Reliability Calculation Research Articles

Machine Learning-Enhanced Quantum Chemistry-Assisted Refinement of the Active Site Structure of Metalloproteins.

Understanding the fine structural details of inhibitor binding at the active site of metalloenzymes can have a profound impact on the rational drug design targeted to this broad class of biomolecules. Structural techniques such as NMR, cryo-EM, and X-ray crystallography can provide bond lengths and angles, but the uncertainties in these measurements can be as large as the range of values that have been observed for these quantities in all the published structures. This uncertainty is far too large to allow for reliable calculations at the quantum chemical (QC) levels for developing precise structure-activity relationships or for improving the energetic considerations in protein-inhibitor studies. Therefore, the need arises to rely upon computational methods to refine the active site structures well beyond the resolution obtained with routine application of structural methods. In a recent paper, we have shown that it is possible to refine the active site of cobalt(II)-substituted MMP12, a metalloprotein that is a relevant drug target, by matching to the experimental pseudocontact shifts (PCS) those calculated using multireference ab initio QC methods. The computational cost of this methodology becomes a significant bottleneck when the starting structure is not sufficiently close to the final one, which is often the case with biomolecular structures. To tackle this problem, we have developed an approach based on a neural network (NN) and a support vector regression (SVR) and applied it to the refinement of the active site structure of oxalate-inhibited human carbonic anhydrase 2 (hCAII), another prototypical metalloprotein target. The refined structure gives a remarkably good agreement between the QC-calculated and the experimental PCS. This study not only contributes to the knowledge of CAII but also demonstrates the utility of combining machine learning (ML) algorithms with QC calculations, offering a promising avenue for investigating other drug targets and complex biological systems in general.

Evidence‐based fault tree analysis of the hydraulic system in CNC machine tools

AbstractThe hydraulic system is an integral part of CNC machine tools. In analyzing the reliability of machine tool hydraulic systems, their failures are influenced by both aleatory and epistemic uncertainties. This paper utilizes the fault tree analysis method to address failure modes subject to epistemic uncertainty, using the interval rough number scoring method to evaluate the probability of such failures occurring. The resulting reliability calculation is termed as “subjective reliability”. For failure modes influenced by aleatory uncertainty, objective data combined with the Dempster–Shafer evidence theory is used to determine their failure probability, with the corresponding reliability calculation referred to as “objective reliability”. Finally, a comprehensive calculation of both subjective and objective reliability is conducted to determine the overall reliability of the hydraulic system, along with the ranking of the importance of basic events of fault tree. This methodology covers scenarios with small samples, sufficient data, and their combinations, offering extensive application prospects.

Getting to the bottom of why children with spina bifida use the emergency department: A qualitative analysis of parent and stakeholder perspectives

