Material Uncertainties Research Articles

Development of gene-in-plasmid DNA reference materials certified by single-molecule counting.

The mole, the SI unit for measuring the amount of a substance, was redefined as a fixed number of entities. This definition enables straightforward quantification of substances by counting individual entities. Counting proves particularly effective for quantifying large and discrete biological entities such as DNA, proteins, viruses, and cells, which are challenging to quantify via traditional physical or chemical methods. In this study, we detail our approach to develop gene reference materials certified through single-molecule counting, which enables mole-traceable measurements. We quantified three plasmid DNA constructs, each carrying a specific gene of interest, via single-molecule counting. The resulting values were cross-validated via digital PCR and LC‒MS. Sequence impurities in the certified reference materials were quantified via single-molecule real-time sequencing, whereas fragment impurities were quantified via two-color digital PCR analysis. We precisely accounted for various sources of uncertainty, including measurement precision, weighing, homogeneity, and impurities, when estimating the total uncertainty of the reference materials. In conclusion, a practical format for gene-based DNA reference materials, a measurement method to achieve metrological traceability, and methods for quantifying fragments and sequence impurities were developed and implemented in this study. We anticipate that our gene-based DNA reference materials will serve as valuable higher-order standards for the calibration of other methods or reference materials for DNA quantification in a variety of bioanalytical applications.

Bending performance of nail laminated timber (NLT): Experiments and probabilistic modelling based on Monte Carlo simulation

Nail laminated timber (NLT) is gaining attention due to the advantages of low cost, simple fabrication and distinctive aesthetic. However, research is still limited on the design of NLT panels. To investigate the bending behavior of NLT, probabilistic modelling method based on Monte Carlo simulation was presented in this study. Firstly, two kinds of dimension lumber were respectively used as the laminations of the NLT specimens, and bending tests were conducted on both the laminations and the NLT. The failure modes and the bending properties of the NLT were analyzed. Then, a random sampling model for the laminations was developed considering the material uncertainty. The simulated laminations were virtually laminated into NLT, and large-scale modelling on the NLT was conducted. Finally, the modelling was validated by test results and parametric analysis was further carried out. Results showed that the probabilistic modelling is capable of predicting the mean value as well as the variability of the NLT’s bending properties. The bending strength of NLT is influenced primarily by the mean bending strength of its laminations. However, a lower mean value and higher variability in the bending strength of NLT would result from the laminations with lower variability in the modulus of elasticity, higher variability in the bending strength and poorer correlation between the bending strength and the modulus of elasticity.

Material parameter sensitivity analysis for intralaminar damage of laminated composites through direct differentiation

Understanding the effect of the material parameters variability on the mechanical response of laminated composites is of great importance for many engineering problems. Not only an accurate sensitivity analysis enables to estimate how much each parameter under consideration affects the response, but the linearization of the output provides also the possibility to, for example, use gradient-based optimization tools and to propagate in an inexpensive way the material uncertainties. In this paper, a material parameter sensitivity study is carried out in the context of continuum damage mechanics applied to predict intralaminar damage in laminated composites. The sensitivity w.r.t. the input material variables is estimated in a relatively inexpensive way from a single run of the Finite Element (FE) model. The results obtained provide a good understanding of the influence of the material parameters throughout the simulation.

Identification of material excavation difficulty and uncertainty analysis based on Bayesian deep learning

Accurately assessing the difficulty of material excavation is crucial for reducing excavator energy consumption, ensuring operational safety, and optimizing excavator efficiency. Addressing the challenges of uncertain and difficult-to-judge excavation conditions for underground materials, this paper proposes a Bayesian deep learning-based method that integrates excavation process data to identify excavation difficulty. Firstly, we constructed a deep learning model based on Bayesian theory and decomposed the uncertainty of the identification results into aleatory uncertainty and epistemic uncertainty. Next, through a mechanistic analysis of the interaction between materials and the excavator bucket during excavation, we identified the input features for the model. Finally, we validated the effectiveness of the method through experiments. The results show that the proposed method not only accurately identifies the excavation difficulty of the material but also quantifies and decomposes the uncertainty of the identification results, demonstrating both theoretical significance and practical application value.

