Experimental Measurement Data Research Articles

Prediction of Decay Heat from PWR Spent Nuclear Fuel Using Fuel Parameters

In the context of a geological repository for nuclear waste, fast and accurate predictions of decay heat are needed for different applications ranging from canister loading optimization to comparing decay heat predictions from state-of-the-art codes with experimental measurements. This work uses a large database of simulated pressurized water reactor (PWR) spent nuclear fuel (SNF) with an extensive range of fuel parameters to demonstrate that by using only the burnup, initial enrichment, and cooling time of the SNF, it is possible to predict the decay heat of a PWR SNF. A linear interpolation model has been developed using the simulated data and tested on data from decay heat measurements using a calorimeter. The model code was also made publicly available [V. Solans, “Python Script for the Prediction of Decay Heat from PWR Spent Nuclear Fuel Using Fuel Parameters,” Zenodo (2024)]. The results show that the decay heat can be well predicted, with the relative error between measurements and predictions ranging between 4% and 8%. After correcting for a systematic deviation between predictions and experimental results using the limited set of experimental measurement data available, the relative error can be further reduced to 2% to 3%.

Predicting noise for full-scale distributed propulsion aircraft by synthesizing subscale data with existing prediction tools

Future projections of the economic impact of Urban Air Mobility (UAM) or Advanced Air Mobility (AAM) are bold with global GDP increases ranging from billions to trillions over the next few decades. While the potential opportunities are vast, there will be a paradigm shift in the sheer volume of flights at lower altitudes near populated communities. While there is still debate on the initial markets, there is a strong consensus that these aircraft must not appreciably contribute to the existing soundscape and ideally would be imperceptible in most cases. The novel designs of many distributed propulsion aircraft are challenging the existing noise prediction tools that were primarily built around propellers, jet aircraft, and rotorcraft. This paper will present a summary of recent research efforts on synthesizing subscale experimental acoustics measurement data with noise propagation tools to compute community noise exposure on the ground for different full-scale vehicle configurations and flight profiles. The benefits, drawbacks, and limitations of each data source will be discussed along with suggestions for how to improve the prediction methods and models by synthesizing multiple data sets.

Life-cycle seismic resilience prediction of sea-crossing bridge piers exposed to chloride-induced corrosion in marine environments

The life-cycle seismic resilience assessment of sea-crossing highway bridges plays a crucial role in guiding decisions for their long-term operation, maintenance, and rehabilitation. Due to the inherently stochastic nature of marine environments, evaluating the resilience of bridges while considering all possible environmental scenarios throughout their service life necessitates substantial computational efforts and presents practical challenges. Thus, this study develops a three-stage framework for predicting the life-cycle seismic resilience of sea-crossing highway bridges. Stochastic models for marine environmental conditions and bridge durability are developed and validated using experimental measurement data. A modified Good Lattice Point-Partially Stratified Sampling (GLP-PSS) method is employed to generate a uniform and limited number of samples. A typical prestressed concrete sea-crossing highway bridge is selected as the benchmark bridge, and parameterized numerical models are established using 460 representative environmental parameter samples on the OpenSees platform. Leveraging the environmental model and material properties, the durability of the bridge is predicted over its service life. Nonlinear time history analyses are carried out for each bridge model using 120 real ground motion records, which allow the identification of variations in seismic demands, capacities, and system fragilities at different time intervals. Subsequently, the life-cycle seismic resilience of the bridge is predicted utilizing surrogate models based on the response surface method (RSM) and artificial neural networks (ANN), respectively. Finally, the time-dependent probabilistic characteristics of seismic resilience are thoroughly discussed. Results indicate that ANN demonstrates a higher degree of generalization capability in predicting the life-cycle seismic resilience. Focusing solely on changes in mean resilience over the service time may lead to an underestimation of bridge resilience, as it may ignore the tails of its distribution, potentially resulting in an overestimation of bridge resilience. Furthermore, global warming may expedite the decline in resilience.

