Reliability Problems Research Articles

Dual Power Transformation and Yeo–Johnson Techniques for Static and Dynamic Reliability Assessments

This paper addresses key challenges in the static and dynamic reliability analysis of engineering structures, particularly the difficulty in accurately estimating large reliability indices and small failure probabilities. For static reliability problems, a dual power transformation is employed to transform the performance function into a form approaching a normal distribution. The high-order unscented transformation is then applied to compute the first four moments of the transformed performance function. Subsequently, the fourth-moment method is used to calculate large reliability indices, offering a novel improvement over traditional methods such as FORM and SORM. For dynamic reliability problems, the low-discrepancy sampling technique is integrated to efficiently compute structural responses under random seismic excitation, improving computational efficiency for complex dynamic systems. The Yeo–Johnson transformation is introduced to normalize the extreme values of dynamic responses, and the first four moments of the transformed extreme values are statistically evaluated. Additionally, a third-order polynomial transformation (TPT) is applied to approximate the probability density function, leading to the derivation of the probability of exceedance (POE) curve. The optimal transformation parameters for both the dual power and Yeo–Johnson transformations are determined using the Jarque–Bera (JB) test. Four numerical examples, coupled with Monte Carlo simulation, validate the proposed framework’s accuracy and efficiency, providing a robust tool for static and dynamic reliability analysis. This unified approach represents a significant advancement by integrating novel transformations and fourth-moment method, providing a powerful and efficient tool for static and dynamic reliability analysis of engineering structures.

Hyperspheric Integral Reliability Method for efficient reliability analysis of geotechnical ultimate limit states

This paper introduces the Hyperspheric Integral Reliability Method (HINT) for efficient reliability analysis of geotechnical ultimate limit states. The method is motivated by the mechanism of the Shear Strength Reduction Method (SSRM), which is often employed to calculate the factor of safety for geotechnical ultimate limit states. HINT exploits the observation that a factor of safety, computed by the SSRM, is not only a pointwise estimate of safety, but also a measure of distance to the failure limit along a radial direction in the space of the shear strength parameters. This observation is utilized to transform the reliability integral in the hyperspheric coordinate system and develop an efficient estimator of failure probability for geotechnical ultimate limit states. HINT was examined on several benchmarking problems, demonstrating stable and highly efficient performance on low to medium dimensional reliability problems. HINT can be also applied to general reliability problems if a radial search mechanism is implemented as in the SSRM. Given that the SSRM is already available in most commercial geotechnical software packages, HINT is perfectly suited to advance geotechnical reliability analyses and make them accessible to a wider set of use-cases.

A Monte Carlo-based algorithm for the quickest path flow network reliability problem

A Monte Carlo-based algorithm for the quickest path flow network reliability problem

Effects of Charge Imbalance on Field‐Induced Instability of HfO2‐Based Ferroelectric Tunnel Junctions

AbstractFerroelectricity in hafnium‐based materials has attracted significant research attention and is used in various applications owing to their complementary metal‐oxide‐semiconductor compatibility, scalability, and low‐power operation. However, their widespread integration into various technologies is hindered by reliability and stability problems, particularly field‐induced instability, which causes fluctuations in polarization characteristics during operation. Herein, on the underlying mechanism of field‐induced instability is reported in pure hafnium oxide films within metal‐ferroelectric‐insulator‐semiconductor (MFIS) ferroelectric tunnel junctions (FTJs). The comprehensive material analysis combined with low‐frequency noise (LFN) measurements reveals that the presence of oxygen vacancies and interface traps within the ferroelectric and dielectric layers induces a charge imbalance in the FTJ, leading to distortion in its polarization characteristics and the onset of cyclic evolution in field‐induced instability. Furthermore, high‐pressure annealing effectively mitigates field‐induced instability by reducing the defects within the film, thereby alleviating the associated charge imbalance. These findings contribute to a deeper understanding of the internal dynamics of FTJs and provide an efficient approach to enhancing their stability.

