Gamma-Ray Induced Photoconductivity in Pyrex, Quartz, and Vycor

Results of an experimental investigation are reported on photoconductive response of Pyrex, Quartz and Vycor. This research was conducted as a feasibility study for developing a new gamma dose measurement device based on the principle of photoconductivity. However, data collected in this study are equally valuable for various other applications where these materials are to be used in high radiation field. Our experiments and analyzes indicated that the selected dosimeter materials exhibit photoconductivity and respond to changes in gamma dose rate within a useful range. Pyrex glass suffered radiation damage at a relatively high dose rate of 0.25 Gys/sup -1/. Quartz and Vycor exhibit significant advantages over Pyrex as dosimeter material. However, their limit of operability was found to be at a dose rate of approximately 28 mGy s/sup -1/. Vycor dosimeter in particular appears promising for gamma measurement applications. From an endurance point of view, Quartz appears to be the most suitable material for applications in high dose rate conditions, in that photo-currents in Quartz were observed to be minimum

Delayed Fast Neutron as an Indicator of Burn-Up for Nuclear Fuel Elements

Feasibility study of burn-up analysis and monitoring using delayed fast neutrons was investigated at Missouri University of Science and Technology Reactor (MSTR). Burnt and fresh fuel elements were used to collect delayed fast neutron data for different power levels. Total reactivity varied depending on the burn-up rate of fuel elements for each core configuration. The regulating rod worth was 2.07E-04 Δk/k/in and 1.95E-04 Δk/k/in for T121 and T122 core configurations at 11 inch, respectively. Delayed fast neutron spectrum of F1 (burnt) and F16 (fresh) fuel elements were analyzed further, and a strong correlation was observed between delayed fast neutron emission and burn-up. According to the analyzed peaks in burnt and fresh fuels, reactor power dependency was observed and it was determined that delayed neutron provided more reliable results at reactor powers of 50 kW and above

Harnessing the Potential of Blockchain in DevOps: A Framework for Distributed Integration and Development

As the use of DevOps practices continues to grow, organizations are seeking ways to improve collaboration, speed up development cycles, and increase security, transparency, and traceability. Blockchain technology has the potential to support these goals by providing a secure, decentralized platform for distributed integration and development. In this paper, we propose a framework for distributed DevOps that utilizes the benefits of blockchain technology that can eliminate the shortcomings of DevOps. We demonstrate the feasibility and potential benefits of the proposed framework that involves developing and deploying applications in a distributed environment. We present a benchmark result demonstrating the effectiveness of our framework in a real-world scenario, highlighting its ability to improve collaboration, reduce costs, and enhance the security of the DevOps pipeline. Conclusively, our research contributes to the growing body of literature on the intersection of blockchain and DevOps, providing a practical framework for organizations looking to leverage blockchain technology to improve their development processes.Comment: pages 10, figures

Recent Advances in Uncertainty Quantification Methods for Engineering Problems

In the last few decades, uncertainty quantification (UQ) methods have been used widely to ensure the robustness of engineering designs. This chapter aims to detail recent advances in popular uncertainty quantification methods used in engineering applications. This chapter describes the two most popular meta-modeling methods for uncertainty quantification suitable for engineering applications (Polynomial Chaos Method and Gaussian Process). Further, the UQ methods are applied to an engineering test problem under multiple uncertainties. The test problem considered here is a supersonic nozzle under operational uncertainties. For the deterministic solution, an open-source computational fluid dynamics (CFD) solver SU2 is used. The UQ methods are developed in Matlab and are further combined with SU2 for the uncertainty and sensitivity estimates. The results are presented in terms of the mean and standard deviation of the output quantities

Surrogate Modeling-Driven Physics-Informed Multi-fidelity Kriging: Path Forward to Digital Twin Enabling Simulation for Accident Tolerant Fuel

The Gaussian Process (GP)-based surrogate model has the inherent capability of capturing the anomaly arising from limited data, lack of data, missing data, and data inconsistencies (noisy/erroneous data) present in the modeling and simulation component of the digital twin framework, specifically for the accident tolerant fuel (ATF) concepts. However, GP will not be very accurate when we have limited high-fidelity (experimental) data. In addition, it is challenging to apply higher dimensional functions (>20-dimensional function) to approximate predictions with the GP. Furthermore, noisy data or data containing erroneous observations and outliers are major challenges for advanced ATF concepts. Also, the governing differential equation is empirical for longer-term ATF candidates, and data availability is an issue. Physics-informed multi-fidelity Kriging (MFK) can be useful for identifying and predicting the required material properties. MFK is particularly useful with low-fidelity physics (approximating physics) and limited high-fidelity data - which is the case for ATF candidates since there is limited data availability. This chapter explores the method and presents its application to experimental thermal conductivity measurement data for ATF. The MFK method showed its significance for a small number of data that could not be modeled by the conventional Kriging method. Mathematical models constructed with this method can be easily connected to later-stage analysis such as uncertainty quantification and sensitivity analysis and are expected to be applied to fundamental research and a wide range of product development fields. The overarching objective of this chapter is to show the capability of MFK surrogates that can be embedded in a digital twin system for ATF

Data-driven multi-scale modeling and robust optimization of composite structure with uncertainty quantification

