Degradation Performance and Biodiversity of an Anaerobic Polyvinyl Alcohol-Degrading Microbial Community

Polyvinyl alcohol( PVA) is a water-soluble synthetic polymer that is hard to biodegrade. PVA-degrading microorganisms were previously reported as unitary bacteria and most of them have been identified as aerobes. In this work,a microbial community was cultured anaerobically and its degradation performance and biodiversity were analyzed. The microbial community was cultured for more than 40 d,which represents a highly efficient degradation performance with a chemical oxygen demand removal efficiency of 88. 48%. Operational taxonomic unit-based analysis of the sequences revealed a highly diverse community in the reactor. To note,metagenome 16s rDNA sequencing delineated 19 phyla and 41 classes. Specifically, proteobacteria, chlamydiae, bacteroidetes,firmicutes,and planctomycetes play key roles in the biodegradation processes. Moreover,the betaproteobacteria class belonging to the proteobacteria phylum was the predominant bacterial members in this community. Our results demonstrated that anaerobic treatment of PVA wastewater is feasible and confers degradation by a highly diverse microbial community.

Prediction of fuel cell performance degradation using a combined approach of machine learning and impedance spectroscopy

Accurate prediction of performance degradation in complex systems such as solid oxide fuel cells is crucial for expediting technological advancements.However,significant challenges still persist due to limited comprehension of degradation mechanisms and difficulties in acquiring in-situ features.In this study,we propose an effective approach that integrates long short-term memory(LSTM) neural network and dynamic electrochemical impedance spectroscopy(DEIS).This integrated approach enables precise prediction of future evolutions in both current-voltage and EIS features using historical testing data,without prior knowledge of degradation mechanisms.For short-term predictions spanning hundreds of hours,our approach achieves a prediction accuracy exceeding 0.99,showcasing promising prospects for diagnostic applications.Additionally,for long-term predictions spanning thousands of hours,we quantitatively determine the significance of each degradation mechanism,which is crucial for enhancing cell durability.Moreover,our proposed approach demonstrates satisfactory predictive ability in both time and frequency domains,offering the potential to reduce EIS testing time by more than half.

Effect of extrusion process on the mechanical and in vitro degradation performance of a biomedical Mg-Zn-Y-Nd alloy

A new type of biomedical Mg-Zn-Y-Nd alloy was developed and thermal extruded by different processes to investigate the effect of extrusion ratio and extrusion pass on its microstructure,mechanical property and degradation performance.The results show that the increase of extrusion ratio could promote the dynamic recrystallization(DRX)process and led to the coarsening of DRXed grains.While the increase of extrusion pass also contributes to the DRX process but refines the DRXed grains.The simultaneous increasing of extrusion ratio and extrusion pass refines the secondary phases obviously.The increase of extrusion ratio has reduced the tensile strength but improved the elongation of the alloy significantly.However,the increase of extrusion pass could enhance the tensile strength and elongation simultaneously,especially the strength.The degradation performance has been optimized effectively through increasing the extrusion ratio and extrusion pass.

Application of a Novel Method for Machine Performance Degradation Assessment Based on Gaussian Mixture Model and Logistic Regression

The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.

Accelerated Degradation Reliability Modeling and Test Data Statistical Analysis of Aerospace Electrical Connector

As few or no failures occur during accelerated life test,it is difficult to assess reliability for long-life products with traditional life tests.Reliability assessment using degradation data of product performance over time becomes a significant approach.Aerospace electrical connector is researched in this paper.Through the analysis of failure mechanism,the performance degradation law is obtained and the statistical model for degradation failure is set up; according to the research on statistical analysis methods for degradation data,accelerated life test theory and method for aerospace electrical connector based on performance degradation is proposed by improving time series analysis method,and the storage reliability is assessed for Y11X series of aerospace electrical connector with degradation data from accelerated degradation test.The result obtained is basically consistent with that obtained from accelerated life test based on failure data,and the two estimates of product＇s characteristic life only have a difference of 8.7%,but the test time shortens about a half.As a result,a systemic approach is proposed for reliability assessment of highly reliable and long-life aerospace product.

Step-stress Accelerated Degradation Test Modeling and Statistical Analysis Methods

In order to get a rapid assessment on the storage reliability of high-reliable and long-life products within the storage period, accelerated degradation test data with a large amount of reliability information of product is adopted. Conducting a constant-stress accelerated degradation test（CSADT） is generally very costly as it requires a large sample size and long time for test. To overcome this problem, it is necessary to carry out research on modeling and statistical analysis methods of step-stress accelerated degradation test （SSADT）. Taking electrical connectors as the object, a research is conducted on statistical model and assessment method for SSADT. On the basis of mixed-effect degradation path model, the statistical model of SSADT for electrical connectors is presented, the maximum likelihood method for SSADT data based on mixed-effect degradation model is proposed. SSADT accelerated by temperature stress is conducted to Y11X-1419 type of electrical connectors, and the storage reliability is assessed with the SSADT data. Compared with the result obtained from accelerated life test, the reliability estimation of 32-year storage period for electrical connectors obtained from S SADT data only have a difference of 0.869%, which validates the accuracy of the degradation model and the feasibility of the test data statistic analysis method put forward.

