Test Bench Research Articles

Status of the Deep Learning-Based Shattered Pellet Injection Shard Tracking at ASDEX Upgrade

Plasma disruptions pose an intolerable risk to large tokamaks, such as ITER. If a disruption can no longer be avoided, ITER’s last line of defense will be the Shattered Pellet Injection. An experimental test bench was created at ASDEX Upgrade to inform the design decisions for controlling the shattering of the pellets and develop the techniques for the generation of the fragment distributions necessary for optimal disruption mitigation. In an effort to analyze the videos resulting from the more than 1000 tests and determine the impact of different settings on the resulting shard cloud, an analysis pipeline, based on traditional computer vision (CV), was created. This pipeline enabled the analysis of 173 of the videos, but at the same time showed the limits of traditional CV when applied in applications with a highly heterogeneous dataset such as this. We created a machine learning-based (ML) alternative as a drop-in replacement to the original image processing code using a semantic segmentation model to exploit the innate adaptability and robustness of deep learning models. This model is capable of labeling the entire dataset quickly, accurately and reliably. This contribution details the implementation of the ML model and the current state and future plans of the project.

Innovative engine test bench set-up for testing of exhaust gas aftertreatment and detailed gas species analysis for CNG-SI-operation

For an efficient reduction of methane slip, a precise understanding of exhaust gas after treatment under real conditions is essential. Since it is not possible to produce catalytic converters in near-series geometry on a laboratory scale, it is necessary to resort to significantly smaller sample catalysts. Therefore, an engine test bench was designed to ensure real operating conditions for such samples with the help of space velocity and temperature control. A comparison between the actual and reference values of the space velocity results in a small deviation of 0.1% on average. Furthermore, the pressure conditions at the catalyst have been measured showing a propagation of pressure oscillations from the engine outlet which in combination with the space velocity regulation show that real conditions could be applied to the catalyst sample. Subsequently, the exhaust gas concentrations were monitored with a Fourier transform infrared spectrometer. The catalyst material used is PdO on Al2O3, common for methane oxidation. The measurements show that the CH4 conversion is higher under lean conditions, but is below complete conversion. In a final comparison between purely stoichiometric operation and dithering, the course of the CH4 conversion rate over the test period is examined more closely. In addition to sampling pre- and post-catalyst, the exhaust gas composition is measured spatially resolved within a catalyst channel using special measurement technology. In the temporal course of the CH4 emissions, a stabilizing effect due to the change of the operating mode can be seen, showing that dithering seems to prevent further deactivation.

Data Validation Utilizing Expert Knowledge and Shape Constraints

Data validation is a primary concern in any data-driven application, as undetected data errors may negatively affect machine learning models and lead to suboptimal decisions. Data quality issues are usually detected manually by experts, which becomes infeasible and uneconomical for large volumes of data. To enable automated data validation, we propose “shape constraint-based data validation”, a novel approach based on machine learning that incorporates expert knowledge in the form of shape constraints. Shape constraints can be used to describe expected (multivariate and nonlinear) patterns in valid data, and enable the detection of invalid data which deviates from these expected patterns. Our approach can be divided into two steps: (1) shape-constrained prediction models are trained on data, and (2) their training error is analyzed to identify invalid data. The training error can be used as an indicator for invalid data because shape-constrained models can fit valid data better than invalid data. We evaluate the approach on a benchmark suite consisting of synthetic datasets, which we have published for benchmarking similar data validation approaches. Additionally, we demonstrate the capabilities of the proposed approach with a real-world dataset consisting of measurements from a friction test bench in an industrial setting. Our approach detects subtle data errors that are difficult to identify even for domain experts.

Current advances and gaps in knowledge on personalizing masks for non-invasive respiratory support: a scoping review.

