Bayesian assessment of the characteristic concrete compressive strength using combined vague-informative priors

Bayesian statistics can be used in order to determine the characteristic value of an unknown distribution based on a limited number of test samples. In cases where no previous test results are available, most often a Bayesian method based on vague prior information is used. The assumption of a vague or uniform prior results in a conservative approach in cases where only a limited number of test results are available. However, in case of concrete, prior information on concrete strength can be found in literature or country-specific prior information can be determined. Therefore, the use of a combined vague-informative prior is of particular interest, more specifically in the form of scaled inverse-χ² distributions that can be used for updating the standard deviation of the strength distribution of concrete. The differences between the use of a vague and a combined vague-informative prior are investigated through Monte Carlo simulations. Because prior information is taken into account, the uncertainty regarding the standard deviation of the predictive strength distribution is significantly reduced.     

Project affinity: the role of emotional attachment in construction projects

Although a wide range of human and organizational factors have been found to be important in the operation of projects, those determined by cultural variables are less well defined. One such influence concerns the notion of ‘project affinity’, the commitment and attachment by stakeholders and participants to projects and their outcomes. The temporal nature and transient involvement context provided by construction projects arguably presents a climate in which many participants are less likely to display commitment to its goals. This note is concerned with the issue of whether an attachment to a project's goals or to the completed product can lead to improved commitment among those involved. The concept of project affinity was developed in the course of a case study investigation in which operatives' attitudes towards the construction of a cancer research facility were explored. Because of the contribution of the facility to the future care of cancer sufferers, the concept of project affinity proved helpful in understanding a factor that appeared to be influencing the commitment of those involved. The results suggest a complementary concept to that of ‘project chemistry’ (c.f. Nicolini, 2002 Nicolini, D. 2002. In search of ‘project chemistry’.. Construction Management and Economics, 20: 167–77.  ).     

Structural frame selection: case studies of hybrid concrete frames

Hybrid concrete construction (HCC) uses a combination of in-situ and precast concrete and is an example of ‘mixed’ construction, which is the term for an innovative combination of different materials or framing methods. Examples of HCC exist in many countries to fulfil varying structural requirements, so it is not clear why HCC is not better used in the UK. Research was undertaken to gain a better understanding of the selection and use of HCC. Two case study projects were investigated to explore decision-making criteria, the roles of project participants and the challenges particular to HCC. The findings suggest that HCC is selected when measurable cost or programme advantages are not the most important criteria, but where other factors such as satisfying architectural requirements (finish, colour, etc.) or operational demands (such as internal comfort or maintenance) are critical. In both cases, clients and architects were found to be the most influential team members in the frame-selection process.

La construction en béton hybride (HCC) utilise une combinaison de béton in situ et de béton précoulé; c'est un exemple de ‘construction mixte’; cette expression définit une combinaison innovante de différents matériaux et méthodes de coffrage. Il existe des exemples de HCC dans de nombreux pays qui répondent à différentes exigences structurales; on peut donc difficilement expliquer pourquoi la HCC n'est pas mieux utilisée au Royaume-Uni. Des recherches ont été entreprises pour mieux comprendre les choix et les usages de la HCC. Deux études de cas ont été engagées, l'objectif étant d'explorer les critères décisionnels, le rôle des participants à ces projets et les défis particuliers propres à la HCC. Les résultats laissent à penser que la HCC est retenue lorsque le coût mesurable ou les avantages du programme ne sont pas les critères les plus importants et lorsque d'autres facteurs comme la réponse aux exigences architecturales (finition, couleur, etc.) ou d'autres exigences opérationnelles (comme le confort intérieur ou la maintenance) sont critiques. Dans les deux cas, les clients et les architectes sont apparus comme les membres les plus influents des équipes lors du processus de sélection du cadre.

Mots clés: processus de conception, construction en béton hybride, construction mixte, critères de performances, cadre structural     

Probabilistic evaluation of conformity criteria for concrete families

When only a limited number of test results are available, compressive strength results of concrete family members can be combined in order to enable conformity control on a sufficient number of test results. The principles behind the conformity control of concrete families are explained and an original probabilistic evaluation of conformity criteria for concrete families is introduced. For the calculation of the corresponding operating characteristics, some approximate formulae are presented. Additionally, Monte Carlo simulation techniques are used for more exact calculations. In this way, also autocorrelation between consecutive test results can be taken into account, using an autoregressive process. The current guidelines and conformity criteria for concrete families in EN 206-1 are evaluated and discussed, based on the AOQL concept. Different conformity criteria and transformation methods are described, evaluated and discussed.     

