Normal Operating Conditions Research Articles

Assessment of the three-dimensional flow field in the reactor pressure vessel in Hualong One nuclear power plants

This study uses computational fluid dynamics (CFD) to investigate the three-dimensional flow field under normal operating conditions in the reactor pressure vessel (RPV) in the Hualong One nuclear power plants (NPPs). With a particular focus on the flowrate distribution at the core inlet, the numerical framework is validated against the integral hydraulic experiment in a 1:4-scaled RPV of CNP1000, the prototype of the Hualong One reactor. The simulation results of the normalized flowrate at the core inlet agree reasonably well with the measured data. Based on the experimental data, several methods of calibrating the CFD turbulence model coefficients are suggested by introducing the concepts of data assimilation and machine learning. The flow field in a realistic RPV for Hualong One is predicted using the validated numerical framework, showing that the flowrate distribution at the core inlet is nearly homogeneous and that the turbulent intensity is acceptably low for each fuel assembly. It can provide essential information for the reactor core thermal–hydraulic design and the fuel assembly mechanical assessment.

A hybrid mixed‐cells DC‐DC modular multilevel converter with balanced arm energy and DC fault blocking capability for high voltage direct current systems

SummaryDC‐DC converters play a vital role in the integration of renewable energy sources. Modular multilevel converter (MMC) has emerged as a highly promising option for high‐voltage high‐power applications, for DC‐AC and DC‐DC conversion, thanks to its distinctive characteristics. An inherent limitation of using traditional MMC in DC‐DC conversion is the occurrence of arm energy drift, leading to imbalanced voltages across capacitors of submodules (SMs). Many approaches have been presented in the literature to address the energy drift issue during DC‐DC conversion process. In this paper, a novel bidirectional hybrid modular multilevel DC‐DC converter with balanced arm energy has been proposed. The proposed converter consists of one high‐voltage valve and two legs. Each leg is equipped with half‐bridge submodules (HB‐SMs) in the upper arm and full‐bridge submodules (FB‐SMs) in the lower arm. The proposed architecture enables the parallel connection between series‐connected capacitors of the upper arm and series‐connected capacitors of the lower arm during the equalization period. The parallel connectivity enables the energy transfer between the upper and lower arms in the same leg, hence preventing energy drift issues. A detailed illustration of converter operational concept, mathematical analysis, design, and efficiency estimation are presented. The presented simulation and experimental results show the bidirectional power flow ability and the promising behavior of the proposed converter during normal operating conditions with balanced arm energy. Finally, a comparison between the proposed converter and other existing topologies has been made to show the superiority of the proposed converter over the other alternatives. The proposed converter has a lower count of insulated gate bipolar transistors (IGBTs) and eliminates the usage of isolating transformers when compared to the energy equalization modules approach. In addition, unlike the other alternatives, the proposed converter has a DC fault blocking capability.

Simulation of High Thermal Conductivity Polyurethane DC Support Capacitor

In the field of energy storage, capacitors are receiving more and more attention due to their high power density, long life cycle, lack of maintenance, etc. We have developed a thermoelectric coupling model to simulate the temperature rise of DC support capacitors under normal operating conditions at room temperature and to obtain accurate results. Boundary conditions are established under this model and the temperature rise of the capacitor is shown by iteration as well as solving the partial differential equation. The temperature rise condition of the capacitor is shown by iteration and solving partial differential equations and the actual situation is predicted and investigated. The results show that the capacitor can operate steadily under normal working conditions.

A new estimation approach based on phi‐divergence measures for one‐shot device accelerated life testing

AbstractOne‐shot device testing data are used only once and they get destroyed when tested. As these products usually have large mean times to failure under normal operating conditions, accelerated life tests are commonly used to infer their lifetime distribution. While much work has been done to determine the maximum likelihood estimates (MLEs) of model parameters for one‐shot device accelerated life testing, the efficiency of these methods may not be guaranteed for small to moderate sample sizes. In this paper, we develop new estimators and confidence intervals based on phi‐divergences, we show that they outperform the conventional MLE under different lifetime distributions and present an example to illustrate all the inferential methods developed here.