Non-invasive respiratory support delivered through a face mask has become a cornerstone treatment for adults and children with acute or chronic respiratory failure. However, an imperfect mask fit using commercially available interfaces is frequently encountered, which may result in patient discomfort and treatment inefficiency or failure. To overcome this challenge, over the last decade increasing attention has been given to the development of personalized face masks, which are custom made to address the specific facial dimensions of an individual patient. With this scoping review we aim to provide a comprehensive overview of the current advances and gaps in knowledge regarding the personalization of ventilation masks. We performed a systematic search of the literature, and identified and summarized a total of 23 studies. Most studies included were involved in the development of nasal masks. Studies targeting adult respiratory care mainly focused on chronic (home) ventilation and included some clinical testing in a relevant subject population. In contrast, pediatric studies focused mostly on respiratory support in the acute setting, while testing was limited to bench or case studies only. Most studies were positive regarding the performance (i.e. comfort, level of air leak and mask pressure applied to the skin) of personalized masks in bench testing or in human, healthy or patient, subjects. Advances in the field of 3D scanning and soft material printing were identified, but important gaps in knowledge remain. In particular, more insight into cushion materials, headgear design, clinical feasibility and cost-effectiveness is needed, before definite recommendations can be made regarding implementation of large scale clinical programs that personalize non-invasive respiratory support masks for adults and children.

A Sensorized 3D-Printed Knee Test Rig for Preliminary Experimental Validation of Patellar Tracking and Contact Simulation

Experimental validation of computational simulations is important because it provides empirical evidence to verify the accuracy and reliability of the simulated results. This validation ensures that the simulation accurately represents real-world phenomena, increasing confidence in the model’s predictive capabilities and its applicability to practical scenarios. The use of musculoskeletal models in orthopedic surgery allows for objective prediction of postoperative function and optimization of results for each patient. To ensure that simulations are trustworthy and can be used for predictive purposes, comparing simulation results with experimental data is crucial. Although progress has been made in obtaining 3D bone geometry and estimating contact forces, validation of these predictions has been limited due to the lack of direct in vivo measurements and the economic and ethical constraints associated with available alternatives. In this study, an existing commercial surgical training station was transformed into a sensorized test bench to replicate a knee subject to a total knee replacement. The original knee inserts of the training station were replaced with personalized 3D-printed bones incorporating their corresponding implants, and multiple sensors with their respective supports were added. The recorded movement of the patella was used in combination with the forces recorded by the pressure sensor and the load cells, to validate the results obtained from the simulation, which was performed by means of a multibody dynamics formulation implemented in a custom-developed library. The utilization of 3D-printed models and sensors facilitated cost-effective and replicable experimental validation of computational simulations, thereby advancing orthopedic surgery while circumventing ethical concerns.

Effect analysis on passive and active regeneration performance of catalytic diesel particulate filters at the equilibrium point in the presence of ash layer

AbstractCatalytic diesel particulate filters (CDPF) form the main post‐processing devices for the diesel engines. Particulates trapped by CDPF can be oxidized by nitrogen dioxide (NO2) and oxygen (O2). The CDPF passive and active regeneration model on platinum‐based catalyst in the presence of ash layer, including the mass, momentum, and enthalpy balances of the gas and the solid phase, the gas diffusion, and the kinetic of the soot oxidation reaction is performed and validated by the bench test. The effects of different temperatures on CDPF passive and active regeneration at the equilibrium point are analyzed. Further, the effective analysis of ash loading and ash layer distribution on the equilibrium state is conducted. The research on CDPF passive and active regeneration at the equilibrium point in the presence of ash layer provides a theoretical basis for CDPF application.

