Rod seals are one of the most critical components of hydraulic systems. However, the fundamental physics of seal behavior is still poorly understood and the seal designers have virtually no analytical tools with which to predict the behavior of potential seal designs. In pursuit of a comprehensive physics based seal analysis/ design tool, in this work, a multi-scale multi-physics (MSMP) seal model is developed. The model solves the transient problem involving macro-scale viscoelastic deformation mechanics, macro-scale contact, micro-scale two phase fluid mechanics in the sealing zone, micro-scale asperity contact mechanics and micro-scale deformation mechanics of the sealing edge in a strongly coupled manner. The model takes into account surface roughness, mixed lubrication, cavitation and two phase flow, transient squeeze film effects and the dynamic operation as well as the effect of macro/micro/nano scale viscoelasticity. A hybrid finite element-finite volume-statistical computational framework is developed to solve the highly coupled multi-physics interactions of the MSMP model simultaneously. Surface characterization experiments are performed to extract the parameters like RMS roughness, asperity density, autocorrelation length and asperity radius needed by MSMP. To remove the high frequency noise without removing the high frequency real surface features, a wavelet transform based adaptive surface extraction method is implemented. Dynamic mechanical analysis (DMA) is performed to extract the macro-scale viscoelastic parameters of the seal. Through atomic force microscopy (AFM) experiments, the local micro/nano scale elastic moduli were found to be varying within two orders of magnitude higher than the bulk of the polymer. Significant differences in local stiffness, adhesion and the relaxation time scales of individual surface asperities were also observed. With the MSMP model, dynamic seal performance was analyzed. The results confirmed the mixed lubrication and the effect of surface roughness. Thicker fluid films during instroke and cavitation during the outstroke were found to be important for non-leakage. Seal behavior was a function of the complex dual dependence on the time varying sealed pressure and hydrodynamic effects. Viscoelasticity is seen to critically affect the leakage and friction characteristics. It produces thicker fluid films and produces a significant increase in Poiseuille component of flow during instroke. Ignoring viscoelasticity leads to under-prediction of the time required to reach the zero leakage state. Several high pressure - high frequency sealing applications were analyzed. In such applications, a new phenomenon of "secondary contact" was observed. Viscoelastic creep was seen to critically affect the contact pressure and hence the friction characteristics. In high frequency applications, viscoelasticity induced significant differences in Poiseuille flow and friction force from cycle to cycle. Cycle frequency was seen to play an important role in governing visco-elastohydrodynamics and the leakage of such seals. The seals need to be designed by considering the relationship between relaxation time scales of the polymer and the cycle frequencies. Study also revealed the presence of characteristics like "critical temperature" and "critical frequency". Using the multi-physics modeling capability of MSMP framework, several novel seal designs using smart materials like piezo-ceramic embedded polymers are proposed and analyzed. The MSMP computational framework developed here has a great potential to be used as a stand-alone seal design and analysis software in academic and industrial research.

The mechanical reliability of electronic components has become harder and harder to predict due to the use of composite materials. One of the key issues is creating an accurate model of the delamination mechanism, which consists in the separation of two different bounded materials. This phenomenon is a very challenging issue that is investigated in the Nano Interface Project (NIP), in which this thesis is involved. The macroscopic adhesion force is governed by several parameters described at different length scales. Among these parameters, the roughness profile of the interface has a pronounced influence. The main difficulty for an accurate delamination characterization is then investigating the effects of this roughness profile and the modifications it implies for the overall cohesion. The objective of the NIP is to develop an interface model for the numerical testing of electronic components in a finite element software. The problem is that a direct modeling of all the mechanisms described previously is really expensive in term of computation time, if possible at all. This difficulty is increased by the huge mismatch of the mechanical properties of the materials in contact. A scale transition method is therefore required, which is provided by homogenization. The idea is to consider the delamination at a wider scale. Rather than modeling the whole roughness profile, the adhesion at the interface will be described by homogenized, or macroscopic, parameters extracted from a representative model at the micro-scale, the RVE. This thesis will deal with the determination of these homogenized parameters.