A Test System for Transmission Expansion Planning Studies

This paper introduces a 17-bus 500 kV test system intended for transmission expansion planning (TEP) studies. The overhead lines used in the system are based on an actual 500 kV transmission line geometry. Although several test systems have been developed for various forms of power system analysis, few are specifically tailored for TEP studies at the transmission voltage level, as opposed to the distribution voltage level. Current test systems for TEP studies are limited to single loading conditions only for normal operating conditions, and the majority of these systems are intertwined with issues related to the energy market or devised specifically for integrating new generations and loads into the existing power systems. However, ensuring a test system satisfies both voltage drop and line loading criteria during both normal and all single contingency operations is crucial in TEP studies, and addressing these issues under contingency conditions poses notable challenges. Moreover, practical TEP scenarios involve varied loadings, including peak load and dominant loading (60% of peak load) scenarios, while the existing test systems are configured solely for single loading conditions. To address these technical gaps, this paper introduces the 17-bus test system operating at a transmission voltage level of 500 kV, meeting technical requirements under normal and all single contingency operations for both peak load and dominant load scenarios. Detailed specifications of the proposed test system and load flow analysis at both normal and contingency conditions for different loading conditions are presented. This test system serves as an invaluable resource for TEP studies.

Waterproofing a Thermally Actuated Vibrational MEMS Viscosity Sensor

An efficient and inexpensive post-process method to waterproof an electrically actuated microtransducer has been studied. The electrical signals of microtransducers operating in electrically conductive fluids must be effectively isolated from the surrounding environment while remaining in contact for sensing purposes. A thermally actuated MEMS viscosity sensor uses electrical signals for both actuation and sensing. Three post-processing materials, (1) Parylene-C, (2) flouroacrylate-based polymer, and (3) nitrocellulose-based polymer, were coated as thin layers of waterproofing materials on different sensors. All three coating materials provided adequate protection when tested under normal operating conditions. Although the vibration response of the sensors was slightly modified, it did not affect their functionality in a significant way when measuring conductive fluids based on glycerol–water mixtures. All the treated sensors lasted over 1.2 million actuations without any decay in performance or failures. When the test bias conditions were increased by 5x to accelerate failures, the flouroacrylate-based polymer samples lasted 2x longer than the others. Visual analysis of the failures indicates that the edge of the diaphragm, which undergoes the most significant stress and strain values during actuation, was the location of the mechanical failure. This work guides post-processed waterproofing coatings for microscale actuators operating in harsh and damaging environments.

Determination of the reliability of cement mills

For any industrial entity put into operation, the problem is that it fulfils its specified function, under certain conditions of use and for a specified period of time, i.e. to have an appropriate reliability. In calculating the reliability of industrial entities in general and cement mills in particular, the main problem is to obtain the necessary information. They may be obtained from laboratory tests or tests under normal operating conditions, from maintenance teams, or from specialized control institutions. The general opinion is that only tests under normal operating conditions can provide real data on the behaviour of entities, subassemblies, and their component parts, which is why in general, reliability calculations are based on data obtained from so-called operation / failure reports. Therefore, considering this opinion, the reliability of cement mills was assessed following the operation of such a machine.

Study on cavitation performance improvement of high-power centrifugal pump impeller

High power centrifugal pump is frequently used in large project for water resources allocation. Cavitation phenomenon causes noise and vibration and affects the centrifugal pump unit stability. The impeller model was used an initial impeller to be developed, and the impeller geometry, the blade profile, blade inlet edge were optimized by design method based on numerical simulation technique to improve cavitation performances. The 3D model with the initial and optimized impeller were simulated to obtain cavitation characteristic. The results of optimization impeller are compared and verified by model test. The numerical simulation results show that the pressure distribution is distributed on the blade surface is uniform and the location of lowest pressure is reasonable. The test results show that the optimized design significantly increases the ratio of plant cavitation coefficient σp to incipient cavitation coefficient σi and critical cavitation coefficient σ1 of the impeller under normal operation conditions, the safety margin of cavitation is increased. It was confirmed from numerical simulation and model test results that the impeller blade optimization is a reasonable and effective method for cavitation performance improvement. The study results provides design reference for the cavitation performance improvement and safe operation of high power centrifugal pump.

Development and experimental validation of a prototype system for Machine Learning based SHM in composite aerostructures

The development and experimental validation of a Machine Learning (ML) vibration based Structural Health Monitoring (SHM) prototype system for composite aerostructures operating under uncertainty is presented. Following initial training, it is intended to operate autonomously, in almost real-time, without interrupting normal operation, relying on a limited number of acceleration and strain measurements from properly selected locations on the aerostructure. It is equipped with a multi-level information fusion methodology comprising multiple sensor technologies and diagnostic algorithms for optimized SHM performance in terms of damage detection and characterization. Through its flexible software, the system provides multiple options of ML based SHM methods targeting wide applicability to various types of structures. The system is validated based on numerous experiments with healthy and damaged full-scale composite bonded spars operating under multiple uncertainty factors. Its diagnostic performance indicates that the current progress in hardware and robust vibration-based Machine Learning algorithms may lead to compact, effective, and low cost SHM systems for composite aerostructures under normal operating conditions.