A Single-Output-Filter Double Dual Ćuk Converter

This study introduces an innovative version of a recently studied converter. A Double Dual Ćuk Converter was recently studied with advantages like the possibility of designing it for achieving a low-input current ripple. The proposed converter, called the Improved Double Dual Ćuk Converter, maintains the advantages of the former one, and it is characterized by requiring one less capacitor and inductor than its predecessor. This allows addressing the challenge of optimizing the topology to reduce component count without compromising the operation; this work proposes an efficient design methodology based on theoretical analysis and experimental validation. Results demonstrate that the improved topology not only retains the advantages of the previous version, including high efficiency and robustness, but also enhances power density by reducing the number of components. These advancements open new possibilities for applications requiring compact and efficient power converters, such as renewable energy systems, electric vehicles, and portable power supply systems. This work underscores the importance of continuous innovation in power converter design and lays the groundwork for future research aimed at optimizing converter topologies. A detailed discussion of the operating principles and modeling of the converter is provided. Furthermore, simulation outcomes highlighting differences in steady-state duration, output voltage, input current ripple, and operational efficiency are shared. The results from an experimental test bench are also presented to corroborate the efficacy of the improved converter.

Experiment and simulation study on the functional fatigue of shape memory alloy beam actuators

Abstract The functional fatigue behavior of shape memory alloy (SMA) beam actuators is gaining importance as their utilization in engineering applications becomes more widespread. However, research on the functional fatigue behavior of SMA beam actuators under bending conditions is not as extensive as that on SMA wires. In this paper, an experimental study and theoretical analysis of the functional fatigue behavior of SMA beam actuators were conducted. A measuring method for bending deflection and an automatic thermal cyclic test bench was designed. A series of functional fatigue tests were conducted on SMA beam actuators under different bias load conditions and the functional fatigue patterns were obtained. The material damage factor is defined and calculated through specimen tests. By incorporating the damage factor to modify the existing constitutive model, a model considering functional fatigue and tension-compression asymmetry is obtained. Finite Element Analysis (FEA) is performed based on this modified model to simulate the actuating performance of SMA beam actuators and to compute the deflection at different numbers of cycles. Additionally, a small parameter study on the actuator shape is conducted using FEA. By comparing the FEA results with functional fatigue experimental data, the effectiveness of the modified model is validated, demonstrating its capability to describe functional fatigue and predict actuator lifespan.

Physiological hardware-in-the-loop test bench for mechanical ventilation

Abstract This article presents a hardware-in-the-loop system that can simulate a patient’s physiological responses to mechanical ventilation. The system includes a hardware platform with a mechatronic lung that can physically simulate the respiratory mechanics. A computational patient model replicates the pressure/volume behaviour of the lungs and the impaired gas exchange. Based on current ventilator settings, the model calculates signal curves, which are then transmitted to the physically existing sensors. This enables the test bench to reproduce the pressure/volume behaviour of the lungs and the gas exchange of a simulated patient on mechanical ventilation. In the future, the hardware-in-the-loop system could play an important role in testing and validating highly automated functions in mechanical ventilation and represent an alternative to animal testing.

Investigation of the interaction between corium and metal-coolers at the VCG-135 test bench in the conditions of a severe accident

This article presents the results of research after a series of experiments at the VCG-135 test bench to study the interaction between corium and candidate metal-coolers. Metal-coolers can be used to organize a heat removing from the surface of the corium in the core catcher until the cooling water supply. Zinc, antimony and manganese were selected as the investigated candidate metal-coolers.As a result of the conducted research, the patterns and features of the interaction of metals with corium in the conditions of discharging fragments of solid metal into the corium melt have been established. The macro and microstructure of the solidified compositions of the products of the interaction of corium with metal coolers, the elemental composition to determine the presence of the studied metals in their structure were studied. An elemental analysis of material samples in various areas of the experimental assembly and the working chamber of the VCG-135 test bench was conducted to determine the pattern of migration of corium components and interaction products from the melting volume.