MATHEMATICAL MODEL AND ALGORITHM FOR THE DETERMINATION OF THE ORIGIN OF ELECTRICITY FROM RENEWABLE ENERGY SOURCES IN THE ELECTRIC POWER SYSTEM

The article deals with the development of a method and algorithm for calculation of individual compo-nents of electricity flows in the branches of an electric power grid circuit caused by generation and con-sumption in its nodes. In particular, it is about estimating the share of renewable energy sources (RES) in the electricity consumption of a given consumer. The method is based on methods and algorithms for the calculation of steady-state modes of power grids, integrating a mathematical model for determining the components of current flows in the branches of the power system circuit. The model employs distribution coefficients of currents in the circuit branches from RES nodes and node voltages to form a matrix of cur-rent distribution coefficients for RES across the power grid branches. Since RES in electric power systems (EPS) use general power grids to transmit the electricity they generate, accurate determination of their power share within overall flows enables the impact of RES on the EPS mode parameters to be considered. The peculiarity of the algorithm for estimating the share of RES in the electricity consumption of a given consumer is its consideration of physical processes in the power system. The input data for the calculation are the power system parameters, the node loads (specified by capacity or schedules), as well as arrays of RES generation and centralized power supply nodes and consumers with a controlled value of the Guar-anteed Origin of electricity from RES. The voltages during the formation of the matrix of power distribu-tion coefficients at nodes along the branches of the power grid are determined by the calculation results of the power grid steady-state modes or by experimental measurement data. The method's efficacy and the accuracy of estimating the RES share in the power consumption of a given consumer are verified and demonstrated through a practical example. Determination of the share of the consumer's electricity con-sumption, which origin from renewable sources can be guaranteed, creates an enabling environment that would foster producers and consumers to increase the use of renewable energy sources and promotes the development of the green energy market. Ref. 18. Fig.3.

Non-linear influences of track dynamic irregularities on vertical levelling loss of heavy-haul railway track geometry under cyclic loadings

Abstract With an emphasis on the combined degradation of railway track geometry and components, a new numerical-analytical method is proposed for predicting the track geometrical vertical levelling loss (VLL). In contrast to previous studies, this research unprecedentedly considers the influence of initial track irregularities (ITI) on VLL under cyclic loadings, elastic-plastic behaviour, and different operational dynamic conditions. The non-linear numerical models are simulated using an explicit finite element package known as LS-Dyna, and their results are validated by full-scale experimental and field measurement data. The outcomes are iteratively regressed by an analytical logarithmic function that cumulates permanent settlements, which innovatively extends the effect of ITI on VLL in a long-term behaviour. For a typical heavy-haul railway operating under 30 tons axle load and 60 km/h train velocity, the result indicates that the set of ITI with the highest standard deviation (SD) of vertical profile (VP) degrades faster (37% on average) than that with the lowest SD. Additionally, our new findings reveal that the worst scenario is related to a train running at 60 km/h and carrying a load of 20 tons/axle in an uneven track whose SD of VP evolves from 3.23 mm at N = 0 (ITI) to 7.20 mm, whereas the best one corresponds to a train at 60 km/h and 30 ton axle load in an uneven track whose SD of VP downgrades from 0.48 to 1.50 mm, both at 3 M cycles (or 60 million gross tons). These findings indicate the importance of considering the ITI for predicting track geometrical VLL under cyclic loadings. Therefore, based on this research, an acceptable condition (thresholds) of ITI can be redefined for a minimum effect on VLL, which can support the development of practical maintenance guidelines to extend the railway track service life.

