Damage Quantities Research Articles

A simulation approach for quantifying ballistic impact damage in ultra-high-performance concrete

In this work, we provide a hydrocode simulation model for high-velocity projectile impact against ultra-high-performance concrete targets and establish a methodology to extract damage quantities from the simulation results. In the parameter derivation process, published and own data stemming from material experiments, such as uniaxial, triaxial, and planar plate impact tests, are used as a starting point. To fill the systematic gaps of strength data for pressures of 1 GPa to 5 GPa and for fractured concretes, residual velocities of projectiles and qualitative target damage information from ballistic experiments with high-hard steel spheres are additionally used as a reference in parametric simulations. All criteria from the comparatively broad data basis are successfully reproduced by the simulation model simultaneously. The simulated damage quantities derived by the proposed extraction procedure are reasonable counterparts to the corresponding experimental measures from earlier published works, allowing a new quality of comparison between both worlds.

Emergence of critical state in granular materials using a variationally‐based damage‐elasto‐plastic micromechanical continuum model

AbstractThe mechanical response of granular materials, exemplified by frictional grain interactions, is characterized by a critical state in which deformation occurs without change of material volume or stresses when subjected to large shear deformation. In this work, a granular micromechanics approach (GMA) based continuum model is used to investigate the emergence of such a critical state. The continuum description is constructed through mechanical concepts based upon elastic and dissipation energies defined for a generic grain‐pair interaction. A hemivariational principle provides the basis for considering the evolution of damage and plasticity phenomena comprising grain‐pair contact loss and irreversible deformation. As a consequence, the Karush–Kuhn–Tucker (KKT)‐type conditions are derived, which give the evolution equations for the irreversible phenomena. Notably, in this derivation there is no invocation of flow rules and other similar assumptions of classical phenomenological continuum damage and plasticity. Further, Piola's ansatz is elaborated to kinematically connect granular micromechanics of grain‐pair to the continuum description. While the concept of critical state analysis has been handled with either phenomenological approaches or discrete numerical frameworks, in the present paper this concept is examined within a micromechanics‐based continuum description. The constitutive model is established and the coupled damage and plastic irreversible quantities are assessed. The critical state is shown to emerge as grain‐pair related damage and plastic evolution in a competitive/collaborative manner during the imposed loading path.

High-velocity impact experiments and quantitative damage evaluation for finite ultra-high-performance concrete targets

In this work, we aim at improved characterization of target damage occurring as the result of projectile impact against ultra-high-performance concrete (UHPC). For this purpose, we present the results of high-velocity impact experiments with spherical steel projectiles and finite-thickness UHPC targets of approximately 115 MPa compressive cylinder strength in the impact velocity range from approximately 600 m/s to 1500 m/s. The data set obtained from these experiments includes residual projectile velocities as well as qualitative and quantitative information on damage. Quantitative damage information is mainly extracted from digital 3D post mortem targets, which are produced by 3D-scanning. For all damage quantities, a dependence on the impact velocity and the target thickness is discussed and used to provide possible explanations for the origin of the particular type of damage. The large data set presented in this work can constitute the basis for a comprehensive and quantitative verification and validation of analytical, empirical, and numerical models that describe the perforation of UHPC targets in the investigated impact velocity range.

Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network

Neural network models have been widely applied in wind energy to enable data-driven modelling of turbine’s power, loads, damage, and other quantities in wind farm. They have shown advantages in the flexibility, robustness, and efficiency, as well as the ease of application. An important task in data-driven modelling of wind farm is the characterization of wake-induced effects within wind farm. Because of the large number of wind turbines in wind farm and the broad range of conditions required for power output assessment, it has become relevant to use computationally efficient surrogate models that are based on parameterizations of the wind farm layout. Previous studies on surrogate models of wake-induced effects have focused on parameterizations based on manually extracted features from the wind farm geometry. The present study applies an autoencoder neural network to automatically learn the features representing the wind farm layout. Specifically, two autoencoders are studied and compared. The autoencoder provides dimension reduction and feature learning that allow representing the entire wind farm layout in just a few latent variables, thus allowing efficient and accurate surrogate models of wake-induced effects. The outputs of the autoencoder, together with any ambient wind condition variables, serve as inputs to a standard feedforward neural network that predicts the wake-induced effects for any turbine in the wind farm. Our results show that the autoencoder provides an automatic and effective way to parameterize the wind farm geometry, and facilitates the building of efficient surrogate models that are capable of accurate modeling of wake-induced effects in a wind farm with arbitrary layout.

