B-Spline FEM for Time-Harmonic Acoustic Scattering and Propagation

in Journal of Theoretical and Computational Acoustics (2019), 27

We study the application of a B-splines Finite Element Method (FEM) to time-harmonic scattering acoustic problems. The infinite space is truncated by a fictitious boundary and second-order Absorbing ... [more ▼]

We study the application of a B-splines Finite Element Method (FEM) to time-harmonic scattering acoustic problems. The infinite space is truncated by a fictitious boundary and second-order Absorbing Boundary Conditions (ABCs) are applied. The truncation error is included in the exact solution so that the reported error is an indicator of the performance of the numerical method, in particular of the size of the pollution error. Numerical results performed with high-order basis functions (third or fourth order) showed no visible pollution error even for very high frequencies. To prove the ability of the method to increase its accuracy in the high frequency regime, we show how to implement a high-order Padé-type ABC on the fictitious outer boundary. The above-mentioned properties combined with exact geometrical representation make B-Spline FEM a very promising platform to solve high-frequency acoustic problems. [less ▲]

Batch control of the master equation: a linear programming approach

Scientific Conference (2008)

A Bayesian framework to identify random parameter fields based on the copula theorem and Gaussian fields: Application to polycrystalline materials

in Journal of Applied Mechanics (in press)

For many models of solids, we frequently assume that the material parameters do not vary in space, nor that they vary from one product realization to another. If the length scale of the application ... [more ▼]

For many models of solids, we frequently assume that the material parameters do not vary in space, nor that they vary from one product realization to another. If the length scale of the application approaches the length scale of the micro-structure however, spatially fluctuating parameter fi elds (which vary from one realization of the fi eld to another) can be incorporated to make the model capture the stochasticity of the underlying micro-structure. Randomly fluctuating parameter fields are often described as Gaussian fields. Gaussian fi elds however assume that the probability density function of a material parameter at a given location is a univariate Gaussian distribution. This entails for instance that negative parameter values can be realized, whereas most material parameters have physical bounds (e.g. the Young's modulus cannot be negative). In this contribution, randomly fluctuating parameter fi elds are therefore described using the copula theorem and Gaussian fi elds, which allow di fferent types of univariate marginal distributions to be incorporated, but with the same correlation structure as Gaussian fields. It is convenient to keep the Gaussian correlation structure, as it allows us to draw samples from Gaussian fi elds and transform them into the new random fields. The bene fit of this approach is that any type of univariate marginal distribution can be incorporated. If the selected univariate marginal distribution has bounds, unphysical material parameter values will never be realized. We then use Bayesian inference to identify the distribution parameters (which govern the random fi eld). Bayesian inference regards the parameters that are to be identi fied as random variables and requires a user-defi ned prior distribution of the parameters to which the observations are inferred. For the homogenized Young's modulus of a columnar polycrystalline material of interest in this study, the results show that with a relatively wide prior (i.e. a prior distribution without strong assumptions), a single specimen is su ciffient to accurately recover the distribution parameter values. [less ▲]

Bayesian inference to identify parameters in viscoelasticity

in Mechanics of Time-Dependent Materials (2017)

This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii ... [more ▼]

This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii) to show that this influence decreases for an increasing number of measurements and (iii) to show how different types of experiments influence the identified parameters and their uncertainties. The standard linear solid model is the material description of interest and a relaxation test, a constant strain-rate test and a creep test are the tensile experiments focused on. The experimental data are artificially created, allowing us to make a one-to-one comparison between the input parameters and the identified parameter values. Besides dealing with the aforementioned issues, we believe that this contribution forms a comprehensible start for those interested in applying BI in viscoelasticity. [less ▲]

Bayesian statistical inference on the material parameters of a hyperelastic body

in Proceedings of the ACME-UK 2016 24th Conference on Computational Mechanics (2016, March 31)

We present a statistical method for recovering the material parameters of a heterogeneous hyperelastic body. Under the Bayesian methodology for statistical inverse problems, the posterior distribution ... [more ▼]

We present a statistical method for recovering the material parameters of a heterogeneous hyperelastic body. Under the Bayesian methodology for statistical inverse problems, the posterior distribution encodes the probability of the material parameters given the available displacement observations and can be calculated by combining prior knowledge with a finite element model of the likelihood. In this study we concentrate on a case study where the observations of the body are limited to the displacements on the surface of the domain. In this type of problem the Bayesian framework (in comparison with a classical PDE-constrained optimisation framework) can give not only a point estimate of the parameters but also quantify uncertainty on the parameter space induced by the limited observations and noisy measuring devices. There are significant computational and mathematical challenges when solving a Bayesian inference problem in the case that the parameter is a field (i.e. exists infinite-dimensional Banach space) and evaluating the likelihood involves the solution of a large-scale system of non-linear PDEs. To overcome these problems we use dolfin-adjoint to automatically derive adjoint and higher-order adjoint systems for efficient evaluation of gradients and Hessians, develop scalable maximum aposteriori estimates, and use efficient low-rank update methods to approximate posterior covariance matrices. [less ▲]