Children with Spina Bifida (SB) have considerable healthcare utilization, including Emergency Department use (EDU). We aimed to elicit reasons for EDU using qualitative analysis of interviews with both patient-caregiver dyads and stakeholders. A cohort of children with SB followed at our institution between 2016 and 2020 was identified and patient and clinical characteristics abstracted. Purposeful sampling by age and degree of past EDU was performed. Semi-structured interviews of dyads were performed using iteratively revised interview guides. Spanish-language interviews were conducted by a native Spanish speaker and transcripts professionally translated. Supplemental interviews with stakeholders, namely knowledgeable healthcare professionals, were also conducted. A qualitative framework approach was used for analysis, including open followed by closed independent coding with calculation of inter-rater reliability. A final interpretation of coding reports assessing convergence, divergence, and variation in themes across participant characteristics. 116 families (4 Spanish-speaking) and 7 stakeholders were interviewed. Sampling yielded a heterogenous cohort for EDU (56% with 0-10, 44% with >10 visits) and age (25% 0-4, 44% 5-11, 31%>11 years). IRR was optimal (κ=0.9). Themes in perceived reasons for EDU were 1) desire for "one-stop-shop" care, 2) an emergent medical problem, 3) providers' instructions, 4) negative past healthcare experience, 5) intrinsic caregiver moderators, and 6) temporospatial influences. Themes 1, 2, and 5 predominated in dyads, whereas themes 6, 3, and 5 were most common in stakeholders. Stakeholders focused largely on negative institutional and patient characteristics. Among dyads only, theme #1 was disproportionately emphasized by Spanish-speaking patients. Families desired access to coordinated expert care, testing and imaging. The ED offers this for children with SB, regardless of clinical acuity. This may be especially valued by families with inherent challenges to navigating the healthcare system. Negative experiences in community clinical settings, healthcare provider recommendations and intrinsic parental factors were themes that seemed to contribute to seeking this "one-stop-shop" type of care. Care coordination may reduce ED reliance, but themes for the interviews suggest a systems-based efforts should weave in the community care setting. For both stakeholders and caregivers, the ED represented a valued form of immediate access to multispecialty, expert care and testing in the context of perceived lack of timely, coordinated outpatient care. This may be moderated by intrinsic caregiver factors and negative past experiences. Although stakeholders discussed ideas that fit into patient-caregiver themes, the also uniquely focused on systems-based and patient-caregiver limitations.

Optimum embedment depths for CFST column-to-foundation connections: Analytical and reliability-based approach

In the present study, the pullout capacity models were developed to derive analytical expressions for the minimum required depths of embedment for conventional and two recently published schemes of connection for circular and square concrete-filled steel tubular (CFST) columns. The models were developed by equating the pullout strength of the tube with the pullout capacity of the reinforced concrete (RC) footing. The pullout capacity of the RC footing was a function of the strength of cement grout, footing concrete, and RC footing reinforcement. The analytical expressions derived for the minimum required depths of embedment were utilized to deduce limit state functions. These limit state functions were then employed for the reliability calculations by means of the Monte Carlo Simulation (MCS) technique. The reliability calculations provide optimum embedment depths for CFST columns for the given reliability level. It was shown for the required reliability index of 3.0, the requirements of nominal embedment depth for the second column-to-foundation connecting scheme for circular and square CFST columns are 37.3% and 45.2% less than their corresponding first schemes of connection. This outcome proves the superiority of the second scheme (as a result of mechanical interlocking) over the first scheme. A few parametric studies were also conducted to obtain results of practical value.

Investigating the structural, electronic, and magnetic properties of Cd1-xVxTe: Insights from First-Principles calculations

In our study, we aim to investigate the structural, electronic, and magnetic properties of CdVTe, a diluted magnetic semiconductor with a Cadmium telluride (CdTe) structure. To achieve this, we employ the full potential linear augmented plane wave method implemented in the CASTEP code, which allows us to accurately simulate the behavior of the system. To describe the electronic exchange and correlation effects, we adopt the generalized gradient approximation (GGA) within the density functional theory (DFT) framework. This choice of methodology ensures reliable and accurate calculations of the electronic and magnetic properties of Cd1-xVxTe. Our results reveal that the substitution of Vanadium (V) into the Cadmium (Cd) site of the CdTe lattice does not alter the zinc blende crystal structure, demonstrating the stability and structural integrity of the system. Furthermore, our calculations demonstrate that the introduction of Vanadium impurities leads to spin polarization within the material, resulting in the emergence of a magnetic moment. Notably, we find that a Vanadium concentration of approximately x≈0.12 exhibits the strongest magnetic properties, characterized by a significant magnetic moment. These findings provide valuable insights into the behavior and potential applications of CdVTe as a diluted magnetic semiconductor, shedding light on the interplay between structural, electronic, and magnetic properties in this material.

