Neutron field shaping is the suitable method for validation of cross section in various energy regions. By increasing the share of neutrons of a certain energy interval and decreasing the share of other, a reaction becomes more sensitive to selected neutrons. As a result, reaction cross section can be validated in selected energy regions more precisely. The shaping can be carried out by both neutron filters which are materials with high absorption in some energy region, or by diffusion material changing the shape of neutron spectra by means of slowing down process. In the presented experiments, the neutron field of the light reactor 0 (LR-0) research reactor was shaped by both using graphite blocks inserted into the core and Cd cladding for increasing the epithermal reaction rate share in total reaction rates. The calculations were carried out with the Monte Carlo N-Particle Transport Code 6 (MCNP6) code and the most recent nuclear data libraries. The results in the pure graphite neutron field are in good agreement; in case of Cd cladding, significant discrepancies were reported. In case of the 23Na(n,γ)24Na reaction, overestimation by about 14% was reached in International Reactor Dosimetry and Fusion File (IRDFF-II), results in other libraries are comparable. In case of 58Fe(n,γ)59Fe, the overestimation as high as 18% is reported in IRDFF-II. For 64Zn(n,γ)65Zn reasonable agreement was reached in evaluated nuclear data file (ENDF/B-VIII), where discrepancies in pure graphite neutron field or in case of Cd cladding are about 10–15%.
Build Up and Characterization of Ultraslow Nuclear Burn-Up Wave in Epithermal Neutron Multiplying Medium
Authors: Ray D. , Saraswat S. P. , Kumar M. , Singh O. P. , Munshi P. 
Published: January 2021

Abstract
A study is carried out on the build-up and characterization of ultraslow nuclear burn-up wave in epithermal neutron multiplying medium for slab geometry. Uranium-plutonium fissile medium is considered for the calculation. Transient part of the wave is characterized by transient time (TT), transient length (TL), and TT and TL are defined as the time and distance required to develop asymptotic neutron flux propagating through the media. Steady-state part of the wave is characterized with wave velocity and reaction zone width (full width half maximum (FWHM) and full width 10% of maximum (FW10M)). Parametric studies are carried out for different enrichment of 235U and different values of external source of neutron. It is observed that TT, TL, FWHM, and FW10M decrease with the increase in enrichment. The velocity of the wave increases with the enrichment of 235U. This study is beneficial for understanding the characteristics of nuclear burn-up wave in epithermal region as it will help in further researches in this area.
Actinide in Air (Rn-Progeny Rejected) Alpha Spectroscopy With Tensioned Metastable Fluid Detectors
Authors: Hemesath M. , Boyle N. , Archambault B. , Troy Lorier C. , DiPrete D. , Taleyarkhan R. P. 
Published: January 2021

Abstract
This article discusses outcome of research for deriving a methodology and apparatus for ascertaining for the presence of ultratrace-level actinides in air from their alpha emission signatures, while remaining blind to the relatively large (1000× higher activity) alpha emissions from Rn-progeny. Apparatus and techniques were developed to collect and characterize alpha-emitting nuclides of Rn-progeny and actinides in air on a polycarbonate 3 μm pore size continuous air monitor (CAM) filter. A wet-chemistry approach was developed and validated for successfully separating the Rn-progeny alpha emitting isotopes of Po-214 and Po-218, while extracting the actinides (U, Pu, Am) in a fluid mixture that is suitable for conduct of alpha spectroscopy with a centrifugally tensioned metastable fluid detector (CTMFD). The resulting α-TMFD technology was compared against the state-of-art “Alpha-Sentry™” Continuous Air Monitor (CAM) system commonly utilized world-wide. Results indicate that the α-TMFD technology can potentially offer complementary and superior performance in multiple performance categories, and ∼18× improvement in the time to detect (e.g., at 0.02 derived air concentration (DAC) within ∼3 h, versus ∼70 h for Alpha-Sentry) for actinides of interest while also remaining ∼100% blind to ∼103× higher Rn-progeny background—with the added potential for offering few keV scale energy resolution without resorting to peak shape fitting, versus ∼300–400 keV for existing CAM systems.
Online Spark Timing Optimization With Complex High-Fidelity Combustion Phasing, Knock, and Coefficient of Variation of IMEP Models
Authors: Zhu Qilun , Prucka Robert , Wang Shu , Prucka Michael 
Published: January 2021