Comparison of the effects of induction heating composite shot peening and conventional shot peening on residual stress, microhardness, and microstructure of 20CrMnTi gear steel

As a commonly used surface strengthening technology, shot peening, which can significantly improve the fatigue strength of mechanical parts, is widely used in the fields of vehicles and aviation. To obtain a larger residual compressive stress and further refine the grain size under normal shot peening intensity and coverage, this study proposes an induction heating composite shot peening (IHCSP) surface strengthening method, aiming to utilize the coupling effect of temperature and stress fields to promote the shot peening strengthening effect. An IHCSP test plan was designed and an IHCSP test bench was created to achieve simultaneous induction heating and shot peening. This study compares the surface integrity parameters and microstructures under three processes: un-peened, conventional shot peening, and IHCSP. The results show that the maximum axial and radial compressive residual stresses increase by 72.41 and 75.4 MPa respectively; the depth of the hardened layer increases by 0.3 mm, the martensitic transformation more complete, the grain size decreases by 483 nm, the dislocation density increases significantly, and nanocrystals are obtained on the surface of the material. These results verify the superiority of IHCSP surface strengthening.

Nonlinear mechanical response analysis and convolutional neural network enabled diagnosis of single-span rotor bearing system

The wide application of rotating machinery has boosted the development of electricity and aviation, however, long-term operation can lead to a variety of faults. The use of different measures to deal with corresponding malfunctions is the key to generating benefits, so it is significant to carry out the fault diagnosis of rotating machinery. In this work, a test bench for single-span rotor bearings was established, three faults, including spindle bending, spindle crack without end loading and spindle crack with end loading, are experimental analyzed with basic mechanical response. Moreover, a diagnosis is performed using a convolutional neural network, according to the differences in mechanical responses of the three faults obtained from experiments. For three faults, the change in the properties of spindle itself results in different axis trajectories and spectra. Compared with spindle bending fault, spindle crack fault not only cause 1×, 2×, 3× frequency component excitation, also 4×, 5× frequency component excitation. Additionally, the classification accuracy of the training set and the test set under machine learning for the three types of working conditions is 100%. This indicates that the network can significantly identify signal features so as to make effective fault classification.

A Three-Level Neutral-Point-Clamped Converter Based Standalone Wind Energy Conversion System Controlled with a New Simplified Line-to-Line Space Vector Modulation

Wind power systems, which are currently being constructed for the electricity worldwide market, are mostly based on Doubly Fed Induction Generators (DFIGs). To control such systems, multilevel converters are increasingly preferred due to the well-known benefits they provide. This paper deals with the control of a standalone DFIG-based Wind Energy Conversion System (WECS) by using a three-level Neutral-Point-Clamped (NPC) converter. The frequency and magnitude of the stator output voltage of the DFIG are controlled and fixed at nominal values despite the variable rotor speed, ensuring a continuous AC supply for three-phase loads. This task is achieved by controlling the DFIG rotor currents via a PI controller combined with a new Simplified Direct Space Vector Modulation strategy (SDSVM), which is applied to the three-level NPC converter. This strategy is based on the use of a line-to-line three-level converter space vector diagram without using Park transformation and then simplifying it to that of a two-level converter. The performance of the proposed SDSVM technique in terms of controlling the three-level NPC-converter-based standalone WECS is demonstrated through simulation results. The whole WECS control and the SDSVM strategy are implemented on a dSPACE DS 1104 board that drives a DFIG-based wind system test bench. The obtained experimental results confirm the validity and performance in terms of control.

Thermal fatigue life prediction of brake disks based on coupled thermal simulation

The thermal-mechanical performance of friction pairs of the foundation brake gear is an important guarantee for the safe operation of high-speed trains. The thermal stress of brake disks under high temperature is the primary cause of thermal fatigue damage. In this article, the brake bench tests were carried out under braking speed of 350km/h and a thermo-mechanical-wear coupled model was established to simulate tests. By analyzing the results of bench test and finite element simulation, it shows the top temperature of brake disk was over 600°Cand the friction surfaces of brake friction pair show obvious wear. Combining the FE simulation and test results of the thermal fatigue sample, the thermal fatigue characteristics of brake disk material were studied. Based on the residual stress results, the propagation life of brake disk thermal fatigue crack was estimated. It shows that when the crack length increases to 10mm, the crack propagation life of brake disk is halved, and continues to decrease as the crack grows.

