Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.

Influence of loudspeaker directivity on the measurement uncertainty

One of the most significant aspects of a building’s acoustic behavior is the airborne sound insulation of the room façades, since this determines the protection of its inhabitants against environmental noise. For this reason, authorities in most countries have established in their acoustic regulations for buildings the minimum value of sound insulation that must be respected for façades. In order to verify compliance with legal requirements it is usual to perform acoustic measurements in the finished buildings and then compare the measurement results with the established limits. Since there is always a certain measurement uncertainty, this uncertainty must be calculated and taken into account in order to ensure compliance with specifications. The most commonly used method for measuring sound insulation on façades is the so-called Global Loudspeaker Method, specified in ISO 140-5:1998. This method uses a loudspeaker placed outside the building as a sound source. The loudspeaker directivity has a significant influence on the measurement results, and these results may change noticeably by choosing different loudspeakers, even though they all fulfill the directivity requirements of ISO 140-5. This work analyzes the influence of the loudspeaker directivity on the results of façade sound insulation measurement, and determines its contribution to measurement uncertainty. The theoretical analysis is experimentally validated by means of an intermediate precision test according to ISO 5725-3:1994, which compares the values of sound insulation obtained for a façade using various loudspeakers with different directivities

Considerations in Determining the Cost of Measurement Uncertainty Associated with Dimensional Tolerances Verification

The verification of compliance with a design specification in manufacturing requires the use of metrological instruments to check if the magnitude associated with the design specification is or not according with tolerance range. Such instrumentation and their use during the measurement process, has associated an uncertainty of measurement whose value must be related to the value of tolerance tested. Most papers dealing jointly tolerance and measurement uncertainties are mainly focused on the establishment of a relationship uncertainty-tolerance without paying much attention to the impact from the standpoint of process cost. This paper analyzes the cost-measurement uncertainty, considering uncertainty as a productive factor in the process outcome. This is done starting from a cost-tolerance model associated with the process. By means of this model the existence of a measurement uncertainty is calculated in quantitative terms of cost and its impact on the process is analyzed.

Influence of loudspeaker directivity on the measurement uncertainty of the acoustic testing of facades.

One of the most significant aspects of a building?s acoustic behavior is the airborne sound insulation of the room façades, since this determines the protection of its inhabitants against environmental noise. For this reason, authorities in most countries have established in their acoustic regulations for buildings the minimum value of sound insulation that must be respected for façades. In order to verify compliance with legal requirements it is usual to perform acoustic measurements in the finished buildings and then compare the measurement results with the established limits. Since there is always a certain measurement uncertainty, this uncertainty must be calculated and taken into account in order to ensure compliance with specifications. The most commonly used method for measuring sound insulation on façades is the so-called Global Loudspeaker Method, specified in ISO 140-5:1998. This method uses a loudspeaker placed outside the building as a sound source. The loudspeaker directivity has a significant influence on the measurement results, and these results may change noticeably by choosing different loudspeakers, even though they all fulfill the directivity requirements of ISO 140-5. This work analyzes the influence of the loudspeaker directivity on the results of façade sound insulation measurement, and determines its contribution to measurement uncertainty. The theoretical analysis is experimentally validated by means of an intermediate precision test according to ISO 5725-3:1994, which compares the values of sound insulation obtained for a façade using various loudspeakers with different directivities. Keywords: Uncertainty, Façade, Insulation

A hybrid measurement systems analysis and uncertainty of measurement approach for industrial measurement in the light controlled factory

The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.

Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.