Reliability Evaluation and Sensitivity Analysis for Multi-state System Based on Time Degradation Measures

The performance and state of multi-state system depend on its structure and different state combinations of the components. In order to evaluate the reliability of multi-state system effectively,a reliability evaluation and sensitivity analysis method based on the time degradation measures was proposed. The equivalence sets of the multi-state system under different output performances were established. The state combinations were classified according to the performance level. The degradation probability models under different states were established,and the new reliability measures,such as dynamic probability of multi-state system,holding time in each state,dynamic expectation function and integrated expectation function of the performance,were proposed and used to implement the dynamic reliability evaluation and sensitivity analysis. A certain diesel engine fuel feeding system was taken as an application example to illustrate the proposed method. The results show that not only the holding time in the desired state of the components and the system can be predicted,but also the best state component in a certain time period can be obtained.

Unified control and detection framework and its applications: a review, some new results, and future perspectives

Initiated three decades ago,integrated design of controllers and fault detectors has continuously attracted research attention.The recent development of the unified control and detection framework with an observer-based residual generator in its core gives a more general form of the previous works.Its applications to residual centred modelling of uncertain control systems,fault detection in feedback control systems with uncertainties,fault-tolerant control(FTC)as well as control performance degradation monitoring,detection and recovery are introduced.In conclusion,some future perspectives are proposed.

A note on diagnosis and performance degradation detection in automatic control systems towards functional safety and cyber security

This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention on three aspects:(i)application of control and detection uni ed framework to enhancing the diagnosis capability of feedback control systems,(ii)projection-based fault detection,and complementary and explainable applications of projection-and machine learning-based techniques,and(iii)system performance degradation detection that is of elemental importance for today's automatic control systems.Some ideas and conceptual schemes are presented and illustrated by means of examples,serving as convincing arguments for research e orts in these aspects.They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.

Storage life of power switching transistors based on performance degradation data

NPN-type small and medium power switching transistors in 3DK series are used to conduct analyses and studies of accelerating degradation. Through three group studies of accelerating degradation in different temperature-humidity constant stresses, the failure sensitive parameters of transistors are identified and the lifetime of samples is extrapolated from the performance degradation data. Average lifetimes in three common distributions are given, when, combined with the Hallberg-Peck temperature-humidity model, the storage lifetime of transistor samples in the natural storage condition is extrapolated between 105-10^7 h. According to its definition, the accelerating factor is 1462 in 100 ℃/100% relative humidity （RH） stress condition, and 25 ℃/25% RH stress con- dition. Finally, the degradation causes of performance parameters of the test samples are analyzed. The findings can provide certain references for the storage reliability of domestic transistors.

Modeling of reliability and performance assessment of a dissimilar redundancy actuation system with failure monitoring

Actuation system is a vital system in an aircraft, providing the force necessary to move flight control surfaces. The system has a significant influence on the overall aircraft performance and its safety. In order to further increase already high reliability and safety, Airbus has imple- mented a dissimilar redundancy actuation system （DRAS） in its aircraft. The DRAS consists of a hydraulic actuation system （HAS） and an electro-hydrostatic actuation system （EHAS）, in which the HAS utilizes a hydraulic source （HS） to move the control surface and the EHAS utilizes an elec- trical supply （ES） to provide the motion force. This paper focuses on the performance degradation processes and fault monitoring strategies of the DRAS, establishes its reliability model based on the generalized stochastic Petri nets （GSPN）, and carries out a reliability assessment considering the fault monitoring coverage rate and the false alarm rate. The results indicate that the proposed reli- ability model of the DRAS, considering the fault and redundancy degradation process and identify monitoring, can express its fault logical relation potential safety hazards.

Erosion degradation characteristics of a linear electro-hydrostatic actuator under a high-frequency turbulent flow field

The paper proposes a performance degradation analysis model based on dynamic erosion wear for a novel Linear Electro-Hydrostatic Actuator（LEHA）. Rather than the traditional statistical methods based on degradation data, the method proposed in this paper firstly analyzes the dominant progressive failure mode of the LEHA based on the working principle and working conditions of the LEHA. The Computational Fluid Dynamics（CFD） method, combining the turbulent theory and the micro erosion principle, is used to establish an erosion model of the rectification mechanism. The erosion rates for different port openings, under a time-varying flow field, are obtained. The piecewise linearization method is applied to update the concentration of contaminated particles within the LEHA, in order to gain insight into the erosion degradation process at various stages of degradation. The main contribution of the proposed model is the application of the dynamic concentration of contamination particles in erosion analysis of Electro-Hydraulic Servo Valves（EHSVs）, throttle valves, spool valves, and needle valves. The effects of system parameters and working conditions on component wear are analyzed by simulations. The results of the proposed model match the expected degradation process.