Research on cavitation characteristics of water-jet pumps with different blade tip clearances based on entropy production theory

Water-jet pumps are widely used in ship and other power fields. An axial-flow water-jet pump is studied with different size of tip clearance, and the cavitation characteristics are studied based on the theory of entropy production. Modified SST with curvature correction and modified Zwart cavitation model based on vortex identification are adopted, and the numerical calculation method is verified by reference experiments of a model pump. Under normal operating conditions, the results show that when the size of the tip clearance varies from 1.6‰ to 7.9‰ of the impeller diameter, efficiency takes a linear decrease accordingly, and the total entropy production increases linearly. At the same time, the main energy dissipation mode changes from wall dissipation to turbulent dissipation. Under severe cavitation conditions the total entropy production adds 30%. The water-jet pump shows that the entropy production in the impeller section is the highest, which accounts for 40%-50% and is closely related to the vortex and cavitation flow field in the tip clearance of the impeller. The tip leakage vortex region causes cavitation, but significant energy dissipation occurs at the outer edge of leakage vortex and on the nearby wall area, while the attached cavitation on the blade surface is the main source of turbulent dissipation.

CFD modelling of velocity fields around a fume cupboard: Evaluating static and dynamic meshes with experimental measurements

This paper presents a comparison of experimental and numerical modelling results of the velocity field around a fume cupboard with a static and a dynamic mesh. During fume cupboard testing, components are required to move which mimic typical operating conditions, the amount of tracer gas released is then measured. This tracer gas is harmful to the environment and so an alternative is required. Advanced Computational Fluid Dynamics (CFD) techniques, such as dynamic meshing, have been utilised to replicate aspects of the current tests. The fume cupboard was tested in normal operating conditions and under the influence of a board inducing a wake close to the fume cupboard entrance. The velocity fields have been compared and show a reasonable level of accuracy with a percentage difference between experimental and simulated results of around 5% using both a static and a dynamic domain. This is an improvement on the 15–20% accuracy for detecting concentration of tracer gas using previous experimental methods. The aim of this work is to satisfy the scientific community and fume cupboard operators that CFD is sufficiently accurate to assess fume cupboard performance under real world scenarios.

Impact of Lithium‐Ion Battery Separators on Gas Evolution during Temperature Abuse

AbstractSeparators in lithium‐ion batteries are typically considered to be electrochemically inert under normal operating conditions. Yet, temperature abuse tests at elevated temperatures of ca. 60 °C to 132 °C show that the choice of separator material has a decisive influence on battery behavior and degradation. Using online electrochemical mass spectrometry, we analyzed the evolution of cell voltage and gas products during and after thermal abuse for different separators. Polypropylene and polytetrafluoroethylene seem exhibited little change in gas evolution, producing only modest amounts of CO2 and POF3. In contrast, glass fiber and polyethylene terephthalate separators caused additional gas release, indicating electrochemical instability. Polyethylene terephthalate produced significantly more gas, resulting in the mechanical failure of the separator and drastic performance losses. The amount of CO2 evolved with polyethylene terephthalate is four times higher than that of the glass fiber separator. However, the amount of POF3 detected was five times higher for the glass fiber separator.

A Novel Multi-loop Fuzzy Logic Dynamic Controller for Wind/Photovoltaic-Grid Interface DC Energy Utilization Farm

This paper proposes a novel control system for control of a hybrid wind/photovoltaic (PV) farm utilization with alternative power source for DC type loads. A controller consisting of six different loop controllers is mainly used to regulate the DC-DC converter to reduce a weighted total sum of all loop errors, to mainly track a given speed reference trajectory depicting the demand for discharge or flow and also to ensure power quality, reliability and stability. The proposed control function is digitally simulated using the MATLAB/Simulink/ SimPower System software environment. The dynamic performance of the hybrid system is examined for the control system validation under normal and abnormal operating conditions.