Variable-dimension optimization study and design of internally finned helically coiled tubes heat exchangers based on numerical simulation and experiment

To improve the heat transfer in the helically coiled tubes, a novel type of internally finned helically coiled tube is proposed. The heat transfer and flow resistance characteristics of internally finned helically coiled tubes are investigated numerically. The empirical correlations to calculate the Nusselt number and friction factor of internally finned helically coiled tubes are summarized. The maximum relative error is not exceeding 18 %. To validate the empirical correlations, a test bench to evaluate the performance of internally finned helically coiled tubes heat exchangers is constructed, with a smooth helically coiled tubes heat exchanger as a comparison. The experimental results indicate that 94 % of the data exhibit a relative error of less than 30 % when compared to the fitting correlations. The heat transfer coefficient of the tube side is increased by approximately 30 %. Based on the validated correlations, a generalized variable-dimension optimization approach is proposed to solve the complex problem of optimizing the design of helically coiled tubes heat exchangers. Taking the area margin, heat transfer area and total cost, the structure of internally finned helically coiled tubes heat exchangers is optimized with different limitation. The optimization results show that the internally finned helically coiled tubes heat exchangers have better performance than smooth helically coiled tubes heat exchangers. A helically coiled tubes heat exchanger has been designed in an engineering project and significant improvements have been achieved in various performance indicators.

An enhanced motorcycle tyre model characterised through experimental riding data

Tyre-road interaction governs motorcycle dynamics; however, the most widespread tyre model formulations must be characterised through a dedicated test bench on the lab or road, unavailable to many interested subjects. This article proposed a new tyre model formulation, conceived to be characterised through riding data using standard instrumentation. Albeit its coefficients are identified through quasi-static, uncombined slip manoeuvres, the model addresses transient, combined manoeuvres and is adaptive to road friction levels and static weight through statistical relationships from the literature. A pre-existing formulation was improved and expanded. The model’s behaviour in demanding conditions was investigated through a high-fidelity simulation environment, using a Magic Formula tyre model as the reference. Next, the characterisation procedure was carried out using actual riding data. The model’s accuracy is shown by reproducing numerically one of the manoeuvres and through comparison with the results of a bench test. The proposed model could correctly reproduce the primary behaviour of a Magic Formula model, also concerning tyre moments and steering torque. Characterising the tyre model through real riding data proved feasible, and its robust formulation limited the propagation of estimation errors. The proposed tyre model formulation and characterisation procedure should interest, among others, those subjects that lack access to a tyre testing machine.

Tracking dry gin volatile organic compounds over distillation: a time course study

Why was the work done: The influence of distillation time on the volatile composition of gin has not been examined in detail at a commercial distillery. How was the work done: Headspace Solid-Phase Micro-Extraction Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) was used to tentatively identify 74 aroma compounds, with their concentration tracked in distillate samples over the course of three gin distillations. What are the main findings: Four unique fractions were identified using Agglomerative Hierarchical Clustering: ‘heads’, ‘early hearts’, ‘late hearts, and ‘tails’. The hearts fraction (n=24 samples) was examined further, fitting statistically appropriate models to 54 aroma volatiles. Three sub-groups of volatiles were identified, (i) highly volatile monoterpenes with rapidly decreasing concentration over the early hearts fraction, (ii) volatiles whose concentration increased gradually over the hearts fraction and (iii) less volatile sesquiterpenes, sesquiterpenoids, and monoterpenoids which increased rapidly in concentration in the later distillate. Complex cubic models fit 34 volatiles with very high significance (p>0.0001) over the hearts fraction (72%). Informal aroma sensory bench testing identified distinct aroma categories with, for example, ‘Spicy’ being commonly detected in the later distillate. Why is the work important: This investigation characterises the kinetics of flavour extraction over the course of a commercial gin distillation process. These findings highlight the potential for the expression of specific flavour characteristics by modifying the cut points of the distillation process