Fatigue life prediction of BGA solder joint of several alloy compositions under an isothermal harmonic vibration

To ensure durable performance and optimal function of electronic components, it is crucial to guarantee their reliability, robustness and goodness of fit. The solder joints used in the BGA (Ball Grid Array) component play an intrinsic role in the reliability of the system. The vibration present in BGA triggers fatigue in solder joints, which raises a major reliability problem in various sectors such as aerospace, automotive and military industries. This study handles the response to a harmonic vibration at three specific temperatures (−40°C, 25°C, and 125°C) for four types of solder alloys in BGA Soldering. Within this framework, predicting the fatigue life of BGA solder joints with various alloy compositions under the influence of an isothermal harmonic vibration emerges as a crucial challenge in the design as well as reliability of modern electronic devices. The investigated solder compositions are SAC105, SAC305, SAC405, and InnoLot. To simulate and analyze the behavior of solder joints, we used the Ansys APDL finite element analysis (FEA). At both 125°C and −40°C, the Von Mises values proved to exceed those observed at 25°C. Likewise, an S-N curve for InnoLot and the different SACs, under a harmonic vibration at 25°C, was fitted using the Basquin power law relationship. As far as the current research work is concerned, an initial comparison was enacted between InnoLot and SAC alloys under an isothermal harmonic vibration, aiming to ascertain the most reliable alloy. The fatigue life under a harmonic vibration loading at 25°C was estimated. The results revealed that under a harmonic vibration at 25°C, the InnoLot solder displayed the longest lifespan, while the SAC105 solder exhibited the shortest fatigue life.

Problems of Admissibility and Reliability of Metadata as Evidence

This paper examines the challenges surrounding the admissibility and reliability of metadata as evidence in civil proceedings. It explores the legal standards, authentication issues, and technical complexities involved in presenting metadata in court. The study analyzes key legal cases, technical methodologies, and emerging technologies that impact the use of metadata as evidence. It addresses concerns such as metadata alteration, spoliation, privacy issues, and cross-border challenges. The research highlights the importance of forensic soundness, expert testimony, and proper interpretation of metadata in legal contexts. Additionally, it discusses the application of traditional evidence rules to digital information and the evolving standards for burden of proof in electronic evidence. The paper concludes by considering future challenges posed by emerging technologies and the need for ongoing legal and technical education in this rapidly evolving field.

Wire Bond Ability Enhancement of 8 Leads Small Outline Integrated Circuit and 14 Leads Thin Shrink Small Outline Package Using AuPd Coated Cu Wire Bonding for Automotive Devices

Paper present a study enhancement of wire bonding process in the integrated circuit package with 2N AuPd coated Cu wire (2N-AuPdCu) for Automotive devices. Wire bonding is the electrical connection between pad and leadframe. In present, Au wire is recently use for interconnection while the gold price still exorbitant and caused concern to the wire bonding cost. Cu wire is a lower price and considered to be an alternative for the interconnection but still concern in term of corrosion and reliability. Recently, 4N AuPd coated Cu wire (4N-AuPdCu) material have been introduced for automotive device but still encounter the reliability problem. The 2N AuPd coated Cu wire was developed version for more reliability enhancement and consider to use for alternative wire of automotive device. In the experiment, Au wire, 4NAuPdCu wire and 2N AuPd coated Cu wire were used for wire bonding process on 8 leads Small Outline Integrated Circuit Package (8L-SOIC) and 14 leads Thin Shrink Small Outline Package (14L-TSSOP) to compare wire bond ability. Analysis, this package tested wire bond ability and reliability. The results performed well in wire bond ability and reliability for 2N AuPd coated Cu wire when comparing with Au wire and 4N AuPd coated Cu wire. Therefore, 2N AuPd coated Cu wire can enhance the quality and reliability for 8L-SOIC package and 14L-TSSOP package for automotive device.