Composite salt corrosion deterioration characteristics and damage calculation models of concrete incorporated with corrosion inhibiting admixtures

This research investigation was an experimental study which was intended to verify the corrosion deterioration characteristics of C30 concrete incorporated with different dosage amounts of corrosion inhibiting admixtures (abbreviated as CIA in this study) under the environmental conditions of composite salt corrosion. Damage calculation models were proposed for the purpose of evaluating the influencing effects of the different dosage amounts. The experimentation results showed that when the content of CIA was 5%, the compressive strength of the concrete could be effectively improved. In addition, the average penetration depth and migration coefficient of the chloride ions, along with the macrocell current of the rebars, could be decreased. At the same time, the mass loss rates, relative dynamic elastic modulus losses, accumulative damage, and internal pore quantities of the examined concrete specimens incorporated with 5% CIA were observed to be significantly lower than those of ordinary concrete samples during every freezing-thawing cycle. Furthermore, the degree of anti-corrosion deterioration of the concrete was significantly promoted. This study's established chloride ions permeability models, rebars corrosion model, and concrete freezing-thawing damage models, were found to have the ability to more accurately reflect the variations of various performance indexes of the concrete in composite salt erosion environments. Therefore, it was considered that the established damage models could potentially provide valuable guidance for forecasting the life expectancy of concrete in the future.

Using Machine Learning Techniques for Asserting Cellular Damage Induced by High-LET Particle Radiation

This is a study concerning the use of Machine Learning (ML) techniques to ascertain the impacts of particle ionizing radiation (IR) on cell survival and DNA damage. Current empirical models do not always take into account intrinsic complexities and stochastic effects of the interactions of IR and cell populations. Furthermore, these models often lack in biophysical interpretations of the irradiation outcomes. The linear quadratic (LQ) model is a common way to associate the biological response of a cell population with the radiation dose. The parameters of the LQ model are used to extrapolate the relation between the dosage and the survival fraction of a cell population. The goal was to create a ML-based model that predicts the α and β parameters of the well known and established LQ model, along with the key metrics of DNA damage induction. The main target of this effort was, on the one hand, the development of a computational framework that will be able to assess key radiobiophysical quantities, and on the other hand, to provide meaningful interpretations of the outputs. Based on our results, as some metrics of the adaptability and training efficiency, our ML models exhibited 0.18 median error (relative root mean squared error (RRMSE)) in the prediction of the α parameter and errors of less than 0.01 for various DNA damage quantities; the prediction for β exhibited a rather large error of 0.75. Our study is based on experimental data from a publicly available dataset of irradiation studies. All types of complex DNA damage (all clusters), and the number of double-stranded breaks (DSBs), which are widely accepted to be closely related to cell survival and the detrimental biological effects of IR, were calculated using the fast Monte Carlo Damage Simulation software (MCDS). We critically discussed the varying importance of physical parameters such as charge and linear energy transfer (LET); we also discussed the uncertainties of our predictions and future directions, and the dynamics of our approach.

Damage identification of a single RC column subjected to barge impact based on optimization strategies

The safety of civil structures e.g. bridges and frame buildings are threatened by various inevitable hazards such as corrosion, fatigue and extreme loading e.g. earthquake, blast, impact. Such hazards may cause significant damage to structures and hence reduce their performance. This paper proposes two different strategies, i.e. the direct identification method which assumes that the information of loading which causes damage to a structure is not known and the indirect identification method which assumes that the loading causing structural damage is known to be generated by certain scenarios e.g. impact to identify the damage of civil structures after certain loading processes. Barge impact upon a single reinforced concrete (RC) column is considered in this paper to assess the prediction quality of the proposed strategies by comparing the identified damage quantities to the benchmark output data generated by an exact deformation analysis using the previously developed coupled multi-degree-of-freedom model (CMM). The proposed strategies show great potential for practical applications to damage identification of civil structures.