Abstract
The combustion phasing of spark ignition (SI) engines is traditionally regulated with map-based spark timing (SPKT) control. The calibration of these maps is time-consuming for SI engines with a high number of control actuators. This paper proposes three online SPKT optimization algorithms that can utilize control-oriented semiphysics-based combustion models making the SPKT control algorithm more adaptive to different engine designs. These three SPKT optimizers do not require model inversion and derivative information. These methods also preserve the dependence between combustion phasing, knock, and coefficient of variation (COV) of indicated mean effective pressure (IMEP) models to avoid evaluating combustion models multiple times within one iteration. The two-phase and constraint relaxation methods are derived from direct search optimization theories. The recursive least square (RLS) polynomial fitting method can be considered as a virtual extreme seeking (ES) process that converts the original “black” box nonlinear constrained optimization into the solution of three low-order polynomial equations. Although these three online SPKT optimization approaches have unique properties making them preferable with certain types of combustion models, simulation and test results show that all of them can find the optimal SPKT with less than 10 evaluations of the combustion models. This fact makes it possible to implement the proposed model-based SPKT control strategy in future engine control units (ECUs).
Novel Integrated Active and Passive Control of Fluid-Borne Noise in Hydraulic Systems
Authors: Pan Min , Yuan Chenggang , Ding Beichen , Plummer Andrew 
Published: January 2021

Abstract
Fluid-borne noise (FBN) is a major contributor to structure-borne noise (SBN) and air-borne noise (ABN) in hydraulic fluid power systems and could lead to increased fatigue in system components. FBN is caused by the unsteady flow generated by pumps and motors and propagates through the system resulting in SBN and ABN. New hydraulic technologies such as digital switched hydraulic converters are also barriered by the unavoidable FBN. This article reports on a novel integrated FBN attenuation approach, which employs a hybrid control system by integrating an active feedforward noise attenuator with passive tuned flexible hoses. The active system which consists of adaptive notch filters using a variable step-size filtered-X Least Mean Squares algorithm is used to control a newly designed high-force high-bandwidth piezo-electric actuator in order to attenuate the dominant narrowband pressure ripples. The passive hose is tuned in the frequency domain and used to cancel the high-frequency pressure ripples. A time-domain hose model considering coupling of longitudinal wall and fluid waves was used to model the flexible hose in the integrated control system. Very good FBN cancelation was achieved by using the proposed integrated control approach both in simulation and experiments. It can be concluded that the active attenuator with passive flexible hoses can form an effective, cost-efficient and practical solution for FBN attenuation. The problem of high noise levels generated by hydraulically powered machines has risen significantly in awareness within industry and amongst the general public, and this work constitutes an important contribution to the sustainable development of low noise hydraulic fluid power machines.
Gas Supply Reliability Analysis of a Natural Gas Pipeline System Considering the Effects of Demand Side Management
Authors: Li Yichen , Gong Jing , Yu Weichao , Huang Weihe , Wen Kai 
Published: January 2021

Abstract
At present, China has a developing natural gas market, and ensuring the security of gas supply is an issue of high concern. Gas supply reliability, the natural gas pipeline system's ability to satisfy the market demand, is determined by both supply side and demand side and is usually adopted by the researches to measure the security of gas supply. In the previous study, the demand side is usually simplified by using load duration curve (LDC) to describe the demand, which neglects the effect of demand side management. The simplification leads to the inaccurate and unreasonable assessment of the gas supply reliability, especially in high-demand situation. To overcome this deficiency and achieve a more reasonable result of gas supply reliability, this paper extends the previous study on demand side by proposing a novel method of management on natural gas demand side, and the effects of demand side management on gas supply reliability is analyzed. The management includes natural gas prediction models for different types of users, the user classification rule, and the demand adjustment model based on user classification. First, an autoregressive integrated moving average (ARIMA) model and a support vector machine (SVM) model are applied to predict the natural gas demand for different types of users, such as urban gas distributor (including residential customer, commercial customer, small industrial customer), power plant, large industrial customer, and compressed natural gas (CNG) station. Then, the user classification rule is built based on users' attribute and impact of supplied gas's interruption or reduction. Natural gas users are classified into four levels. (1) demand fully satisfied, (2) demand slightly reduced, (3) demand reduced, and (4) demand interrupted. The user classification rule also provides the demand reduction range of different users. Moreover, the optimization model of demand adjustment is built, and the objective of the model is to maximize the amount of gas supplied to each user based on the classification rule. The constraints of the model are determined by the classification rule, including the demand reduction range of different users. Finally, the improved method of gas supply reliability assessment is developed and is applied to the case study of our previous study derived from a realistic natural gas pipeline system operated by PetroChina to analyze the effects of demand side management on natural gas pipeline system's gas supply reliability.
Correlation of Computational Instantaneous Wave-Free Ratio With Fractional Flow Reserve for Intermediate Multivessel Coronary Disease
Authors: Ghorbanniahassankiadeh Arash , Marks David S. , LaDisa John F. 
Published: January 2021