Three-dimensional finite element analysis of biological signal feedback in the mechanical properties of sound production

In response to the problems of low reliability and long time consumption in traditional research on sound production, this article used electromyography (EMG) signals as input signals to build a high-precision sound production mechanics model. A Proportional-Integral-Derivative (PID) controller was used to dynamically adjust the model and develop a real-time feedback system. This article established a detailed three-dimensional (3D) finite element model including the vocal cords and throat, defined the nonlinear elastic properties and linear elastic properties of different tissues, and used tetrahedral grid partitioning technology to improve the computational accuracy of the model. Through a EMG sensor, an individual EMG was collected and filtered to remove noise. The processed EMGs were used as input parameters for the finite element model to drive the muscle units in the model. By using a PID controller to receive real-time EMG input, the error was calculated and the model was adjusted, enabling accurate simulation of the mechanical properties of vocal cord vibration under different vocal states and achieving real-time feedback. Considering the complexity of vocal cord vibration driven by biological signals, this article simulated and analyzed the modal characteristics of vocal cord vibration, and analyzed the differences in vocal cord vibration characteristics under different vocal states. The sound pressure distribution and resonance frequency were simulated and analyzed to understand the propagation characteristics of sound. Finally, by comparing and analyzing the simulated data with the actual collected data, it was found that the maximum relative error rate of the model under different sound states was 6.14%, and the overall error rate of the model was relatively low, which verified the reliability of the model. The findings demonstrated that the feedback delays of the model in different sound states were all within 100 milliseconds, indicating that the system had high real-time performance and accuracy, which was promising in practical applications.

Time-variant reliability analysis using phase-type distribution-based methods

The performance of engineering structures often varies over time due to the randomness and time variability of material properties, environmental conditions and load effects. This paper proposes phase-type (PH) distribution-based methods for efficient time-variant reliability analysis. The core of the proposed methods is to approximate the extreme value of a stochastic process as a PH distributed random variable, and treat the time parameter as a uniformly distributed variable. Consequently, the time-variant reliability problem is transformed into a time-invariant one. Three representative time-invariant reliability methods, first-order reliability method (FORM), importance sampling (IS) and adaptive Kriging (AK) surrogate model-based IS method (AK-IS), are integrated with the PH distribution-based approximation strategy to form the proposed methods, namely PH-FORM, PH-IS and PH-AKIS. The efficiency and accuracy of these methods are demonstrated through three examples. All codes in the study are implemented in MATLAB and provided as supplementary materials.

Research on Road Rage Detection System Based on Multi-feature Fusion

The influence of driver's rage on driving safety is one of the centers of traffic accident research. Road rage is a common potential factor affecting driving safety. Real-time monitoring of driver's emotional state and timely intervention measures can effectively reduce the incidence of traffic accidents. At present, the reliability of driver emotion recognition based on single consistent factor for road rage needs to be further improved. Therefore, based on the multi-feature fusion method, this paper proposes a recognition method of driver's road rage emotional state that integrates facial expression, driving control, voice text and physiological characteristics, and proposes the analysis of fusion strategy. In order to improve the reliability and implementability of road rage symptom judgment, this paper studies the state identification methods of road rage and integrates the characteristics of road rage. The focus of this study is to solve the key problem of insufficient reliability of road rage recognition based on facial expressions through the combination of multiple features and multiple data, aiming at the defects of the study on the single feature of road rage, and effectively improve the accuracy of road rage state emotion detection.

Data Center Problems

“Hyperscale” data centers accompanying the rapid growth of artificial intelligence (AI) is one of the fastest growing uses of electricity in the United States and the rest of the world. Indeed, such growth, with the retirement of dispatchable fossil fuel electricity plants, drives persistent warnings about potential reliability problems for the US power system. As Federal Energy Regulatory Commission's (FERC's) Commissioner Mark Christie warned in late July, to the House Subcommittee on Energy, Climate, and Grid Security.