Fast and Reliable Computation of Instantaneous Orbital Collision Probability

Because of the increasing number of objects in low Earth orbit, the fast and reliable estimation of the collision risk is an important challenge for spacecraft owners/operators. Among the available risk indicators, this paper focuses on computing the instantaneous probability of collision, which can be modeled as the integral of a three-dimensional Gaussian probability density function over a Euclidean ball. The authors propose an efficient and accurate method for evaluating this integral. It is based on the combination of two complementary strategies. For the first one, convergent series and numerical error bounds are computed. These bounds provide a tradeoff between the accuracy needed and the number of terms to compute. The second one, using divergent series, approximates the value of the integral with a good accuracy in most cases with only a few terms computed. Based on those two methods, a hybrid algorithm is tested on cases borrowed from the literature and compared against existing methods. Several numerical results and comparisons confirm both the efficiency and robustness of this paper’s approach.

Optimal Scheme Models with Two Kinds of Errors

In this paper, we propose stochastic scheme models with two kinds of errors for a computer system. A highly reliable computer system needs greatly to be backed up successfully in case of computer system crashes due to hardware failures and malicious software infections. We aim to determine appropriate backup times in computer processing of constant and random tasks. For this purpose, the trade-off between backup times and data losses due to errors is considered. The total execution times until the computing processing completes are obtained, and optimal backup policies to minimize them are derived analytically. Furthermore, we take up extended models of random tasks with [Formula: see text] sub-tasks and analyze them.

CO2 inside sI clathrate-like cages: Automated construction of neural network/machine learned guest-host potential and quantum spectra computations.

We present new results on the underlying guest-host interactions and spectral characterization of a CO2 molecule confined in the cages of the sI clathrate hydrate. Such types of porous solids raise computational challenges, as they are of practical interest as gas storage/capture materials. Accordingly, we have directed our efforts toward addressing their modeling in a proper manner, ensuring the quality of the input data and the efficiency of the computational approaches. The computational procedure for spectral simulations, within the multi-configurational time-dependent Hartree framework, involves the development of a fully coupled Hamiltonian, including an exact kinetic energy operator and a many-body representation of the potential, along with dipole moment surfaces, both obtained through neural network machine learning techniques. The resulting models were automatically trained and tested on extensive datasets generated by PW86PBE-XDM calculations, following the outcome of previous benchmark studies. Our simulations enable us to explore various aspects of the quantized dynamics upon confinement of CO2@D/T, such as constrained rotational-translational quantum motions and the averaged position/orientation of the CO2 guest in comparison to the experimental data available. Particularly notable are the distinct energy patterns observed in the computed spectra for the confined CO2 in the D and T cages, with a considerably high rotational-translational coupling in the CO2@T case. Leveraging reliable computations has proved instrumental, highlighting the sensitivity of the spectral features to the shape and strength of the potential interactions, with the explicit description of many-body contributions being significant.

Performance of multi-ribbed composite wall incorporating reactive powder concrete-filled steel tubular columns under axial compression

In this study, axial compression researches of an innovative composite shear wall, named multi-ribbed composite wall incorporating reactive powder concrete-filled steel tubular columns, were conducted using theoretical analyses as well as experimental and numerical investigations. This precast hybrid system embedded reactive powder concrete-filled steel tubular columns as boundary elements of multi-ribbed composite wall. A novel approach, namely the unified strength theory, was adopted in consideration of various materials diversity. The outcomes of unified strength theory were utilized to predict the ultimate compressive capacity of multi-ribbed composite wall equipped with reactive powder concrete-filled steel tubular columns. The proposed theoretical formulas were validated against the experimental results reported in this paper. Despite the fact that the calculated formula with b= 0 was obtained to predict the closest capacity value of the test specimen infilling ordinary concrete. The calculations with different values of b clearly indicated that the intermediate principal stress effect should be rationally considered. Experimental observations suggested that the frame column significantly contributed to improving the compressive performance throughout the entire process and maintained the wall integrity. Meanwhile, finite element models were developed using the ABAQUS program, followed by the elaboration of its numerical implementation. The numerical predictions of ten shear wall specimens infilling reactive powder concrete were found to be reasonably in agreement with the calculated results corresponding to b= 0.5. These findings revealed the characteristics of multiple defensive lines of "block-ribbed column-frame column" under axial compression. Following the successful validation of finite element models, parametric studies were carried out to evaluate the influences of the filled block compressive strength, steel tube wall thickness and height-width ratio. The results show that the axial compression capacity of multi-ribbed composite wall incorporating reactive powder concrete-filled steel tubular columns can be noticeably improved with an increase in block strength and tube thickness. The proposed composite wall demonstrates favorable cooperative working performance and desirable displacement ductility. Subsequently, the primary objective of this pilot study aimed at developing a reliable theoretical calculation formula and conducting numerical simulation verification of the innovative composite wall. The aforementioned conclusions are intended to provide insights for the guidance and optimization of engineering structures.