Improved multi-objective sensor optimization method for structural damage identification based on genetic algorithm

An improved multi-objective sensor location optimization method based on genetic algorithm is proposed. According to the analytic relationship between structural response, mode shapes and damage quantities, the sensitivity matrix of structural dynamic response containing both structural modal information and damage information is firstly constructed, and then the objective function of multi-objective sensor location optimization method is established according to the minimum identification error criterion and the principle of ill- posedness in the inverse problem. In addition, a multi-objective genetic algorithm, NSGA-II, is used to solve the optimal location of measurement points. Finally, a simply supported box girder bridge is studied for validating the proposed method. Numerical simulations show that the improved optimization method based on genetic algorithm can achieve the optimization goal better, and the measurement points optimized by the improved method can get better damage identification results at the same level of measurement noise.

Criminalidad de cuello azul, civilidad, ciudadanía y prevención. Reflexiones en torno a México

La criminalidad azul es una categoría intermedia en la clasificación de los delitos, de forma particular de los ilícitos de corte económico. Durante mucho tiempo se dio poca importancia a esta categoría, pues se pensaba más en el tamaño del daño (cantidades) y en la clasificación de los grandes delincuentes, y no en las consecuencias sociales producidas. En el México de hoy la crisis de inseguridad y control del delito ubica en el contexto criminológico a las clases económicas siempre vulneradas como nichos del delito ocupacional en función de sus precarias condiciones materiales de existencia y oportunidad de progreso. El delito económico se origina, desarrolla y vincula a otros delitos en las clases medias y trabajadoras, y es ahí, donde toma relevancia la criminalidad azul y las explicaciones para generar opciones de política criminal preventiva.

Experimental and Numerical Study on the Damage Evolution of Random Rock Joint Surface During Direct Shear Under CNL Condition

Because of the complex structure of joint surface morphology, the damage evolution of joint surface during direct shear was hardly investigated. In this paper, a series of direct shear tests were conducted on broken joint obtained by breaking rock cubes under constant normal loads condition. The surface morphologies of rock joints were tested by laser scanning technique and damage evolution and damage area of joint surface during direct shear were studied by means of numerical simulation. The damage quantities of rock joint during shear were defined as the volume of broken elements. Results of numerical modeling and laboratory tests show that, most damage of joint surface happens in the pre-peak stage and post-peak stage, and the damage area of joint surface enlarges greatly in post-peak stage. Damage evolution rate decreases with the shear stress in the residual stage and kept a rather low rate until the end of direct shear. The failure modes of convexes include two cases: friction failure in the top of peaks and shear broken in the root of peaks.

Iron NRT- and arc-displacement cross sections and their covariances

Displacement damage cross sections have been calculated for natural iron and its constituent individual isotopes based on the latest versions of the evaluated neutron data libraries ENDF/B-VIII.0 and TENDL-2017 using the conventional NRT and recently introduced athermal recombination-corrected (arc) displacement concepts. Their covariance matrices, which quantify the uncertainties and the associated energy-energy correlations, were assessed for the first time based on TENDL-2017 random data files representing the covariances of the underlying nuclear data. In addition to the nuclear data, the covariances due to the ion energy partition, the primary defect survival efficiency and the lattice threshold energy were also propagated to the damage quantities. The arc-dpa was computed employing all available results from molecular dynamics and binary collision simulations. The comparison of the spectrum-averaged arc-dpa with the few available measurements at fission reactors has demonstrated a reasonable agreement within the experimental and calculation uncertainties. The comparison with the current NRT-dpa standard, provided by ASTM up to 20 MeV but without uncertainty, has indicated differences up to 8% above 0.5 keV and 60% below.

Potential formation damage and mitigation methods using seawater-mixed acid to stimulate sandstone reservoirs