Deformation behavior and constitutive equation of Sn-37Pb solder alloy at cryogenic temperature

In this work, the tensile property, ductile-to-brittle transition (DBT) mechanism and constitutive relations of 63Sn-37Pb (Sn-37Pb) solder alloy at cryogenic temperature were studied by uniaxial tensile experiments for different temperatures. The tensile strength of Sn-37Pb solder alloy increases from 38.2MPa (293K) to 178.9MPa (123K) and then declines to 145.2MPa (77K) with decreases of temperature, and its fracture elongation changes from 42.8% (293K) to 10.2% (77K). Mechanical behavior of Pb second phase in Sn-37Pb alloy at low temperatures is illustrated: when the temperature drops to 123K and below, the fracture failure of β-Sn matrix occurs in an open mode. As a result, Sn-37Pb solder alloy fails by brittle fracture mode. Anand model is adopted as a unified viscoplastic intrinsic law to describe the intrinsic relationship of Sn-37Pb solder alloys. Above 123K, Anand model can effectively fit the stress-strain curves of Sn-37Pb solder alloys. When the temperature lower than 123K, the deformation characters of Sn-37Pb solder alloys change from elasto-viscoplastic to elasto-plastic, and Anand model is unable to continue to fit the intrinsic relationship of Sn-37Pb solder alloys. Sn-37Pb solder alloy exhibits more obvious strain hardening at low temperature, and its low-temperature intrinsic response is successfully described by Hollomon’s equation. The research method of the solder alloy is of great significance to solve the reliability problem of low temperature electronic devices.

A recurrent neural network‐based rotor displacement estimation method for eight‐pole active magnetic bearing

AbstractActive magnetic bearing (AMB) is a key technology in high‐speed rotating machines for rotor suspension, where the displacement sensors play a crucial role in detecting and controlling the rotor position. However, the traditional displacement sensors have the problems of high cost, large volume and poor reliability. To solve these problems, this paper proposes an innovative solution that utilises a recurrent neural network (RNN) to estimate the rotor displacement from the current in the AMB controller. The proposed method offers high‐quality prediction performance for the rotor displacement which is close to the high precision eddy current displacement sensors. The mathematical model of AMB is analysed to provide guidance in historical current data acquisition and design of RNN. The input dimensions and the architecture of the neural network are optimised to improve both prediction accuracy and computational complexity. Experimental results validate the effectiveness of the algorithm and demonstrate that the proposed method has high accuracy, robustness and generalisation ability.

Towards robust visual understanding: A paradigm shift in computer vision from recognition to reasoning

AbstractModels that learn from data are widely and rapidly being deployed today for real‐world use, but they suffer from unforeseen failures that limit their reliability. These failures often have several causes such as distribution shift; adversarial attacks; calibration errors; scarcity of data and/or ground‐truth labels; noisy, corrupted, or partial data; and limitations of evaluation metrics. But many failures also occur because many modern AI tasks require reasoning beyond pattern matching and such reasoning abilities are difficult to formulate as data‐based input–output function fitting. The reliability problem has become increasingly important under the new paradigm of semantic “multimodal” learning. In this article, I will discuss findings from our work to provide avenues for the development of robust and reliable computer vision systems, particularly by leveraging the interactions between vision and language. This article expands upon the invited talk at AAAI 2024 and covers three thematic areas: robustness of visual recognition systems, open‐domain reliability for visual reasoning, and challenges and opportunities associated with generative models in vision.

A Giza Pyramids Construction metaheuristic approach based on upper bound calculation for solving the network reliability problem

Network reliability optimization is an optimization problem that focuses on finding an optimal solution for a reliable network design. In network reliability optimization, the goal is to maximize network reliability so that the overall cost of the network is reduced at the same time. The discussion of the reliability of various systems in the field of industry and engineering is of great importance, that's why reliability optimization has received a lot of attention in recent decades. Since this problem is included in the category of NP-Hard problems, the use of soft computing methods will be highly effective in solving it. In this paper, an approach based on the Giza Pyramids Construction (GPC) metaheuristic algorithm is proposed to solve the network reliability problem. For this purpose, two independent single objective functions with constraints are defined, and then the reliability of the network is calculated through optimistic estimation using the upper bound method. In order to compare the performance, 12 types of diverse and complex network models have been generated and the proposed algorithm has been compared with 10 popular and state-of-the-art algorithms. Statistical analysis has been used to find significant differences in the performance of algorithms. Also, a real model of the university network has been generated, investigated, and solved as a case study. The results of experiments, statistical analysis, and observations show that the proposed algorithm has a better performance than other metaheuristic algorithms and the proposed approach in solving reliability is an effective and low-cost approach.