Beyond Digitizing

in Burrows, Simon; Roe, Glenn (Eds.) Digitizing Enlightenment: Digital Humanities and the Transformation of Eighteenth-century Studies (2020)

A Big Data Demand Estimation Model for Urban Congested Networks

in Transport and Telecommunication (2020)

Biomechanical properties of five different currently used implants for open-wedge high tibial osteotomy

in Journal of Experimental Orthopaedics (2015), 2(14),

Background: As several new tibial osteotomy plates recently appeared on the market, the aim of the present study was to compare mechanical static and fatigue strength of three newly designed plates with ... [more ▼]

Background: As several new tibial osteotomy plates recently appeared on the market, the aim of the present study was to compare mechanical static and fatigue strength of three newly designed plates with gold standard plates for the treatment of medial knee joint osteoarthritis. Methods: Sixteen fourth-generation tibial bone composites underwent a medial open-wedge high tibial osteotomyn(HTO) according to standard techniques, using five TomoFix standard plates, five PEEKPower plates and six iBalance implants. Static compression load to failure and load-controlled cyclic fatigue failure tests were performed. Forces, horizontal and vertical displacements were measured; rotational permanent plastic deformations, maximal displacement ranges in the hysteresis loops of the cyclic loading responses and dynamic stiffness were determined. Results: Static compression load to failure tests revealed that all plates showed sufficient stability up to 2400 N without any signs of opposite cortex fracture, which occurred above this load in all constructs at different load levels. During the fatigue failure tests, screw breakage in the iBalance group and opposite cortex fractures in all constructs occurred only under physiological loading conditions (<2400 N). The highest fatigue strength in terms of maximal load and number of cycles performed prior to failure was observed for the ContourLock group followed by the iBalance implants, the TomoFix standard (std) and small stature (sm) plates. The PEEKPower group showed the lowest fatigue strength. Conclusions: All plates showed sufficient stability under static loading. Compared to the TomoFix and the PEEKPower plates, the ContourLock plate and iBalance implant showed a higher mechanical fatigue strength during cyclic fatigue testing. These data suggest that both mechanical static and fatigue strength increase with a wider proximal T-shaped plate design together with diverging proximal screws as used in the ContourLock plate or a closed-wedge construction as in the iBalance design. Mechanical strength of the bone-implant constructs decreases with a narrow T-shaped proximal end design and converging proximal screws (TomoFix) or a short vertical plate design (PEEKPower Plate). Whenever high mechanical strength is required, a ContourLock or iBalance plate should be selected. [less ▲]

Biopharm - the Influence of Macro-substrates & Conditioning on Pharmaceutical Removal Rates by Moving Bed Biofilm Reactors

Doctoral thesis (2015)

Organic micropollutants with endocrine disruptive properties are present in the aquatic environment. A major part of their emission is caused by municipal wastewater treatment plants (WWTPs). For this ... [more ▼]