Camera Spectral Sensitivity and White Balance Estimation from Sky Images

Photometric camera calibration is often required in physics-based computer vision. There have been a number of studies to estimate camera response functions (gamma function), and vignetting effect from images. However less attention has been paid to camera spectral sensitivities and white balance settings. This is unfortunate, since those two properties significantly affect image colors. Motivated by this, a method to estimate camera spectral sensitivities and white balance setting jointly from images with sky regions is introduced. The basic idea is to use the sky regions to infer the sky spectra. Given sky images as the input and assuming the sun direction with respect to the camera viewing direction can be extracted, the proposed method estimates the turbidity of the sky by fitting the image intensities to a sky model. Subsequently, it calculates the sky spectra from the estimated turbidity. Having the sky \(RGB\) values and their corresponding spectra, the method estimates the camera spectral sensitivities together with the white balance setting. Precomputed basis functions of camera spectral sensitivities are used in the method for robust estimation. The whole method is novel and practical since, unlike existing methods, it uses sky images without additional hardware, assuming the geolocation of the captured sky is known. Experimental results using various real images show the effectiveness of the method.     

An Unbiased Method for Probabilistic Fire Safety Engineering,Requiring a Limited Number of Model Evaluations

The rise of Performance Based Design methodologies for fire safety engineering has increased the interest of the fire safety community in the concepts of risk and reliability. Practical applications have however been severely hampered by the lack of an efficient unbiased calculation methodology. This is because on the one hand, the distribution types of model output variables in fire safety engineering are not known and traditional distribution types as for example the normal and lognormal distribution may result in unsafe approximations. Therefore unbiased methods must be applied which make no (implicit) assumptions on the PDF type. Traditionally these unbiased methods are based on Monte Carlo simulations. On the other hand, Monte Carlo simulations require a large number of model evaluations and are therefore too computationally expensive when large and nonlinear calculation models are applied, as is common in fire safety engineering. The methodology presented in this paper avoids this deadlock by making an unbiased estimate of the PDF based on only a very limited number of model evaluations. The methodology is known as the Maximum Entropy Multiplicative Dimensional Reduction Method (ME-MDRM) and results in a mathematical formula for the probability density function (PDF) describing the uncertain output variable. The method can be applied with existing models and calculation tools and allows for a parallelization of model evaluations. The example applications given in the paper stem from the field of structural fire safety and illustrate the excellent performance of the method for probabilistic structural fire safety engineering. The ME-MDRM can however be considered applicable to other types of engineering models as well.     

Beyond platinum: synthesis,characterization, and in vitro toxicity of Cu(II)-releasing polymer nanoparticles for potential use as a drug delivery vector

The field of drug delivery focuses primarily on delivering small organic molecules or DNA/RNA as therapeutics and has largely ignored the potential for delivering catalytically active transition metal ions and complexes. The delivery of a variety of transition metals has potential for inducing apoptosis in targeted cells. The chief aims of this work were the development of a suitable delivery vector for a prototypical transition metal, Cu²⁺, and demonstration of the ability to impact cancer cell viability via exposure to such a Cu-loaded vector. Carboxylate-functionalized nanoparticles were synthesized by free radical polymerization and were subsequently loaded with Cu²⁺ via binding to particle-bound carboxylate functional groups. Cu loading and release were characterized via ICP MS, EDX, XPS, and elemental analysis. Results demonstrated that Cu could be loaded in high weight percent (up to 16 wt.%) and that Cu was released from the particles in a pH-dependent manner. Metal release was a function of both pH and the presence of competing ligands. The toxicity of the particles was measured in HeLa cells where reductions in cell viability greater than 95% were observed at high Cu loading. The combined pH sensitivity and significant toxicity make this copper delivery vector an excellent candidate for the targeted killing of disease cells when combined with an effective cellular targeting strategy.     

Nonuniform phase distribution in ultrasound speckle analysis. I. Background and experimental demonstration

In some cases, the statistical properties of the phase of ultrasound speckle in B-scan images differ from the uniform distribution characteristic exhibited by the fully developed speckle. This phenomenon has been noted when examining scattering structures with a somewhat regular spacing using wideband pulse excitation. It is shown by computer simulation and experiments on phantoms that when the mean scatterer spacing is equal to multiples of a half wavelength at the reference frequency of the receiver quadrature demodulator, the center of the echo phase distribution, plotted on the complex plane, will shift away from the origin. When the spacing is equal to an odd multiple of a quarter wavelength, the phase distribution will have a figure ;8' shape. By noticing those noncircular phase distributions while changing the demodulation frequency, the mean scatterer spacing can be estimated.