ANALYSIS OF THE CAUSES OF CYLINDER HEAD FAILURE OF INTERNAL COMBUSTION ENGINES

The problem of failure of the cylinder head of an internal combustion engine is considered. The factors influencing the reliability of the cylinder head over a given service life are analyzed. Among the areas that suffer the most are considered: partition between valves and between the valve and the nozzle, exhaust channels, attachment points, the plane of the surface that is in contact with the block. An analysis of existing works was carried out. Usually, the issue of reliability of a separate zone is solved, about which you can find many articles and patents. To date, there are no known works that comprehensively consider the problem of the reliability of all problem areas related to the cylinder head. This work describes the nature of the influence on the stressed state of the cylinder head from various factors: temperature loads, loads from the pressure of the working body in the cylinder, loads arising during fastening. Ways to solve problems with the reliability of individual elements exist and are being solved by many researchers, but the expediency of their implementation is ambiguous. Thus, improving heat removal from the hottest surfaces can lead to an increase in the share of influence from other factors. Solving the problem of reliability requires comprehensive consideration and a comprehensive approach. Thus, when modernizing or developing a new design, it becomes mandatory to carry out a calculation study taking into account the most complete range of factors affecting the system, which combines all the constituent elements included in this node. Modern engineering analysis systems allow such studies to be performed. It is also important to have sufficient knowledge about the properties of materials, which significantly affects the quality of the results of calculation studies. The change in heat dissipation parameters over time can be taken into account with the help of boundary conditions, which will allow us to study how the cylinder head will behave after some time of operation.

SERS and electrochemical dual-mode detection of miRNA-141 by using single Au@Ag nanowire as a new platform.

As biomarkers of cancer, the accurate and sensitive detection of microRNAs is of great significance. Therefore, we proposed a surface-enhanced Raman scattering (SERS)/electrochemical (EC) dual-mode nanosensor for sensitively detecting miRNA-141. The nanosensor uses Au@Ag nanowires as a novel SERS/EC sensing platform, which has the advantages of good biocompatibility, fast response, and high sensitivity. The dual-mode nanosensor can not only effectively overcome the problem of insufficient reliability of single signal, but also realize the amplification and stable output of the detection signal, to ensure the reliability and repeatability of miRNA detection. With this sensing strategy, the target miRNA-141 can be detected over a wide linear range (100 fM to 50 nM) (LOD of 18.4 fM for SERS and 16.0 fM for electrochemical methods). In addition, the process shows good selectivity and can distinguish miRNA-141 from other interfering miRNAs. The actual analysis of human serum samples also proves that our strategy has good reliability, repeatability, and has broad application prospects in the field of analysis and detection.

Developing Risk-Informed Speed Limits Against Single-Vehicle Crashes by Exploiting an Augmented Reliability Problem With Multi-Fidelity Enhancement

Developing Risk-Informed Speed Limits Against Single-Vehicle Crashes by Exploiting an Augmented Reliability Problem With Multi-Fidelity Enhancement

Problems of Admissibility and Reliability of Metadata as Evidence

Problems of Admissibility and Reliability of Metadata as Evidence

Некоторые направления совершенствования правоприменительной деятельности в сфере расследования экономических преступлений

The article analyzes some areas of improvement of investigation of economic crimes. In particular, the problem of boundaries of investigator's discretion is viewed as one of important problems in the economic crime investigation sphere. The evidence reliability problem is also studied. Besides, the need to establish special investigative subdivisions in accordance with regional demands is singled out as an organizational problem.