Surface recombination and peltier heat generation in Kesterite thin film solar cells due to defect increment under elevated heat

Thermal instability is the major barrier against the commercialization and upscaling of thin film solar cells. Heat generation in thin film solar cells occurs both at normal operation conditions and under stress conditions. In this paper, we developed a simulation model to investigate the heat generation in CZTSSe Kesterite thin film solar cells by coupling the optical, electrical, and thermal modules in the COMSOL simulation package. This strongly coupled model allows investigation of the two main heat generation factors in solar cell structure: Surface recombination heat and Peltier heat. These factors have been rarely analyzed in literature but can be significantly detrimental to the solar cell structure especially when the temperature of the cell rises over time under operation conditions. We extended our simulation to insert the defect growth at the Surface and bulk of the CZTSSe layer of the cell for elevated temperatures (400 °C. for 1000 h) and calculate the heat generation at CZTSSe/Mo(S,Se)2 and CZTSSe/CdS interfaces and at the deletion width of the junction where Surface recombination heat and Peltier heat generated from electrons and holes are generated. The simulation shows that Peltier heat generation from electrons is more dominant than Peltier heat from holes while the surface recombination heat is significantly more dominant compared to Peltier heat generation.

A comparison between grey-box models and neural networks for indoor air temperature prediction in buildings

Model Predictive Control has gained much attention due to its potential to improve building operations by reducing costs, integrating renewable energy sources, and increasing thermal comfort. This paper aims to compare the accuracy of grey-box models based on resistance–capacitance (RC) networks and Long-Short-Term Memory (LSTM) neural networks in the prediction of the buildings’ thermal response, which is a key feature for the successful implementation of predictive controllers. Indoor air temperature prediction tests have been performed on simulated and measured data from buildings with different thermal insulation and thermal mass during both heating and cooling seasons. Results show that neural networks have, on average, a better prediction performance than grey-box models. Both modelling approaches are affected by the building characteristics and by the season considered. The grey-box models require less training data, although the latter seems to play a role only in the worse-performing tests. When user setpoint changes in the testing phase, the LSTM neural network shows a significant drop in the root mean square error. In conclusion, although LSTM outperforms grey-box models on average, the reduced training data and higher reliability under normal operating conditions, as well as their linearity, make RC models a strong alternative for predictive controllers.

Design and technical evaluation of an AMBU-BAG based low-cost ventilator-AARMED

The COVID-19 pandemic has caused a significant strain on the healthcare system worldwide, resulting in an acute shortage of ventilators. Conventional ventilators are costly, and production is difficult to scale up during a rapidly spreading pandemic. Ambu bags offer a low-cost solution for manual ventilation, but their lack of precise control over parameters makes them unsuitable as a replacement for conventional ventilators. To address this issue, we propose the AARMED (Ambu bag Attachment for Rapid Mass Emergency Deployment) system, which is a low-cost and easy-to-assemble mechanical resuscitator that can achieve most of the recommended modes and parameter ranges for managing COVID-19 patients. AARMED can operate in volume-control, pressure-control, and assist-controlled modes continuously over long periods, making it suitable for use in emergency settings. The AARMED system has been tested using an ISO certified Test-lung over various parameter settings and has been found to be an effective alternative to costly conventional ventilators. It has a battery backup of 2.5 h under normal operating conditions, making it an ideal transport ventilator. In conclusion, the AARMED system offers a low-cost and easy-to-assemble solution for mechanical ventilation in emergency settings. Its ability to achieve most of the recommended modes and parameter ranges for managing COVID-19 patients makes it a viable alternative to conventional ventilators in resource-constrained settings.

Unsupervised anomaly detection for earthquake detection on Korea high-speed trains using autoencoder-based deep learning models

We propose a method for detecting earthquakes for high-speed trains based on unsupervised anomaly-detection techniques. In particular, we utilized autoencoder-based deep learning models for unsupervised learning using only normal training vibration data. Datasets were generated from South Korean high-speed train data, and seismic data were measured using seismometers nationwide. The proposed method is compared with the conventional Short Time Average over Long Time Average (STA/LTA) model, considering earthquake detection capabilities, focusing on a Peak Ground Acceleration (PGA) threshold of 0.07, a criterion for track derailment. The results show that the proposed model exhibit improved earthquake detection capabilities than STA/LTA for PGA of 0.07 or higher. Furthermore, the proposed model reduced false earthquake detections under normal operating conditions and accurately identified normal states. In contrast, the STA/LTA method demonstrated a high rate of false earthquake detection under normal operating conditions, underscoring its propensity for inaccurate detection in many instances. The proposed approach shows promising performance even in situations with limited seismic data and offers a viable solution for earthquake detection in regions with relatively few seismic events.