It has been a practice to use seawater to prepare hydrochloric acid for carbonate reservoir stimulation in the offshore operations where fresh water is relatively expensive or logistically impossible to use. However, compare with carbonate matrix stimulation, F− and secondary SiF62− are released into the solution using hydrofluoric acid to treat sandstone reservoirs. The released components will combine with Mg2+, Ca2+, Na+, and K+ ions in seawater. Large quantities and various types of precipitates are formed when critical scaling tendency was exceeded, which results in serious formation damage.In this research, artificial simulated seawater (salinity about 35‰) was mixed with mud acid (almost hydrofluoric acid) and multi-hydrogen acid (an organophosphonic acid complex). Chemical effects of current seawater-mixed acid were investigated using spectrophotometry methods. The chemical effects include acid composition and concentration, HCl volume, seawater dilution ratio, and inorganic salt on damage quantities during acid preparation and reaction. Effective mitigation methods favorable to the inhibition of precipitation were provided.Results show that fluoride precipitates including CaF2 and MgF2 can be effectively mitigated by decreasing the free F− concentration and the pH value, increasing the seawater dilution and adding the inorganic electrolytes to elevate the ionic strength of solution. Because the organic phosphonic acid forms complexes with the metal ions, precipitation mitigation capacity of the multi-hydrogen acid is stronger than that of the mud acid. A special and abnormal common-ion effect was discovered based on the multi-hydrogen acid system. The addition of calcium ions in the seawater-mixed multi-hydrogen acid solution produces a super-clear liquid system with the turbidity <30 FTU. Static simulation shows that fluorosilicate precipitates as products of the secondary reaction in acidizing are mainly determined by the dissolution ratio. The precipitates can be mitigated by adding proper amount of hydrochloric acid, increasing the concentration of ammonium chloride in acid, and using appropriate inhibitors such as organophosphonic acid HA and DA. According to a parametric analysis, a seawater-mixed acid system based on the synergistic reactions of acid effect, salt effect and complex effect was proposed to mitigate formation damage for the sandstone reservoir stimulation using seawater-mixed acid. Reactions between the acid and different minerals indicate that this acid system could remain clear and eliminate secondary deposition during acidizing treatment.

광변위 계측과 주행하중시험기법에 의한 교량구조의 손상도 추정기법

In this paper, a damage assessment technique using a moving load test and optical sensors was studied to overcome the deficiency of measurement information in bridge maintenance. Continuous displacements by applying the reciprocal theorem to the test can make the assessment simpler and more practical. Numerical and experimental studies were performed to show the efficiency and accuracy of the proposed technique as well as the possibility of a more realistic assessment for large infrastructure. The results showed that the assessed damage levels are quite accurate, and similar to the exact values in actual damage locations, even in the experiments. The proposed technique is useful and practical for both detecting damage locations and damage quantities.

Multimodal Nondestructive Testing Damage Quantification, Presentation, and Condition Rating of Bridge Decks

Advanced nondestructive testing (NDT) methods have become an effective and reliable way to evaluate the condition of bridge decks. Tools such as ground-penetrating radar, impact echo, and half-cell potentials are more frequently used to identify deck deterioration and evaluate condition. Although NDT methods are becoming more popular, the way in which NDT data are presented to bridge owners and maintenance personnel depends on the practitioner. Research has been conducted to develop methods to improve and standardize the presentation of multimodal NDT results. The primary goal of the current research was to make multimodal NDT a more effective and objective tool for asset management by improving the presentation of NDT results. This effort included the development of proper damage quantities to help budget repairs and asset management decisions; the accurate representation of deck condition with contouring software, which if used incorrectly can provide misleading information; and the use of NDT condition assessments to rate bridge decks through federally mandated condition rating systems. These federally mandated rating systems had their bases primarily in visual and sounding inspections as opposed to advanced NDT methods. Through study of the rating systems and discussions with asset managers, a method was developed to apply these ratings with multimodal NDT results. Although this method of condition rating was preliminary, the overarching goal of this work was to drive the NDT industry to focus its results for better assistance to asset managers, as well as to drive governing bodies to adapt the current rating systems for better compatibility with up-to-date technologies.

Creep in microelectronic solder joints: finite element simulations versus semi-analytical methods

The presence and change of thermal stresses in solders, which are used for mounting microelectronic packages on PC-boards, will eventually lead to material fatigue. The number of cycles to failure can be predicted from empirical relations of the Coffin–Manson type provided the increments of creep strains and/or energy densities are known, for example, from (rather extensive) FE-simulations. A special problem arises for newly developed solders for which the Coffin–Manson equations are not known yet and need to be established first from a combination of FE and costly reliability experiments. In any case the goal of the industry and research institutions is to replace experiments as much as possible by reliable predictive simulations. However, FE calculations, which are widely used to perform this task, can—as indicated—be rather time-consuming, due to the huge effort involved for component meshing, and due to the various non-linear constitutive equations required for the description of creep in solders and other package materials. In a previous paper (Muller and Hauck in Mech Adv Mater Struct, 15(6):485–489, (2008)) a simple analytical 1D-model was presented that allows computing characteristic damage quantities, such as creep strain and creep energy density, for different solder materials and different temperature profiles in a very efficient manner, provided a creep law is known. In this paper the proposed procedure is validated by comparison with results from detailed FE-simulations.