SAR performance-based fault diagnosis for electrohydraulic control system:A novel FDI framework for closed-loop system

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control systems.However,the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems.To avoid these difficulties,a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed.Under this framework,a socalled performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability,accuracy,and rapidity(SAR)respectively.The criteria for quantification,normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given.FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space.A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.

Performance of highly flexible sub-cable for REBCO Cable-In-Conduit conductor at 5.8 T applied field

Due to the high current capability and excellent flexibility,High Flexible REBCO Cables(HFRC)have emerged as an important candidate for composite high‐temperature superconducting conductors.The REBCO six around one Cable‐In‐Conduit Conductor(CICC)concept has been designed for application in the Central Solenoid(CS)coil of the China Fusion Engineering Test Reactor.In the application of fusion devices,the performance of CICC under electromagnetic(EM)loading and thermal stress is very important for reliable and economic operation.Therefore,a 1.22 m long sub‐cable with HFRC design for CICC was manufactured and tested at 4.2 K in a background magnetic field up to 5.8 T.The aim is to investigate the stability of the current‐carrying properties of the HFRC cable under electromagnetic and thermal cyclic loading.The test results show that the critical current(I_(c))of the HFRC cable reached 17.3 kA in a background magnetic field of 5.8 T at 4.2 K.Furthermore,no performance degradation was observed after 24 cycles of 80 kN/m peak load with a background field of 5.8 T and 8 warm‐up‐cool‐down cycles between 77 K and room temperature.The test results provide a good basis for the development of full‐size conductors in future magnet applications.

Effects of heavy ion irradiation on ultra-deep-submicron partially-depleted SOI devices

The effects of the physical damages induced by heavy ion irradiation on the performance of partiallydepleted SOI devices are experimentally investigated. After heavy ion exposure, different degradation phenomena are observed due to the random strike of heavy ions. A decrease of the saturation current and transconductance,and an enhanced gate-induced drain leakage current are observed, which are mainly attributed to the displacement damages that may be located in the channel, the depletion region of the drain/body junction or the gate-to-drain overlap region. Further, PDSOI devices with and without body contact are compared, which reveals the differences in the threshold voltage shift, the drain-induced barrier lowing effect, the transconductance and the kink effect. The results may provide a guideline for radiation hardened design.

Remaining useful life prognostics for aeroengine based on superstatistics and information fusion

Remaining useful life（RUL） prognostics is a fundamental premise to perform conditionbased maintenance（CBM） for a system subject to performance degradation. Over the past decades,research has been conducted in RUL prognostics for aeroengine. However, most of the prognostics technologies and methods simply base on single parameter, making it hard to demonstrate the specific characteristics of its degradation. To solve such problems, this paper proposes a novel approach to predict RUL by means of superstatistics and information fusion. The performance degradation evolution of the engine is modeled by fusing multiple monitoring parameters, which manifest non-stationary characteristics while degrading. With the obtained degradation curve,prognostics model can be established by state-space method, and then RUL can be estimated when the time-varying parameters of the model are predicted and updated through Kalman filtering algorithm. By this method, the non-stationary degradation of each parameter is represented, and multiple monitoring parameters are incorporated, both contributing to the final prognostics. A case study shows that this approach enables satisfactory prediction evolution and achieves a markedly better prognosis of RUL.

Optimizing guest swapping using elastic and transparent memory provisioning on virtualization platform

On virtualization platforms, peak memory de- mand caused by hotspot applications often triggers page swapping in guest OS, causing performance degradation in- side and outside of this virtual machine （VM）. Even though host holds sufficient memory pages, guest OS is unable to utilize free pages in host directly due to the semantic gap between virtual machine monitor （MM） and guest operat- ing system （OS）. Our work aims at utilizing the free memory scattered in multiple hosts in a virtualization environment to improve the performance of guest swapping in a transparent and implicit way. Based on the insightful analysis of behav- ioral characteristics of guest swapping, we design and im- plement a distributed and scalable framework HybridSwap. It dynamically constructs virtual swap pools using various policies, and builds up a synthetic swapping mechanism in a peer-to-peer way, which can adaptively choose different vir- tual swap pools. We implement the prototype of HybridSwap and evaluate it with some benchmarks in different scenar- ios. The evaluation results demonstrate that our solution has the ability to promote the guest swapping efficiency indeed and shows a double performance promotion in some cases. Even in the worst case, the system overhead brought by Hy- bridSwap is acceptable.