Simulation and test for the micro-newton electromagnetic calibration force measurement

For micro-Newton (μN) level thrust measurement, achieving highly accurate calibration forces is crucial as an initial step. To provide high-precision and wide-range electromagnetic calibration forces, this study introduces a C-type magnetic circuit structure and a rectangular coil combination method. The magnetic field distribution within the device’s characteristic region was examined using the finite element method, and the impact of the relative positions of the rectangular coil and magnet was explored. Subsequently, calibration experiments were conducted on a specially developed platform. The primary findings are as follows: The electromagnetic force calibration range is from 0.097 to 237.32 μN, with the maximum error between experimental measurement data and simulation results being 1.73%. With a coil current resolution of 10 μA, the measured resolution of the calibration force exceeds 0.1 μN. Within the characteristic region, the magnetic field distribution exhibits high uniformity, with a maximum deviation rate of only 0.7%. This research establishes a technique for micro-Newton level thrust measurement.

Loss-Optimized Design of Magnetic Devices.

Maximizing efficiency, power density, and reliability stands as paramount objectives in the advancement of power electronic systems. Notably, the dimensions and losses of magnetic components emerge as primary constraints hindering the miniaturization of such systems. Researchers have increasingly focused on the design of loss minimization and size optimization of magnetic devices. In this paper, with the objective of minimizing the loss of magnetic devices, an optimal design method for the winding structure of devices is proposed based on the coupling relationship between the loss prediction model and the design variables. The method examines the decoupling conditions between the design variables and the loss model, deriving optimized design closure equations for the design variables. This approach furnishes a technical foundation for the miniaturized design of miniature apparatuses incorporating magnetic components, offering a straightforward and adaptable design methodology. The finite element method simulation results and experimental measurement data verify the accuracy of the prediction of the proposed method and the validity of the optimal design theory of device loss.

Broadband four-shoulder sine antenna of radio monitoring and direction finding equipment with a note system of two orthogonally combined printed resistance transformers

Problem statement. The article presents material on the development of antennas used in radio monitoring and radio direction finding equipment of electronic warfare equipment. The basic requirements for the design and characteristics of antennas of radio monitoring and direction finding equipment are presented. Aspects of the fundamentals of the development of a four-arm broadband antenna powered by two orthogonally combined printed resistance transformers, which has not been used before, for the possibility of controlling polarization, are considered, the results of modeling the developed antenna are presented and recommendations for its use in the antenna array are given. Purpose. To develop a small-sized antenna that allows to increase the efficiency of the operation of radio direction finding and radio monitoring complexes in an ultra-wide frequency band, with a special power supply system of two orthogonally combined printed resistance transformers for the possibility of implementing polarization control. Results. Based on the methods of electrodynamic modeling, computational methods of technical electrodynamics, methods of full–scale experimental measurements of antenna characteristics and methods of computer processing of data of full-scale experimental measurements, an antenna has been developed that allows the control of amplitude, phase and polarization parameters in an ultra-wide frequency band. The developed antenna is based on a flat four-arm sine element with a power supply system of two orthogonally arranged printed resistance transformers. The resistance transformer significantly reduces the level of the reflection coefficient at the input and radiation losses. The use of this development in radio direction finding and radio monitoring complexes will reduce the number of sublattices of the antenna system due to the functioning of its elements in an ultra-wide frequency band. The practical significance lies in reducing the number of letters of radio direction finding antenna systems consisting of the developed antenna elements, minimizing the degree of distortion of ultra-wideband signals and ultrashort pulses of arbitrary (varying) polarization received by antenna devices and systems from the antenna presented in the article. The developed antenna and antenna devices based on it can be used for electronic warfare, as well as improving communication and remote control systems.

Experimental design and verification of heat transfer flow in a scaled cabin model under the influence of convective and radiative coupling

With the development of aircraft towards high altitude, high speed, and long endurance, the influence of aerodynamic and radiant heat on the flow and heat transfer in the cabin has increased. To explore the flow conditions in the cabin under the influence of ventilation, convection, and radiation coupling, a scaled model test was conducted for verification and simulation. According to the scaling principle, a small ventilation box with a scale of 1: 5 was designed to simulate the boundary conditions in grid computing methods by building ventilation, heating, and irradiation systems. The CFD results were compared with experimental results for analysis. The results show that the experimental results of the scaled model are comparable to the flow field of the prototype model, and the experimental measurement data can be used as a reference indicator for evaluating the temperature field inside the model cabin. The comparison between the simulation experiment and the simulation results verifies the applicability of numerical calculation methods to simulate the flow field in the passenger compartment and the rationality of the scaled test technical scheme.