Reliability analysis of rolling bearings considering failure mode correlations

AbstractAs an essential mechanical component, a rolling bearing can exhibit multiple failure modes that may occur independently or in correlation with one another. A reliability analysis method that meticulously accounts for the interdependencies among various bearing failure modes is presented in this paper. The examination of wear and fatigue failure mechanisms in rolling bearings is carried out using the Physics of Failure (PoF) approach. By considering the influence of uncertain variables, the limit state functions for individual failure modes are formulated through the application of stress‐strength interference theory. In the context of wear failure, the limit state function is derived using working clearance as the characteristic quantity. On the other hand, the limit state function for fatigue failure is constructed with a focus on fatigue damage accumulation. The Copula function is used to characterize the relationship between wear failure and fatigue failure, and a reliability calculation model for rolling bearings is developed, considering the correlation between these failure modes. Ultimately, the proposed method is utilized to assess the reliability of bearings under two different sets of test conditions. The feasibility of this method is confirmed through test data, demonstrating its effectiveness in predicting bearing reliability. Through the application of this method, engineers can optimize bearing size parameters, select appropriate initial clearances, and enhance the reliability design of bearing.

Reliability analysis of A combination of [formula omitted] and [formula omitted] systems

In the paper, two-element (f,k) and <f,k> combined systems are developed, and two-kind combined reliability systems and some related new concepts such as irreducible structure and structure equivalence are introduced, which can be used not only in real practical situations, but also enrich the reliability contents. We proved that four-class combined reliability systems need to be considered actually, which facilitates the handling of these combined reliability systems. Meanwhile, a coordinate system with two axes, the number of total failed components and the number of maximal consecutive failed components, is introduced in the paper for representing the working and failed areas for the combined reliability systems, which brings out a useful tool for understanding the working and failure mechanisms, and system state transition ways, for the combined reliability systems. To summarize the reliability calculation, a procedure for calculations of the combined reliability systems is presented, which is an efficient guidance for these reliability computations. Finally, two numerical examples are given to illustrate the computation procedure in which the detailed steps, special on using Finite Markov Chain Imbedding Approach (FMCIA), are shown. We believe that the present paper can shed light on researches on combined reliability systems.

Four-gluon vertex from the Curci-Ferrari model at one-loop order

We compute the four-gluon vertex from the Curci-Ferrari model at one-loop order for a collinear configuration. Our results display a good agreement with the first lattice data for this vertex, released very recently []. A noteworthy novelty of our work is that we can provide analytical expressions for the four-gluon vertex in collinear configurations, together with a renormalization scheme that allows us to perform reliable perturbative computations even in the infrared regime. We observe an infrared suppression in the form factor associated with the tree-level four-gluon tensor with a possible zero crossing in the deep infrared which demands new lattice investigations to be confirmed. Moreover, we report an infrared divergence in the completely symmetric tensor form factor due to the ghost-loop contributions. These results come as predictions, since previous two-point correlations fix all the available parameters of the model, up to an overall constant factor. Published by the American Physical Society 2024