The legality of roads in Chile, 1842–1969: A historical overview

Currently, no academic work examines the history of the legality of roads in Chile during its independent existence as a sovereign country. Addressing this gap in the literature, this paper focuses specially on the period from 1842 to 1969, when different actors articulated a set of guiding ideas about the duties of the state and the legal powers of the administrative authority in terms of planning, construction and management of road infrastructure that would allow connectivity between population centers and across regions, according to the ideas and resources available at their historical time. This historical overview of Chilean “road law” is done in the light of insights and questions of contemporary intellectual history and institutional history. In this regard, it is argued that the evolution of road infrastructure norms and institutions during the period under study can be divided into three historical regimes, based on their fundamental legislative milestones, guiding ideas, institutional settings, and strategies of state action: from 1842 to 1887, a period of a decentralized “minimal road state” with precarious roads characterized by both material and juridical uncertainty; from 1887 to 1920, the emergence of a “proto-developmentalist road state” intent on strengthening its grip on the nationwide road infrastructure; and from 1920 to 1969, a period of a “techno-developmentalist road state” that created a nationwide paved road network for the new technology of mobile vehicles.

Efficient Approximation of Varying Fiber Orientation States in Injection Molded Parts Under Consideration of Multiple Manufacturing Uncertainties

AbstractThe production of high-quality fiber reinforced polymer parts is an important aspect in several industrial areas. However, due to unavoidable uncertainties in material and manufacturing processes, the part quality scatters. One important aspect here is the fiber orientation, being crucial for the thermo-mechanical properties of the part and being influenced by the uncertain material state and process conditions. Process simulations are an important tool for predicting the fiber orientation, but state-of-the-art simulations are normally deterministic and represent only one specific case. Performing enough deterministic simulations to model manufacturing uncertainties requires high numerical effort. Therefore, this work presents methods to quickly and efficiently approximate the fiber orientation under varying material and process parameters, requiring only a few simulations as input. Different schemes for approximation are evaluated and compared with each other and with 3D process simulations.

Advanced Sobol sensitivity analysis of a 1:4-scale prestressed concrete containment vessel using an ANN-based surrogate model

The safety of nuclear power plants can be enhanced by performing sensitivity analyses to identify and evaluate factors that significantly impact their structural integrity. In this study, an artificial neural network-based surrogate model was developed using an experimentally validated finite element model. A Sobol sensitivity analysis was performed using this model to quantitatively assess the impact of material uncertainty on the internal pressure–displacement behavior of containment buildings at various internal pressure levels. The results indicate that the compressive strength of concrete and the prestressing force in the hoop direction critically influence the behavior of containment buildings, with their importance varying according to the internal pressure level. Furthermore, the proposed surrogate model can efficiently substitute for expensive and complex finite element analyses, enabling effective exploration of the multidimensional uncertainty space and quantitative assessment of the major factors affecting structural behavior. The process presented herein facilitates the quantification of factors under various uncertainty scenarios.

A Comparative Study of Precast and Cast-in Place Concrete in Construction Home Project by Life Cycle Cost Analysis

Construction industry plays a significant role in economic growth, and the industry will continue to grow with the economic expansion. However, the industry is known for its labor-intensiveness, In order to shorten construction time and address labor issues, developers have explored new systems of construction such as a precast system. This paper is to present a comparative study of precast and cast-in place concrete system in construction home project by life cycle cost analysis by dividing project period into 3 phase (Preparing phase, Construction phase and O&M phase). In modelling life cycle costs, sensitivity analysis and Monte Carlo simulation will be employed to incorporate uncertainty of material and labor costs into the proposed model. The study also found that in 6 home projects, there have risk factors that impact to life cycle cost by using sensitivity analysis are construction cost, major repair and minor repair. The result from this study is life cycle cost from precast and cast -in place systems

Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework

In this study, the spatial variability of materials is incorporated into the static analysis of functionally graded sandwich nanoplates to achieve higher accuracy. Utilising a modified point estimation method and the radial point interpolation method, we develop a novel stochastic meshfree computational framework to deal with the material uncertainty. Higher-order shear deformation theory is employed to establish the displacement field of the plates. The elastic modulus of ceramic and metal (Ec and Em) are treated as separate random fields and discretized through the Karhunen-Loève expansion (KLE) method. To improve the performance of procedure, the Wavelet-Galerkin method is introduced to solve the second type of Fredholm integral equation. Subsequently, substituting the random variables obtained by KLE into the stochastic computational framework, a high accuracy stochastic response of structures can be acquired. By comparing computed findings with those of Monte Carlo simulation, the accuracy and efficiency of developed framework are verified. Moreover, the results indicate that the plate's deflection exhibits varying sensitivities to the random fields Ec and Em. Also, the sandwich configuration as well as power-law exponents affect the stochastic response of structures. These findings offer valuable insights for the optimized design of functionally graded sandwich nanoplates.