The impact of COVID-19 related flight reductions on bird prevalence and behaviour at Manchester Airport, UK, and the implications for airport management

Airport management is a complex and multifarious activity, involving many operators including airlines, retailers and ground handlers, and processes. The presence of wildlife at airports poses a safety risk to aircraft operations and as such managing wildlife hazards is a mandatory legal responsibility. This is important not only from a safety perspective but also from the fact that safety incidents can impact the operational efficiency and the reputation of an airport. Airport operators are required to devise and enact site-specific Wildlife Hazard Management Plans (WHMP) to reduce the risk of aircraft-wildlife interaction under normal airport operating conditions. The COVID-19 pandemic, however, led to an unprecedented reduction in commercial air traffic and the partial or total suspension of flights at some airports. The aim of this paper is to examine the impact of COVID-19 related flight reductions on bird prevalence and behaviour and the potential implications for airport management. Drawing on an empirical dataset of wildlife observations at Manchester Airport, UK, in 2019 and 2020, this paper details the airfield ornithology before and during the pandemic and examines the impact of COVID-19 related flight reductions on bird prevalence and behaviour. The findings reveal variations in the frequency and apparency of individual species as well as changes in the spatial location of bird sightings on the airfield. The paper concludes by discussing the implications of these findings for post-pandemic operations and for the formulation of future airport wildlife hazard management policies.

On the hierarchical Bayesian modelling of frequency response functions

Structural health monitoring (SHM) strategies seek to evaluate, predict, and maintain structural integrity, to improve the safety and design service life of structures in operation. Many of these strategies involve monitoring changes in structural dynamics, as damage can affect modal properties and present as changes in the characteristics of the resonance peaks of the frequency response function (FRF). While recent advances have improved the safety and reliability of structures, a number of challenges remain, impeding the practical implementation and generalisation of these systems. Like damage, benign variations, such as those caused by changes in temperature or other environmental fluctuations, can affect dynamic properties, making it difficult to distinguish between damage and normal operating conditions. In addition, newly-deployed structures can have insufficient data to describe the normal operating conditions (i.e., data scarcity), which can impair the development of data-based prediction models. Another common challenge is data loss (i.e., data sparsity), which may result from transmission issues, sensor failure, a sample-rate mismatch between sensors, and other causes. Missing data in the time domain will result in decreased resolution in the frequency domain, which can impair dynamic characterisation.For situations that may benefit from information sharing among datasets, e.g., population-based SHM of similar structures, the hierarchical Bayesian approach provides a useful modelling structure. Hierarchical Bayesian models learn statistical distributions at the population (or parent) and the domain levels simultaneously, to bolster statistical strength among the parameters. As a result, variance is reduced among the parameter estimates, particularly when data are limited. In this paper, a combined probabilistic FRF model is developed for a small population of nominally-identical helicopter blades, using a hierarchical Bayesian structure, to support information transfer in the context of sparse data. The modelling approach is also demonstrated in a traditional SHM context, for a single helicopter blade exposed to varying temperatures, to show how the inclusion of physics-based knowledge can improve generalisation beyond the training data, in the context of scarce data. These models address critical challenges in SHM, by accommodating benign variations that present as differences in the underlying dynamics, while also considering (and utilising), the similarities among the domains.

Thermal-hydraulic study of the EU-DEMO Helium Cooled Pebble Bed Breeding Blanket Primary Heat Transport System

The European DEMO reactor will work under normal operating conditions in accordance with a pulsed duty cycle. However unplanned and planned transients of plasma overpower may occur compromising the integrity of its plasma-facing components structures. Consequently, adopting appropriate tools is essential to accurately and consistently model the thermal-hydraulic response of the involved cooling systems under both normal operating conditions and accidental events. Given this background, the University of Palermo, in collaboration with EUROfusion, started a research work to study the thermal-hydraulic behaviour of the Primary Heat Transport System (PHTS) of the Helium Cooled Pebble Bed Breeding Blanket (HCPB BB) of the DEMO device under steady-state and transient conditions. The activity has been performed adopting a computational approach, employing the thermal-hydraulic system code TRACE version 5.0 patch 6. The key point of the work has been the code-to-code benchmark with the outcomes previously obtained with the RELAP5-3D code, to estimate the impact of the physical models, numerical resolution schemes and modelling techniques adopted on the predictive capabilities of the system codes considered. The models and the analysis results are presented and critically discussed herein.