Wet cooling of air on plate finned tube heat exchangers

The objective of this paper is to provide the reliable calculation procedure for determining heat and mass flow rates for plate finned tube heat exchangers in dehumidification regimes that can be used easily in engineering practice. For this purpose, the experiments are conducted on two heat exchangers, and datasets for six more heat exchangers are used from literature. Comprehensive database is established with total of 637 sets of data, and it gathers 365 new measurement sets and 272 sets from open literature. The new calculation procedure predicts heat transfer rate and condensate flow rate where new methodology approach (based on the porous velocity, the ratio of characteristic surfaces and hydraulic diameter) is used. Predicted results show 5–10 % deviation for heat duty and up to 20 % for mass flow rate from experimental results, which is of importance to industrial practice.

Progression, reliability, predicting parameters and sample size calculations for quantitative fundus autofluorescence measures in ABCA4-related retinopathy

Background/aimsTo investigate the progression of quantitative autofluorescence (qAF) measures and the potential as clinical trial endpoint in ABCA4-related retinopathy.MethodsIn this longitudinal monocentre study, 64 patients with ABCA4-related retinopathy (age (mean±SD),...

A unified fractional flow framework for predicting the liquid holdup in two-phase pipe flows

Two-phase pipe flow occurs frequently in oil & gas industry, nuclear power plants, and CCUS. Reliable calculations of gas void fraction (or liquid holdup) play a central role in two-phase pipe flow models. In this paper we apply the fractional flow theory to multiphase flow in pipes and present a unified modeling framework for predicting the fluid phase volume fractions over a broad range of pipe flow conditions. Compared to existing methods and correlations, this new framework provides a simple, approximate, and efficient way to estimate the phase volume fraction in two-phase pipe flow without invoking flow patterns. Notably, existing correlations for estimating phase volume fraction can be transformed and expressed under this modeling framework. Different fractional flow models are applicable to different flow conditions, and they demonstrate good agreement against experimental data within 5% errors when compared with an experimental database comprising of 2754 data groups from 14 literature sources, covering various pipe geometries, flow patterns, fluid properties and flow inclinations. The gas void fraction predicted by the framework developed in this work can be used as inputs to reliably model the hydraulic and thermal behaviors of two-phase pipe flows.

Reliable and adaptive computation offload strategy with load and cost coordination for edge computing

There are several important factors to consider in edge computing systems including latency, reliability, power consumption, and queue load. Task replication requires additional energy costs in mobile edge offloading scenarios based on master-slave replication for fault tolerance. Excessive task offloading may lead to a sharp increase in the total energy consumption of the system including replication costs. Conversely, new tasks cannot enter the waiting queue and are lost, resulting in reliability issues. This paper proposes an adaptive task offloading strategy for balancing the edge node queue load and offloading cost (Lyapunov and Differential Evolution based Offloading schedule strategy, LDEO). The LDEO strategy innovatively customizes the Lyapunov drift-plus-penalty function by incorporating replication redundancy offloading costs to establish a balance model between the queue load and offloading cost. The LDEO strategy computes the optimal offloading decisions with dynamic adjustment characteristics by integrating a low-complexity differential evolution method, aiming to find the optimal balance point that minimizes the offloading cost while maintaining reliability performance. The experimental results show that compared with the existing strategies, LDEO strategy effectively reduces the redundancy of fault tolerance cost and the waiting time under the condition of ensuring that the task will not be discarded over time. It stabilizes the queue length in a reasonable range, controls the waiting time and loss rate of tasks, reduces the extra energy consumption paid by replication redundancy, and effectively realizes the optimal balance under multiple conditions.