Static analysis using flexibility disassembly perturbation for material nonlinear problem with uncertainty

Nonlinear finite element analysis of large-scale structures usually requires a lot of calculation cost, because it is necessary to repeatedly inverse the modified stiffness matrix caused by nonlinearity in the calculation process. When considering the uncertainty in materials, the calculation of the nonlinear analysis will be more unbearable. To improve the computational efficiency, this work develops a new method for nonlinear analysis with material uncertainty based on flexibility disassembly perturbation (FDP) approach. The FDP is an algorithm that can quickly calculate the inverse of a stiffness matrix. The basic idea of the proposed method is to introduce the FDP formula into Newton-Raphson iteration method to accelerate the nonlinear iterative calculation. Three numerical examples, one statically determinate structure and two statically indeterminate structures, are used to verify the accuracy and efficiency of the proposed method. The results show that the calculation time of the proposed method is far less than that of the existing complete analysis and combined approximation algorithms. In terms of computational accuracy, for statically determinate structures, the proposed algorithm can obtain exact solutions that are identical to the complete analysis results, while for statically indeterminate structures, the proposed algorithm can obtain approximate solutions that are very close to the complete analysis results.

Navigating Competing Discourses in Mixed-Citizenship Romantic Relationships

ABSTRACT The United States has an increasing number of people from around the world, which has led to a rise in mixed-citizenship romantic relationships. Yet, these relationships and family structures remain significantly understudied. Mixed-citizenship romantic relationships, referring to individuals in a romantic relationship who hold or previously held different citizenships, are faced with various unique experiences in comparison to same-citizenship romantic relationships (e.g. immigration rhetoric, filing of paperwork, and financial obligations). Grounded in relational dialectics theory, this study examined how discourses operate and inform the meaning of mixed-citizenship romantic relationships, as well as the ways discourses compete. Through 15 semi-structured interviews, results reveal two discourses: A Discourse of Love is the Driving Force and A Discourse of Material Uncertainty. Moreover, discourses competed for dominance and, at times, intersected to create new meanings. Findings illuminate implications of talk for members of mixed-citizenship relationships, and offer suggestions for practitioners in communicating about these consequences.

Collapse fragility analysis of historical masonry buildings considering in-plane and out-of-plane response of masonry walls.

This paper explores the seismic fragility assessment of historical masonry buildings in the context of performance-based earthquake engineering, using multiple-record incremental dynamic analyses (MR-IDA). The methodology is applied to two case studies, the first being a stiff monumental structure, and the second a tall and slender masonry building. Both case studies are modelled in the OpenSees software using three-dimensional macroelements that account for the in-plane (IP) and out-of-plane (OOP) response of masonry walls. Simultaneously, the numerical models account for the influence of non-linear connections in floor-to-wall interfaces and wall-to-wall interlocking. The record-to-record variability induced by the random nature of the ground motion is addressed through earthquake selection consistent with the variability of European hazard. Ground motion records are normalised at a uniform level of seismic intensity to be sequentially increased for the computation of IDA curves. Once IDA curves and fragility functions are derived, the failure results are thoroughly discussed. The fragility functions accounting for the uncertainties arising from the record-to-record variability are contrasted against the results of the seismic assessments affected by multiple sources of uncertainty in material and modelling parameters from a previous study. Finally, the fragility curves derived from the methodology presented herein are directly compared with fragility functions from probabilistic seismic demand analysis (PSDA). Overall, IDA-based fragility functions are found to provide more conservative predictions than the ones obtained from the cloud-based approach using unscaled records.