AbstractThis study computationally assesses the accuracy of an instantaneous wave-free ratio (iFR) threshold range compared to standard modalities such as fractional flow reserve (FFR) and coronary flow reserve (CFR) for multiple intermediate lesions near the left main (LM) coronary bifurcation. iFR is an adenosine-independent index encouraged for assessment of coronary artery disease (CAD), but different thresholds are debated. This becomes particularly challenging in cases of multivessel disease when sensitivity to downstream lesions is unclear. Idealized LM coronary arteries with 34 different intermediate stenoses were created and categorized (Medina) as single and multiple lesion groups. Computational fluid dynamics modeling was performed with physiologic boundary conditions using an open-source software (simvascular1) to solve the time-dependent Navier–Stokes equations. A strong linear relationship between iFR and FFR was observed among studied models, indicating computational iFR values of 0.92 and 0.93 are statistically equivalent to an FFR of 0.80 in single and multiple lesion groups, respectively. At the clinical FFR value (i.e., 0.8), a triple-lesion group had smaller CFR compared to the single and double lesion groups (e.g., triple = 3.077 versus single = 3.133 and double = 3.132). In general, the effect of additional intermediate downstream lesions (minimum lumen area &gt; 3 mm2) was not statistically significant for iFR and CFR. A computational iFR of 0.92 best predicts an FFR of 0.80 and may be recommended as threshold criteria for computational assessment of LM stenosis following additional validation using patient-specific models.
Effects of External Load on Sagittal and Frontal Plane Lower Extremity Biomechanics During Back Squats
Authors: Maddox Eva U. , Bennett Hunter J. 
Published: January 2021

Abstract
Previous literature suggests the sticking region, the transition period between an early peak concentric velocity to a local minimum, in barbell movements may be the reason for failing repeated submaximal and maximal squats. This study determined the effects of load on lower extremity biomechanics during back squats. Twenty participants performed the NSCA's one-repetition-maximum (1RM) testing protocol, testing to supramaximum loads (failure). After completing the protocol and a 10-min rest, 80% 1RM squats were performed. Statistical parametric mapping (SPM) was used to determine vertical velocity, acceleration, ankle, knee, and hip sagittal and frontal plane biomechanics differences between 1RM, submaximum, and supramaximum squats (105% 1RM). Vertical acceleration was a better discriminative measure than velocity, exhibiting differences across all conditions. Supramaximum squats emphasized knee moments, whereas 1RM emphasized hip moments during acceleration. Submaximum squats had reduced hip and knee moments compared to supramaximum squats, but similar knee moments to 1RM squats. Across all conditions, knee loads mirrored accelerations and a prominent knee (acceleration) to hip (sticking) transition existed. These results indicate that (1) submaximum squats performed at increased velocities can provide similar moments at the ankle and knee, but not hip, as maximal loads and (2) significant emphasis on hip strength is necessary for heavy back squats.
Total Least-Squares Determination of Body Segment Attitude
Authors: Challis John H. 
Published: January 2021

Abstract
To examine segment and joint attitudes when using image-based motion capture, it is necessary to determine the rigid body transformation parameters from an inertial reference frame to a reference frame fixed in a body segment. Determine the rigid body transformation parameters must account for errors in the coordinates measured in both reference frames, a total least-squares problem. This study presents a new derivation that shows that a singular value decomposition-based method provides a total least-squares estimate of rigid body transformation parameters. The total least-squares method was compared with an algebraic method for determining rigid body attitude (TRIAD method). Two cases were examined: case 1 where the positions of a marker cluster contained noise after the transformation, and case 2 where the positions of a marker cluster contained noise both before and after the transformation. The white noise added to position data had a standard deviation from zero to 0.002 m, with 101 noise levels examined. For each noise level, 10 000 criterion attitude matrices were generated. Errors in estimating rigid body attitude were quantified by computing the angle, error angle, required to align the estimated rigid body attitude with the actual rigid body attitude. For both methods and cases, as the noise level increased the error angle increased, with errors larger for case 2 compared with case 1. The singular value decomposition (SVD)-based method was superior to the TRIAD algorithm for all noise levels and both cases, and provided a total least-squares estimate of body attitude.