Diffusivities and Atomic Mobilities in BCC Ti-Fe-Cr Alloys.

In this research, the diffusion behaviors within the Ti-Fe-Cr ternary system were examined at the temperatures of 1273 K and 1373 K through the diffusion couple technique. This study led to the determination of both ternary inter-diffusion and impurity diffusion coefficients in the body-centered cubic (bcc) phase for the Ti-Fe-Cr alloy, utilizing the Whittle-Green and Hall methods. The statistics show that the average diffusion coefficients D˜FeFeTi and D˜CrCrTi measured at 1273 K were 1.34 × 10-12 and 3.66 × 10-13, respectively. At 1373 K, the average values of D˜FeFeTi and D˜CrCrTi were 4.89 × 10-12 and 1.43 × 10-12. By adopting the CALPHAD method, a self-consistent database for atomic mobility in the bcc phase of the Ti-Fe-Cr system was established. This database underwent refinement by comparing the newly acquired diffusion coefficients with data from the existing literature. Diffusion simulations for the diffusion couples were performed, drawing on the established database. The error between the simulated diffusion coefficient and the experimental measurement data is within 15%, and the simulated data of the component distance distribution and diffusion path are in good agreement with the experimental data. The simulations generated results that aligned well with the observed experimental diffusion characteristics, thereby affirming the reliability and accuracy of the database.

Reconstruction of γ Dose Rate Field and Algorithm Validation Based on Inverse Distance Weight Interpolation

The inverse distance weighting (IDW) interpolation algorithm is used to reconstruct the γ radiation field. The traditional IDW interpolation algorithm is improved. The power exponent of distance P in the IDW for each interpolation point is not fixed and varies from one point to the other point. A fitting expression of P is obtained, which is a function of the coordinates of each point and can minimize the interpolation error when the number of sampling points is specified. Afterward, the improved algorithm is used to reconstruct a γ radiation field of a single source, and the theoretic results are compared with the results from Geant4, yielding an average relative error of 7.50%. The interpolated results from the experimental measurements align well with the actual data, with an average relative error of only 0.12%. The P derived from the interpolated experimental measurement data shows an error of 2.0% compared to the power exponent obtained from the Geant4 data interpolation. Then we set up a double-source γ radiation scene experiment and measured the count rate data at the grid points. At the same time, the experiment scene was simulated by Geant4. The improved IDW algorithm could not reconstruct the double-source γ radiation field well, thus further improvement is needed.

Steam Storage Rankine Cycle for Unutilized Applications in Distributed High-Temperature Waste Heat Recovery

In the light of increasingly valuable resources and a trend towards more efficient processes pushed by climate change, distributed Waste Heat Recovery (WHR) is an important element in the transformation of the energy supply. In recent years, however, WHR systems have often been optimized and implemented for steady-state applications. In this paper, dynamic system modeling and a Steam Rankine Cycle (SRC) pilot plant with 40 kWel are used to investigate applications unutilized thus far for the conversion of high-temperature waste heat into electricity using a shell boiler with 1.27 m3 of liquid water for short-term energy storage. In addition to experimental investigations of the storage system as an Uninterruptible Power Supply (UPS) and the input and output of +/−100% electrical power peaks for grid-assistive operation, a control concept for the use of volatile waste heat is developed from a model-based controller design up to a Model Predictive Control (MPC) with the help of a dynamic system simulation. Based on the validated model and experimental measurement data, outlooks for concrete applications with higher storage capacity and power are provided.