Organic micropollutants with endocrine disruptive properties are present in the aquatic environment. A major part of their emission is caused by municipal wastewater treatment plants (WWTPs). For this reason, a vast amount of research has been undertaken to remove xenobiotics from municipal wastewater by developing post-treatment technologies with some success. However, these technologies cause considerable environmental costs due their high demand for electrical energy implicating an increase in CO2 emissions. Consequently, existing biological treatments need first to be better understood and subsequently optimized regarding xenobiotic removal before post-treatments are employed. The study focused on the fate of xenobiotics during biological wastewater treatment. In particular, metabolic strategies of bacteria degrading pharmaceuticals were investigated within moving bed biofilm reactor (MBBR) processes. Two main objectives were tracked. On the one hand, it was to unfold the impact of macro-substrates in terms of type and molecular complexity on the activity of microorganisms and consequently pharmaceutical degradation performance. On the other hand, the study was set out to explore the adaptation of metabolic means regarding exoenzymes and consortia structure during continuous (long-term) exposure to pharmaceuticals. Accordingly, the ability to increase microbial competences during pharmaceutical short-term pulses was the general target of investigation. Both conditions continuous substance flow and short-term peak loads of xenobiotics are believed to occur in urban WWTPs. A pilot MBBR was set up next to a domestic WWTP. The pilot treated municipal sewage and served as inoculation reservoir for biofilm carriers used for in-depth laboratory experiments. The latter comprised six lab-scale MBBRs featuring flow through operation under controlled conditions regarding temperature, dissolved oxygen, pH, influent flow and influent load. The reactors were conditioned over four weeks with a synthetic sewage providing substrates and micro-nutrients in a similar manner as expected under real conditions. Biofilm was monitored by respirometry and a series of enzyme assays using fluorogenic substrates to capture esterase, phosphatase, alpha- and beta-glucosidase and aminopeptidase activity. All enzymes are essential during organic carbon metabolism. An array of macro-substrates with different molecular complexity was triggering individual enzyme activity profiles. After conditioning, 12 pharmaceuticals being subject to a range of anticipated metabolic pathways and degradation rates were spiked into the MBBRs. Their degradation kinetics were measured by liquid chromatography coupled with tandem mass spectrometry (LC MS/MS). Pseudo first-order kinetics revealed substrate related fingerprints and showed that readily biodegradable substrate leads generally to good pharmaceutical degradation performance compared to synthetic sewage with a mixture of several high molecular organic substrates. The latter was designed to induce the greatest metabolic effort of tested substrates before microbial uptake occurs. However, single substrates triggering exoenzyme activity in a more targeted manner such as maltose and cellobiose showed positive impact on the pseudo first-order rate coefficients of particular pharmaceuticals such as atenolol and diclofenac. Accordingly, alpha-glucosidase activity was found to be directly proportional to atenolol degradation kinetics. Phylogenetic characterisation of DNA and RNA involving state-of-the-art 16S ribosomal rRNA gene amplification and sequencing techniques was used to explore community structures. Prokaryote diversity in lab-scale MBBRs was in agreement to previous studies which investigated microbial consortia in full-scale systems. Multivariate analysis revealed that bacteria are adapting their active gene pool when the beta-blocker atenolol is continuously present with a concentration in ug/L range. Differential analysis unfolded that the prokaryotic genera Delftia and Lysobacter were thereby exclusively benefiting from the exposure to atenolol. Yet, compared to the influence of macro-substrates, biomass conditioning (training) with atenolol and diclofenac had no notable impact on the degradation performance of pharmaceutical short-term pulses. The outstanding comprehensive character of the study which encompassed sophisticated experimental design and powerful analytical tools from different scientific domains uncovered some interesting insights in xenobiotic degradation processes. The results finally show how biomass is reacting towards the presence of primary carbon sources and organic micro-pollutants. The outcomes highlight the importance of WWTP influent characterization being indicative of metabolic activity and therefore degradation capacity of xenobiotics. The study further suggests that xenobiotic metabolism and co-metabolism co-exist during biological treatment processes. Co-metabolism is the decisive actor when adaption time is relatively short as it was the case during the lab-scale experiments compared to real conditions. Further, the study indicates some potential of process enhancement of WWTPs ranging from straightforward implementations such as external carbon sources to more elaborated processes of bioaugmentation. [less ▲]

Blood flow simulation using smoothed particle hydrodynamics: application to thrombus generation

Scientific Conference (2016, March 31)

Blood flow rheology is considered to be a complex phenomenon. In order to understand the characteristics of blood flow, it is important to identify key parameters those influence the flow behaviour of ... [more ▼]

Blood flow rheology is considered to be a complex phenomenon. In order to understand the characteristics of blood flow, it is important to identify key parameters those influence the flow behaviour of blood. Further, the characterisation of blood flow will also enable us to understand flow parameters associated with physiological conditions such as atherosclerosis. Thrombosis plays a crucial role in atherosclerosis, or to stop bleeding when a blood vessel is injured. This article focuses on using meshless particle-based Lagrangian numerical technique named smoothed particles hydrodynamic (SPH) method to study the flow behaviour of blood and to explore flow condition that induces formation of thrombus in a blood vessel. Due its simplicity and effectiveness, the SPH method is employed here to simulate the process of thrombogenesis under the influence of various blood flow parameters. In the present SPH simulation, blood is modelled by particles that have characteristics of plasma and of platelets. To simulate coagulation of platelets which forms thrombus, the adhesion and aggregation process of platelets are modelled by an effective inter-particle force model. With these models, platelet motion in the flowing blood and platelet adhesion and aggregation are effectively coupled with viscous blood flow. In this study, the adhesion and aggregation of blood particles are performed on a bifurcated artery under a various low Reynolds number scenarios. The results are compared with experimental results and a good agreement is found between the simulated and experimental results. [less ▲]