Measurement of the local static mechanical pressure of earplugs

Earplugs are used in various critical industrial sectors, such as construction, aviation, military and defense, transportation, and healthcare. However, they present inherent drawbacks, notably discomfort that can lead to inconsistent and incorrect use, thereby leaving a significant proportion of workers vulnerable to irreversible hearing damage, ranging from tinnitus to deafness. This discomfort is closely linked to a physical parameter known as static mechanical pressure (SMP), representing the pressure exerted by earplugs on the earcanal walls. Determining the SMP is crucial for developing earplugs that prioritize comfort. However, experimental studies in this area are scarce and there is no experimental set-up capable of measuring the SMP whether in vivo or ex vivo. The objective of this paper is to fill this gap by presenting a novel experimental system designed to mimic a real earcanal, equipped with an optical probe for precise pressure measurements at various points along the earcanal. This precision-targeted methodology holds the promise of yielding a comprehensive pressure map spanning the entirety of the contact area between the earplug and earcanal, thereby offering unprecedented insights into SMP distribution. To validate our test bench, we conducted experiments using cylindrical rolled-down PVC earplugs inserted into a rigid cylindrical earcanal replica of varying radii. We compared our results with data obtained from a commercially available radial force tester commonly used in investigating stent grafts. Once validation was achieved, we expanded our investigation to measure SMP across various types of earplugs. Additionally, we designed and measured the SMP using roll-down foam earplugs in an artificial earcanal shaped to resemble the human anatomy. Our experimental findings were corroborated with data from finite element method (FEM) numerical calculations. Apart from providing the first comprehensive characterization of the static mechanical pressure exerted by earplugs, our research reveals that with roll-down foam earplugs, increased compression prior to insertion leads to reduced SMP. The versatility of our specially designed test bench allows for mapping SMP caused by earplugs across diverse earcanal shapes. Integration of this instrument into design frameworks holds promise for enhancing the physical comfort of earplugs and, consequently, improving their overall efficacy in hearing protection.

Potassium Borate/graphene Nanocomposite Lubricant Additive with Anti-friction/wear and Anti-corrosion Functions for Marine Diesel Engine Burning Low Sulfur Fuel

To suppress the corrosion and wear of cylinder liner of marine diesel engine burning low sulfur fuel, potassium borate/graphene lubricant additive was prepared by plasma assisted ball milling. Tribological tests were conducted by simulating operating condition of diesel engine to evaluate the anti-friction/wear and anti-corrosion properties of potassium borate/graphene additive. The effect of additive on cylinder liner corrosion and wear was verified by bench test of diesel engine. The results of tribological tests indicated tribochemical reaction occurred on the surface of the cylinder liner-piston ring and generated a tribochemical film composed of graphene, FeO, Fe2O3, Fe3O4, B2O3 and Fe2B with anti-friction/wear and anti-corrosion properties. Bench test shown that potassium borate/graphene additive had good anti-friction/wear and anti-corrosion functions, and reduced fuel consumption and exhaust emissions of the engine.

Improvement on the linearity response of PandaX-4T with new photomultiplier tube bases

With the expanding reach of physics, xenon-based detectors such as PandaX-4T in the China Jinping Underground Laboratory aim to cover an energy range from sub-keV to multi-MeV. A linear response of the photomultiplier tubes (PMTs) is required for both scintillation and electroluminescence signals. Through a dedicated bench test, we investigated the cause of the non-linear response in the Hamamatsu R11410-23 PMTs used in PandaX-4T. The saturation and suppression of the PMT waveform observed during the commissioning of PandaX-4T were caused by the high-voltage divider base. The bench test data validated the de-saturation algorithm used in the PandaX-4T data analysis. We also confirmed the improvement in linearity of a new PMT base design with three more low radioactivity capacitors at later dynodes, which will be used to upgrade the PMT readout system in PandaX-4T.