PM2.5 and PM10 in the Atmosphere of Kutaisi City

Based on the atmospheric air monitoring data and using experimental measurements there has been assessed concentrations of micro aerosols (PM2.5 and PM10) and features of their time change in the atmosphere of Kutaisi city and its adjacent territories. There have been determined the numbers of days and observation, when their average daily concentrations exceed the respective maximum permissible concentrations. Micro aerosols surface distribution pattern has been built up according to experimental measurements data. Zones of high and low concentrations have been established.

The role of surface roughness on the electrical behavior of flexible and stretchable screen-printed silver ink on Kapton substrate

Changes in the morphology and profile of the printed electronic traces affect the radio frequency (RF) performance, especially when compared to the simulated designs, which are primarily rectangular and smooth. The shape and morphology of the printed traces depend on the printing system, a combination of ink and substrate properties, and the printed technology used for fabrication. This paper investigates the significance of printing parameters like roughness, height, width, and profile shape on the RF performance of screen-printed traces statistically. This paper also derives a model based on actual profile shape and roughness measurements from incorporating these effects into the simulations. From the statistical study, we found that the role of surface roughness becomes more significant as the frequency increases. Thus, modeling surface roughness in flexible hybrid electronics simulations is fundamental for accurate results. Different simulated profile shapes also showed their effect on the RF performance, when combined with roughness, showed better correlation with experimental data. Our proposed model combines the modified Morgan and Hammerstad equation with the compound conductor model. Our proposed model uniquely integrates the modified Morgan and Hammerstad equation with the compound conductor model, leveraging a comprehensive approach focused on the quality and uniformity of printed electronics trace. This integration is aimed at constructing a model that is firmly grounded in actual roughness data, resulting in a solution that is both straightforward to implement and exceptionally accurate in its outcomes. The model agreed well with experimental measurement data over 7 GHz–40 GHz with a root-mean-square error average of 5.7%.

ВТРАТИ ЕЛЕКТРОЕНЕРГІЇ, ВИКЛИКАНІ ПЕРЕТОКАМИ ВІДНОВЛЮВАНИХ ДЖЕРЕЛ ЕНЕРГІЇ, В БАЛАНСІ ЕЛЕКТРИЧНИХ МЕРЕЖ

Renewable energy sources (RES) affect the technical and economic parameters of electrical grids. In particular, with the increase in the amount of electricity in the EPS balance produced by RES, it is relevant to determine the power and electricity losses in electric grids caused by flows of electricity from RES. The method, algorithm and program for determining the component of power and electricity losses from RES in the total losses of electrical grids have been developed. The basis of the method is a mathematical model of the electrical grid for determining losses, which uses the current distribution coefficients in the circuits of the circuits from RES nodes and node voltages. As a result, a matrix of power loss distribution coefficients is formed in the branches of the circuit depending on the power in the nodes of the circuit. The voltages during the formation of the loss distribution matrix are determined based on the results of the calculation of steady-state modes of the electrical network or according to experimental measurement data. It is shown that the values of electricity losses in electrical grids caused by RES can be used during the operational planning of the electricity balance in the EPS and, since they are addressable, their cost can be compensated accordingly. References 8, figures 2.

Research on rapid imaging with cosmic ray muon scattering tomography

Cosmic ray muons tomography is a non-destructive imaging technique that uses the natural radiation of cosmic ray muons to create tomographic images of objects. This article presents a novel imaging algorithm that effectively utilizes experimental measurement data to achieve rapid and clear imaging of cosmic ray muons. A clear image can be obtained with only 20 min of measurement time and approximately 200 effective muons. However, the current detection flux is only about 0.044 cm^{-2} min^{-1}, which is significantly lower than the natural cosmic ray flux of about 1 cm^{-2} min^{-1}.