It is important to accurately model materials' properties at lower length scales (micro-level) while translating the effects to the components and/or system level (macro-level) can significantly reduce the amount of experimentation required to develop new technologies. Robustness analysis of fuel and structural performance for harsh environments (such as power uprated reactor systems or aerospace applications) using machine learning-based multi-scale modeling and robust optimization under uncertainties are required. The fiber and matrix material characteristics are potential sources of uncertainty at the microscale. The stacking sequence (angles of stacking and thickness of layers) of composite layers causes meso-scale uncertainties. It is also possible for macro-scale uncertainties to arise from system properties, like the load or the initial conditions. This chapter demonstrates advanced data-driven methods and outlines the specific capability that must be developed/added for the multi-scale modeling of advanced composite materials. This chapter proposes a multi-scale modeling method for composite structures based on a finite element method (FEM) simulation driven by surrogate models/emulators based on microstructurally informed meso-scale materials models to study the impact of operational parameters/uncertainties using machine learning approaches. To ensure optimal composite materials, composite properties are optimized with respect to initial materials volume fraction using data-driven numerical algorithms

Calculation and Tabulation of Efficiencies for Tungsten Foil Positron Moderators

Monte Carlo radiation transport simulations were used to calculate the positron stopping profiles in tungsten positron moderator foils. Stopping profiles were numerically integrated with efficiency kernels derived from Green\u27s function solutions of the 3D diffusion equation to determine the moderation efficiency in both the backscattering and transmission geometries. Stopping profiles and efficiencies were calculated for positron energies from 10 keV to 10 MeV and incident angles from 0° to 75°. The resulting efficiencies agreed with other calculated and measured values in the literature, especially when similar values of the positron diffusion length and surface emission branching ratio were used. Large discrepancies with some of the values reported in the literature are mainly attributed to differences in foil manufacture and surface condition - factors which are known to greatly influence the diffusion length - as well as work function and branching ratios. This work provides tabulated efficiencies for tungsten foil moderators that can be interpolated and integrated with a positron flux having arbitrary energy and angular distributions

Experimental Evaluation of the Deadtime Phenomenon for GM Detector: Deadtime Dependence on Operating Voltages

A detailed analysis of Geiger Mueller counter deadtime dependence on operating voltage is presented in the manuscript using four pairs of radiation sources. Based on two-source method, detector deadtime is calculated for a wide range of operating voltages which revealed a peculiar relationship between the operating voltage and the detector deadtime. In the low voltage range, a distinct drop in deadtime was observed where deadtime reached a value as low as a few microseconds (22 µs for 204Tl, 26 µs for 137Cs, 9 µs for 22Na). This sharp drop in the deadtime is possibly due to reduced recombination with increasing voltage. After the lowest point, the deadtime generally increased rapidly to reach a maximum (292 µs for 204Tl, 277 µs for 137Cs, 258 µs for 22Na). This rapid increase in the deadtime is mainly due to the on-set of charge multiplication. After the maximum deadtime values, there was an exponential decrease in the deadtime reaching an asymptotic low where the manufacturer recommended voltage for operation falls. This pattern of deadtime voltage dependence was repeated for all sources tested with the exception of 54Mn. Low count rates leading to a negative deadtime suggested poor statistical nature of the data collected for 54Mn and the data while being presented here is not used for any inference

Experimental Investigation on Heat Transfer in a Prismatic Modular Reactor under Cosine Heat Flux

The current study has investigated natural convection heat during pressurized conduction cooldown (PCC) accident scenario to understand the passive safety features of prismatic modular reactors (PMR) under different intensities of nonuniform center peaking step heat flux distributions (approximating cosine shape) using an advanced fast-response heat transfer technique. A scaled-down PMR module was designed and developed at Missouri S&T by the research team of the Multiphase Reactors Engineering and Applications Laboratory (mReal). The module consists of upper and lower plena connected by heated and cooled channels. Nonuniform heat flux distribution was applied to the heated channel under nonuniform heating center peaking step (approximating cosine shape), simulating nonuniform heat distribution within the core of PMR. Air was used as the coolant to study the effect of nonuniform heating under a range of heat flux intensity (four sets of nonuniform heat flux and one set of uniform heat flux were tested) at 413.7 kPa (60 psi). At an axial position of Z/L = 0.409 along the heated channel, the heat transfer coefficient is increased by 35% for nonunifor libJo2O18*m heat flux distributions of set 1 (0.25*2.579 kW.m-2+0.50*3.152 kW.m-2+0.25*2.579 kW.m-2) and set 2 (0.25*2.292 kW.m-2+0.50*2.865 kW.m-2+0.25*2.292 kW.m-2) with respect to the the uniform heat flux set 5(2.865 kW.m-2), and it is decreased by 56% for nonuniform heat flux distributions of set 3 (0.25*2.006 kW.m-2+0.50*2.579 kW.m-2+0.25*2.006 kW.m-2) and set 4 (0.25*1.719 kW.m-2+0.50*2.292 kW.m-2+0.25*1.719 kW.m-2) with respect to the uniform heat flux set (set 5). There is a significant reorder in the heat transfer coefficients distribution curves in descending order along the heated channel after the inflection point (after Z/L =0.773)