Safety analysis of temporary anchorage system for immersed tube in Shenzhen–Zhongshan Link

In the construction of the Shenzhen–Zhongshan Link, a temporary anchorage system, distributed uniformly along the pipe wall, has been employed. To assess the safety and reliability of this system, a combined method utilizing numerical analysis and model experiments was applied to study the safety of the temporary anchorage system and the reliability of the tension rods. Firstly, an overall model of the caisson segment based on GINA rebound force was established to analyze the stress state of the entire system. Secondly, a comprehensive numerical analysis and model experiment verification were conducted for the single tensioning system, revealing its failure mode and safety margin. The results indicate that the tension rod systems are uniformly stressed at an average of 444 kN during underwater jointing, with a safety factor of 1.94. At this point, the maximum von Mises stresses appearing at the front plate corners and the lower edge of the U-groove, with stress values of 181.8 MPa and 172.4 MPa, and safety factors of 1.54 and 1.71, respectively. When the tension rod force reaches 940 kN, the tensioning system reaches its bearing limit, with initial yielding occurring at the front plate corners. Model experiments were conducted to verify the theoretical analysis results, under a test load of 444 kN, the stresses at the front plate corners and the lower edge of the U-groove were 159.6 and 195.9 MPa, respectively. As the test load increased to 940 kN, these stresses reached 390 and 389 MPa, exhibiting good agreement with the numerical analysis. Considering the uncertainty of loads and materials, a reliability analysis of the tension rods was conducted, yielding a reliability index of 4.34, meeting the secondary safety standard. Based on the comprehensive analysis, it can be concluded that the temporary anchorage system in the caisson segments of the Shenzhen–Zhongshan Link exhibits excellent safety margins.

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions.Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Surrogation and Bayesian updating of a finite element model of the Leaning Tower of Pisa

Numerical models play a crucial role in the study and understanding of cultural heritage structures, serving as valuable tools for predicting their behavior under diverse and prospective scenarios. They are however affected by various uncertainties, which impact can be mitigated through the calibration of model parameters. For heritage structures, where testing is usually restricted to the use of non-destructive techniques, and often unable to directly assess the inherent heterogeneity of the materials, a calibration approach can prove particularly useful to obtain a working model. This work applies a Bayesian model updating procedure to material-related uncertainties affecting a recently developed finite element model of the Leaning Tower of Pisa also comprising the underlying soil layers. A general Polynomial Chaos Expansion-based surrogation of the model was employed to evaluate the sensitivity of modal properties and ease the computational burden that comes with the probabilistic framing of the updating problem. Material property distributions were then updated, taking advantage of modal data from a newly installed sensor network which allowed the most up-to-date dynamic identification of the monument. The results represent the first probabilistic model-based assessment of material uncertainties in a three-dimensional finite element model of the Leaning Tower of Pisa. They shed some light into the value of specific modal information, while the use of analytical surrogation paves the way for the future design of a real-time updating procedure for monitoring and damage detection.

Numerical analysis of uncertain frequency of rotating composites using NURBS-based isogeometric HSDT approach: Rim-driven configuration

This study delves into the impact of material and fabrication uncertainties on the natural frequencies of rim-driven rotating structures. Utilizing a higher-order shear deformation theory (HSDT), an isogeometric analysis (IGA) model predicts these frequencies. Sensitivity analysis via a radial basis function network (RBFN) model, validated with Monte Carlo simulation, highlights parameter influence. Parametric investigations unveil sensitivity patterns and influential parameters. Employing a stochastic approach, the study compares the effects of random material properties on the free vibration response of rotating and non-rotating plates. Additionally, the RBFN-based surrogate model assesses reliability parameters concerning resonance failure in rim-driven rotating composite structures.

Investigating the Impact of Blunt Force Trauma: A Probabilistic Study of Behind Armor Blunt Trauma Risk.

Evaluating Behind Armor Blunt Trauma (BABT) is a critical step in preventing non-penetrating injuries in military personnel, which can result from the transfer of kinetic energy from projectiles impacting body armor. While the current NIJ Standard-0101.06 standard focuses on preventing excessive armor backface deformation, this standard does not account for the variability in impact location, thorax organ and tissue material properties, and injury thresholds in order to assess potential injury. To address this gap, Finite Element (FE) human body models (HBMs) have been employed to investigate variability in BABT impact conditions by recreating specific cases from survivor databases and generating injury risk curves. However, these deterministic analyses predominantly use models representing the 50th percentile male and do not investigate the uncertainty and variability inherent within the system, thus limiting the generalizability of investigating injury risk over a diverse military population. The DoD-funded I-PREDICT Future Naval Capability (FNC) introduces a probabilistic HBM, which considers uncertainty and variability in tissue material and failure properties, anthropometry, and external loading conditions. This study utilizes the I-PREDICT HBM for BABT simulations for three thoracic impact locations-liver, heart, and lower abdomen. A probabilistic analysis of tissue-level strains resulting from a BABT event is used to determine the probability of achieving a Military Combat Incapacitation Scale (MCIS) for organ-level injuries and the New Injury Severity Score (NISS) is employed for whole-body injury risk evaluations. Organ-level MCIS metrics show that impact at the heart can cause severe injuries to the heart and spleen, whereas impact to the liver can cause rib fractures and major lacerations in the liver. Impact at the lower abdomen can cause lacerations in the spleen. Simulation results indicate that, under current protection standards, the whole-body risk of injury varies between 6 and 98% based on impact location, with the impact at the heart being the most severe, followed by impact at the liver and the lower abdomen. These results suggest that the current body armor protection standards might result in severe injuries in specific locations, but no injuries in others.