Zirconium phase diagram from ab initio molecular dynamics

The paper presents analysis of precision of a phonon-based free energy calculation technique (Temperature Dependent Effective Potential method) in comparison with the thermodynamic integration method within classical molecular dynamics. It is shown that the use of the second order force constants is insufficient for accurate calculations of free energies at elevated temperatures due to noticeable anharmonic contributions to lattice vibrations. On the other hand, reliable calculations of the crystal phase equilibrium lines requires free energy accuracy better than 1–3 meV per atom. Based upon the obtained results the Temperature Dependent Effective Potential technique is applied to the detailed study of the solid-state Zr phase diagram from ab initio molecular dynamics that may be achieved if force constants up to the fourth order are used. The calculated zirconium phase diagram is in good agreement with experiment. The α−β−ω triple point was determined at P≈6.74 GPa, T≈837 K.

An efficient analysis method for system reliability of semi-rigid base asphalt pavement structure based on direct probability integral method

The structural design parameters of asphalt pavement inherently possess randomness. Reliability theory aids in considering the stochastic nature of these parameters in asphalt pavement design. However, as the number of considered random factors increases, the complexity of reliability calculation models and the consumption of computational resources also significantly escalate. To analyze the structural reliability of semi-rigid base asphalt pavements more efficiently and accurately, a method combining Weighted Kernel Density Estimation (Weighted-KDE) with Direct Probability Integration Method (DPIM) using sampling strategies was employed. Furthermore, integrating the equivalent extreme value principle, an asphalt pavement structural system reliability analysis method was proposed, considering multiple failure mode correlations. The numerical solution steps of this method are also outlined. Based on the typical semi-rigid asphalt pavement structure in China, this study utilized the elastic layer system method (the program Apbi) and a computational program developed in MATLAB to compare the efficiency and accuracy of calculating reliability between DPIM and the Monte Carlo Simulations (MCS). The computational outcomes indicate that, under the premise of selecting 18 random parameters, DPIM can achieve the required accuracy in assessing the reliability of asphalt pavement structure and system reliability. Analyzing how the number of samples affects the computational results reveals that using weighted-KDE and DPIM only needs a few hundred sample points to limit the relative error within 4 %, compared to the results obtained from 105 samples in MCS. The research findings demonstrate that DPIM incorporating the principle of equivalent extreme value events can serve as an efficient analytical approach for assessing the system reliability of asphalt pavement structures characterized by more complex failure modes.

UJI VALIDITAS KONTEN INSTRUMEN KEMAMPUAN REPRESENTASI MATEMATIS DALAM MENYELESAIKAN MASALAH BANGUN DATAR

Planar material is one of the materials that will be found again in several subsequent materials. In plane material, students' mathematical representation abilities need to be considered so that students are able to solve problems well. The aim of this research is to analyze the level of validity and reliability of the test instrument for junior high school students' mathematical representation abilities in solving flat shape problems. The research method used is a quantitative descriptive method. By using the Aiken's V formula, the expert validation results obtained an average V value of 0.93, which means that the questions have a very high level of validity and can be used. Meanwhile, the results of the reliability calculation show that the r value is 0.94, which means that the question has a very strong correlation coefficient and can be used. So this instrument can be used by teachers to measure the level of students' mathematical representation abilities in solving flat shape problems.

Dynamic optimization on quantum hardware: Feasibility for a process industry use case

The quest for real-time dynamic optimization solutions in the process industry represents a formidable computational challenge, particularly within the realm of applications like model-predictive control, where rapid and reliable computations are critical. Conventional methods can struggle to surmount the complexities of such tasks. Quantum computing and quantum annealing emerge as avant-garde contenders to transcend conventional computational constraints. We convert a dynamic optimization problem, characterized by an optimization problem with a system of differential–algebraic equations embedded, into a Quadratic Unconstrained Binary Optimization problem, enabling quantum computational approaches. The empirical findings synthesized from classical methods, simulated annealing, quantum annealing via D-Wave’s quantum annealer, and hybrid solver methodologies, illuminate the intricate landscape of computational prowess essential for tackling complex and high-dimensional dynamic optimization problems. Our findings suggest that while quantum annealing is a maturing technology that currently does not outperform state-of-the-art classical solvers, continuous improvements could eventually aid in increasing efficiency within the chemical process industry.