Size characterization of airborne SiO2 nanoparticles with on-line and off-line measurement techniques : an interlaboratory comparison study

Results of an interlaboratory comparison on size characterization of SiO2 airborne nanoparticles using on-line and off-line measurement techniques are discussed. This study was performed in the framework of Technical Working Area (TWA) 34—“Properties of Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS) in the project no. 3 “Techniques for characterizing size distribution of airborne nanoparticles”. Two types of nano-aerosols, consisting of (1) one population of nanoparticles with a mean diameter between 30.3 and 39.0 nm and (2) two populations of non-agglomerated nanoparticles with mean diameters between, respectively, 36.2–46.6 nm and 80.2–89.8 nm, were generated for characterization measurements. Scanning mobility particle size spectrometers (SMPS) were used for on-line measurements of size distributions of the produced nano-aerosols. Transmission electron microscopy, scanning electron microscopy, and atomic force microscopy were used as off-line measurement techniques for nanoparticles characterization. Samples were deposited on appropriate supports such as grids, filters, and mica plates by electrostatic precipitation and a filtration technique using SMPS controlled generation upstream. The results of the main size distribution parameters (mean and mode diameters), obtained from several laboratories, were compared based on metrological approaches including metrological traceability, calibration, and evaluation of the measurement uncertainty. Internationally harmonized measurement procedures for airborne SiO2 nanoparticles characterization are proposed.

Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

Uncertainties associated with the structural model and measured vibration data may lead to unreliable damage detection. In this paper, we show that geometric and measurement uncertainty cause considerable problem in damage assessment which can be alleviated by using a fuzzy logic-based approach for damage detection. Curvature damage factor (CDF) of a tapered cantilever beam are used as damage indicators. Monte Carlo simulation (MCS) is used to study the changes in the damage indicator due to uncertainty in the geometric properties of the beam. Variation in these CDF measures due to randomness in structural parameter, further contaminated with measurement noise, are used for developing and testing a fuzzy logic system (FLS). Results show that the method correctly identifies both single and multiple damages in the structure. For example, the FLS detects damage with an average accuracy of about 95 percent in a beam having geometric uncertainty of 1 percent COV and measurement noise of 10 percent in single damage scenario. For multiple damage case, the FLS identifies damages in the beam with an average accuracy of about 94 percent in the presence of above mentioned uncertainties. The paper brings together the disparate areas of probabilistic analysis and fuzzy logic to address uncertainty in structural damage detection.

Macroscopically Dissipative Systems with Underlying Microscopic Dynamics : Properties and Limits of Measurement

While some of the deepest results in nature are those that give explicit bounds between important physical quantities, some of the most intriguing and celebrated of such bounds come from fields where there is still a great deal of disagreement and confusion regarding even the most fundamental aspects of the theories. For example, in quantum mechanics, there is still no complete consensus as to whether the limitations associated with Heisenberg's Uncertainty Principle derive from an inherent randomness in physics, or rather from limitations in the measurement process itself, resulting from phenomena like back action. Likewise, the second law of thermodynamics makes a statement regarding the increase in entropy of closed systems, yet the theory itself has neither a universally-accepted definition of equilibrium, nor an adequate explanation of how a system with underlying microscopically Hamiltonian dynamics (reversible) settles into a fixed distribution.

Motivated by these physical theories, and perhaps their inconsistencies, in this thesis we use dynamical systems theory to investigate how the very simplest of systems, even with no physical constraints, are characterized by bounds that give limits to the ability to make measurements on them. Using an existing interpretation, we start by examining how dissipative systems can be viewed as high-dimensional lossless systems, and how taking this view necessarily implies the existence of a noise process that results from the uncertainty in the initial system state. This fluctuation-dissipation result plays a central role in a measurement model that we examine, in particular describing how noise is inevitably injected into a system during a measurement, noise that can be viewed as originating either from the randomness of the many degrees of freedom of the measurement device, or of the environment. This noise constitutes one component of measurement back action, and ultimately imposes limits on measurement uncertainty. Depending on the assumptions we make about active devices, and their limitations, this back action can be offset to varying degrees via control. It turns out that using active devices to reduce measurement back action leads to estimation problems that have non-zero uncertainty lower bounds, the most interesting of which arise when the observed system is lossless. One such lower bound, a main contribution of this work, can be viewed as a classical version of a Heisenberg uncertainty relation between the system's position and momentum. We finally also revisit the murky question of how macroscopic dissipation appears from lossless dynamics, and propose alternative approaches for framing the question using existing systematic methods of model reduction.