Quantifying quanta: Determining emission rates from clinical data

It is important to quantify uncertainty in the viable genomic material encapsulated in the respiratory particles emitted by infected people so that it can be converted into an emission rate as a function of respiratory and metabolic activities and used to estimate the probability of infection for an indoor scenario. Clinical measurements of viral loads for SARS-CoV-2 made using infection surveys, Gesundheit-II samplers, and human challenge studies are evaluated and a mathematical model is derived to estimate the quantum emission rate as a function of the genomic and viable viral loads. Modelled emission rates for SARS-CoV-2 agree with clinical data above detection limits. The viral load is found to vary over at least 6 orders of magnitude because it is person and time dependent, and contingent on many other factors that are difficult to quantify. It is similarly large for other respiratory pathogens. Therefore, the genomic and viable-virion emission rates display similar heterogeneity. When emission rates are used to estimate absolute infection risk using the Wells-Riley model, the predictions are so uncertain that they cannot be used in any meaningful way to provide useful quantitative guidance for designing indoor spaces.

Multi‐objective reliability‐based robust design for a rock tunnel support system using Pareto optimality

AbstractIn the context of rock material and modeling uncertainties, the optimization of rock tunnel support systems is often conducted by selecting the most cost‐effective solution among several feasible options that typically rely on the engineer's experience, potentially leading to overlooking the most optimal design. To improve such a limitation, this paper presents a multi‐objective reliability‐based robust design, considering the cost, safety, and design robustness systematically while maintaining the computational efficiency. In this framework, the uncertainty‐based reliability constrains is performed using the first‐order reliability method (FORM) and an improved Hasofer–Lind–Rackwits–Fiessler recursive algorithm (iHLRF‐x). The design robustness, in terms of sensitivity index (SI), is evaluated using the normalized gradient of the system response to the noise factors, which can be efficiently obtained from the output of FORM analysis. Then, the Pareto front revealing the tradeoff between multiple objectives can be directly generated using the proposed optimization framework. To illustrate the effectiveness of this procedure, a set of the optimal design combinations of the shotcrete thickness and installation position for the exampled rock tunnel are obtained, and new perspectives pertaining the success of the reliability‐based robust designs are provided.

Surrogate models for seismic and pushover response prediction of steel special moment resisting frames

For structural engineers, existing surrogate models of buildings present challenges due to inadequate datasets, exclusion of significant input variables impacting nonlinear building response, and failure to consider uncertainties associated with input parameters. Moreover, there are no surrogate models for the prediction of both pushover and nonlinear time history analysis (NLTHA) outputs. To overcome these challenges, the present study proposes a novel framework for surrogate modelling of steel structures, considering crucial structural factors impacting engineering demand parameters (EDPs). The first phase involves the development of a process by which 30,000 random steel special moment resisting frames (SMRFs) for low to high-rise buildings are generated, considering the material and geometrical uncertainties embedded in the design of structures. In the second phase, a surrogate model is developed to predict the seismic EDPs of SMRFs when exposed to various earthquake levels. This is accomplished by leveraging the results obtained from phase one. Moreover, separate surrogate models are developed for the prediction of SMRFs’ essential pushover parameters. Various machine learning (ML) methods are examined, and the outcomes are presented as user-friendly GUI tools. The findings highlighted the substantial influence of pushover parameters as well as beams and columns’ plastic hinges properties on the prediction of NLTHA, factors that have been overlooked in prior studies. Moreover, CatBoost has been acknowledged as the superior ML technique for predicting both pushover and NLTHA parameters for all buildings. This framework offers engineers the ability to estimate building responses without the necessity of conducting NLTHA, pushover, or even modal analysis which is computationally intensive.