Structural Health Monitoring Systems for a Steel Structure Using an Ambient Vibration

This study aims at identifying the structural dynamic characteristics using an ambient vibration, and developing a health monitoring system which adopts damage detecting algorithms. One of the main problems for this system design is to measure long-time dynamic response signals and simultaneously estimate the structural dynamic properties. In order to be suitable for a long-time monitoring, we conduct an ambient dynamic testing for a 3-floor moment resistance steel structure and analyze structural dynamic characteristics using time domain estimation techniques. Also, a damage detecting test is performed to evaluate damage state by various detecting algorithms (modal correlation method (MAC &amp; COMAC), eigen-parameter change method). Finally, this paper suggests the optimal algorithms for the identification of the structural damage locations and damage quantities with all such comparisons. The algorithms presented in this paper prove to be applicable in structural health monitoring of structures.

A molecular dynamics study of void growth and coalescence in single crystal nickel

Molecular dynamics simulations using Modified Embedded Atom Method (MEAM) potentials were performed to analyze material length scale influences on damage progression of single crystal nickel. Damage evolution by void growth and coalescence was simulated at very high strain rates (10 8–10 10/s) involving four specimen sizes ranging from ≈5000 to 170,000 atoms with the same initial void volume fraction. 3D rectangular specimens with uniform thickness were provided with one and two embedded cylindrical voids and were subjected to remote uniaxial tension at a constant strain rate. Void volume fraction evolution and the corresponding stress–strain responses were monitored as the voids grew under the increasing applied tractions. The results showed that the specimen length scale changes the dislocation pattern, the evolving void aspect ratio, and the stress–strain response. At small strain levels (0–20%), a damage evolution size scale effect can be observed from the damage-strain and stress–strain curves, which is consistent with dislocation nucleation argument of Horstemeyer et al. [Horstemeyer, M.F., Baskes, M.I., Plimpton, S.J., 2001a. Length scale and time scale effects on the plastic flow of FCC metals. Acta Mater. 49, pp. 4363–4374] playing a dominant role. However, when the void volume fraction evolution is plotted versus the applied true strain at large plastic strains (>20%), minimal size scale differences were observed, even with very different dislocation patterns occurring in the specimen. At this larger strain level, the size scale differences cease to be relevant, because the effects of dislocation nucleation were overcome by dislocation interaction. This study provides fodder for bridging material length scales from the nanoscale to the larger scales by examining plasticity and damage quantities from a continuum perspective that were generated from atomistic results.

Damage correlations and fluctuations in 2D three-state Potts ferromagnet

We investigate, through the damage spreading method, the correlation length associated with the two-point correlation function between damage fluctuations, and the damage susceptibility of the square-lattice three-state Potts ferromagnet. We find that both quantities tend to diverge at the damage transition. These results can be interpreted as a first evidence of a possible fluctuation–dissipation-like relation between damage quantities in this model.

Damage, gradient of damage and principle of virtual power

A theory of continuum damage mechanics is developed within the framework of the principle of virtual power. Because the damage in a solid results from microscopic movements, we decided to include the power of these microscopic movements in the power of the internal forces. The microscopic velocities are related to the damage rate. The power of the internal forces we choose depends on the damage velocity and its gradient to take into account the interactions. Models issued from this theory are presented. They are coherent from the mechanical and mathematical points of view. The numerical computations show no mesh sensitivity. They describe with good agreement the main experimental properties. Concrete is chosen as an example to illustrate the theory. A model using two damage quantities is also presented. It yields the correct description of the unilateral phenomenon observed in concrete. Finally, an extension of the existing models is proposed to describe the fatigue damage behaviour.

Damage in concrete: the unilateral phenomenon

Because the damage in a solid results from microscopic movements, we decided to include the power of these microscopic movements in the power of the internal forces. The microscopic velocities are related to the damage rate. The power of the internal forces that we choose depends on the damage velocity and its gradient to take into account the interactions. Models from this theory are presented. They are coherent from the mechanical and mathematical points of view. The numerical computations show no mesh sensitivity. They describe with good agreement the main experimental properties. Concrete is chosen as an example to illustrate the theory. A model using two damage quantities is also presented. It gives a description of the unilateral phenomenon observed in concrete.