Thermal conductivity measurement of liquids in a microfluidic device

A new microfluidic-based approach to measuring liquid thermal conductivity is developed to address the requirement in many practical applications for measurements using small (microlitre) sample size and integration into a compact device. The approach also gives the possibility of high-throughput testing. A resistance heater and temperature sensor are incorporated into a glass microfluidic chip to allow transmission and detection of a planar thermal wave crossing a thin layer of the sample. The device is designed so that heat transfer is locally one-dimensional during a short initial time period. This allows the detected temperature transient to be separated into two distinct components: a short-time, purely one-dimensional part from which sample thermal conductivity can be determined and a remaining long-time part containing the effects of three-dimensionality and of the finite size of surrounding thermal reservoirs. Identification of the one-dimensional component yields a steady temperature difference from which sample thermal conductivity can be determined. Calibration is required to give correct representation of changing heater resistance, system layer thicknesses and solid material thermal conductivities with temperature. In this preliminary study, methanol/water mixtures are measured at atmospheric pressure over the temperature range 30-50A degrees C. The results show that the device has produced a measurement accuracy of within 2.5% over the range of thermal conductivity and temperature of the tests. A relation between measurement uncertainty and the geometric and thermal properties of the system is derived and this is used to identify ways that error could be further reduced.

Measurement of the mass transfer coefficient at workpiece surfaces in heat treatment furnaces

The mass (e.g. carbon) transfer coefficient at a workpiece surface is an important kinetic factor to control the heat treatment process of the workpiece and to evaluate heat treatment equipment. The coefficient can be calculated from the carbon concentration at the surface of a sample carburized in a carburizing furnace for a given time. Two common measurement methods which use a thin plate and employ a component as samples respectively are evaluated and compared for sensitivity and uncertainty. The comparison shows that the use of a component produces higher measurement precision and also has the advantage in measuring the carbon transfer coefficients at different treated positions. This method is then extended and discussed methodologically. Also two equations are proposed to calculate the carbon transfer coefficient and its uncertainty, respectively. This method is also applied to measure the carbon transfer coefficient in a fluidized bed heat treatment furnace.

Power Measurement Methodology for FPGA Devices

The efficiency of power optimization tools depends on information on design power provided by the power estimation models. Power models targeting different power groups can enable fast identification of the most power consuming parts of design and their properties. The accuracy of these estimation models is highly dependent on the accuracy of the method used for their characterization. The highest precision is achieved by using physical onboard measurements. In this paper, we present a measurement methodology that is primarily aimed at calibrating and validating high-level dynamic power estimation models. The measurements have been carefully designed to enable the separation of the interconnect power from the logic power and the power of the clock circuitry, so that each of these power groups can be used for the corresponding model validation. The standard measurement uncertainty is lower than 2% of the measured value even with a very small number of repeated measurements. Additionally, the accuracy of a commercial low-level power estimation tool has been also assessed for comparison purposes. The results indicate that the tool is not suitable for power estimation of data path-oriented designs.

An Alternative Method to Achieve Metrological Confirmation in Measurement Processes

Metrological confirmation process must be designed and implemented to ensure that metrological characteristics of the measurement system meet metrological requirements of the measurement process. The aim of this paper is to present an alternative method to the traditional metrological requirements about the relationship between tolerance and measurement uncertainty, to develop such confirmation processes. The proposed way to metrological confirmation considers a given inspection task of the measurement process into the manufacturing system, and it is based on the Index of Contamination of the Capability, ICC. Metrological confirmation process is then developed taking into account the producer risks and economic considerations on this index. As a consequence, depending on the capability of the manufacturing process, the measurement system will be or will not be in adequate state of metrological confirmation for the measurement process.