A method of convolutional neural network based on frequency segmentation for monitoring the state of wind turbine blades

Wind turbine blades are prone to failure due to high tip speed, rain, dust and so on. A surface condition detecting approach based on wind turbine blade aerodynamic noise is proposed. On the experimental measurement data, variational mode decomposition filtering and Mel spectrogram drawing are conducted first. The Mel spectrogram is divided into two halves based on frequency characteristics and then sent into the convolutional neural network. Gaussian white noise is superimposed on the original signal and the output results are assessed based on score coefficients, considering the complexity of the real environment. The surfaces of Wind turbine blades are classified into four types: standard, attachments, polishing, and serrated trailing edge. The proposed method is evaluated and the detection accuracy in complicated background conditions is found to be 99.59%. In addition to support the differentiation of trained models, utilizing proper score coefficients also permit the screening of unknown types.

A data-driven equivalent circuit model’s parameter estimation method applied to Lithium-Titanate battery

Lithium battery systems are becoming essential for a variety of applications, such as maximisation of self-produced renewable energy in buildings, grid balances, and electric vehicles. Accurate and equivalent models are required to study and analyse the behaviour of batteries, both static and dynamic. This paper presents a novel data-driven parameter estimation procedure for high-current battery modelling, which has been applied to experimental measurement data conducted on Lithium Titanate batteries. The proposed estimation methodology has been applied to three different equivalent circuit models characterised by increasing modelling complexity. Genetic algorithm optimisation techniques solve the optimisation problem, estimating the model’s parameters and a look-up table of battery parameters estimated in discretised State of Charge. Enhance the battery operation modelling at high depth of discharge, the model is applied to the battery operated at high currents, covering its entire domain of state of charge. The fully depleted and charged state is given increased focus to maintain good modelling performance. Unlike previous works, the proposed methodology repeats the parameters estimation procedure for more than thirty-five state of charge ranges using non-equal width ranges to increase model density in critical regions. Based on the estimation results for one C-rate, it was found that the parameter estimation error ranges from 0.17% for the Rint model to 0.03% for the Dual-Polarisation model. The validation results confirmed that the proposed approach had a normalised root mean square error lower than 2%. The proposed methodology encompasses the entire process of parameter estimation, starting from raw experimental data. As such, it can be generalised and applied to other battery technologies.

Estimating the contribution of community landscape construction to urban carbon neutrality: methodology and database construction

Green ecological communities have garnered significant interest due to their role in providing urban ecosystem services, and community greening plays a pivotal role in urban environmental enhancement. In the context of carbon neutrality-oriented goals, it is imperative to acknowledge the significance of various landscape designs in carbon sequestration within community greening initiatives. However, there is currently a lack of consideration for landscape designs that promote high carbon sequestration in community greening projects. Our research with literature research and experimental measurement data as data sources, established a database of carbon sequestration of 138 common vegetation species in Shanghai. Based on the vertical vegetation structure within landscape design, we propose seven modular planting structures that reflect the carbon sequestration potential of high-capacity plants within different community green spaces. Our findings reveal substantial variations in carbon sequestration among different tree species within arbor and shrub categories, whereas the differences in carbon sequestration among various herbaceous plants per unit area are comparatively smaller. Among the different combination patterns, the highest carbon sequestration is achieved by the vegetation configuration of the three-layer structure pattern, and the combination of arbors, shrubs and grasses can maximize the effective use of space. This study holds significant importance in optimizing the utilization of limited green spaces within communities and enhancing the carbon sequestration benefits of community landscapes. Ultimately, these efforts contribute significantly to Shanghai’s journey toward carbon neutrality.

Determination of Correlations between Melt Quality and the Screw Performance Index in the Extrusion Process.

For polymer-processing extruders, designing screws via analytical computational models is helpful for reducing experimental costs. However, the current simulation programs cannot predict the melt quality at the screw tip with sufficient accuracy. There are a number of definitions of melt quality in the literature. This paper will review some of these definitions and present how melt quality can be assessed in subsequent work. In this paper, both the thermal and material homogeneity of the melt quality are examined for correlations with the screw performance index. If correlations exist with the screw performance index determined from direct experimental measurement data, these can be used as target values for developing a melt quality prediction model.