Early detection of breast cancer on screening mammograms is crucial to reduce mortality rates. Computer-aided detection (CADe) systems for mammography are of great importance since they have been shown to positively assist radiologists in detecting early cancer. However, one area where CADe systems for mammography need improvement is in the early detection and annotation of spiculated lesions, which may represent invasive malignancies, and hence, early detection is crucial. Spicule annotation is important since it can yield useful discriminative information about the suspect lesion location on the mammogram and can also provide rich visual evidence to the interpreting radiologist to make the right follow-up decision. However, spicule annotation is a non-trivial task since spicules are fine scale curvilinear structures that are often not clearly visible amidst the surrounding breast parenchyma. The first contribution of this dissertation is an active contour algorithm called snakules for the annotation of spicules on mammography. Observer studies with experienced radiologists to evaluate the performance of snakules demonstrate the potential of the algorithm as an annotation tool that could be used to augment existing spiculated mass CADe systems. Mammography suffers from a major limitation: the 3-D to 2-D projection process results in anatomical noise due to overlapping of out of plane tissue structures, which hinders both radiologists and CADe systems in finding early cancers. This has motivated the development of 3-D breast imaging in the form of breast tomosynthesis, stereoscopic (stereo) mammography, and breast computed tomography (CT) to augment mammography for early cancer detection. Our second contribution is a novel computational stereo model for estimating a dense disparity map from a pair of stereo mammograms. This problem is very important since this is the first step towards elucidating 3-D information that is essential for conducting 3-D digital analysis on the stereo mammogram images. Nearly all of the 3-D structural information of interest on a stereo mammogram exists as a complex network of multi-layered, heavily occluded curvilinear structures, which is unlike what is seen on optical images of the real world. Our proposed stereo model employs a new singularity index as a constraint in a global optimization framework to obtain better estimates of disparity along critical curvilinear structures. The new singularity index is an important contribution of this work. In-depth theoretical analyses and experiments on several real world images demonstrate the efficacy of the index for detecting multi-scale curvilinear structures. Experiments on synthetic images with known ground truth and on real stereo mammograms highlight the advantages of the proposed stereo model over the canonical stereo model. The final contribution of this dissertation is an observer study, which demonstrates the feasibility of viewing breast tomosynthesis projection images stereoscopically. Unlike stereo mammogram images, each tomosynthesis projection image is acquired at a much lower dose. Stereo viewing of tomosynthesis projection images has the potential to reveal the 3-D structure of the breast, unlike the current cine or slice-by slice viewing modes. The results from our study suggest that stereo viewing could be a viable reading mode for breast tomosynthesis data in the future. / text

Understanding, monitoring and managing savanna ecosystems require characterizing both functional and structural properties of vegetation. Due to functional diversity and structural heterogeneity in savannas, characterizing these properties using remote sensing is methodologically challenging. Focusing on the semi-arid savanna in the central Kalahari, the objective of this dissertation was to combine in situ data with multi-scale satellite imagery and two image analysis approaches (i.e. Multiple Endmember Spectral Mixture Analysis (MESMA) and Object Based Image Analysis (OBIA)) to : (i) determine the superior method for estimating fractional photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS) when high spatial resolution multispectral imagery is used, (ii) examine the suitability of OBIA for mapping vegetation morphology types using a Landsat TM imagery, (iii) examine the impact of changing spatial resolution on magnitude and accuracy of fractional cover and (iv) examine how the fractional cover magnitude and accuracy are spatially associated with vegetation morphology. Using the GeoEye-1 imagery, MESMA provided more accurate fractional cover estimates than OBIA. The increasing segmentation scale in OBIA resulted in a consistent increase in error. While areas under woody cover produced lower errors even at coarse segmentation scales, those with herbaceous cover provided low errors only at the fine segmentation scale. Vegetation morphology type mapping results suggest that classes with dominant woody life forms attained higher accuracy at fine segmentation scales, while those with dominant herbaceous vegetation reached higher classification accuracy at coarse segmentation scales. Contrarily, for bare areas accuracy was relatively unaffected by changing segmentation scale. Multi-scale fractional cover mapping results indicate that increasing pixel size caused consistent increases in variance of and error in fractional cover estimates. Even at a coarse spatial resolution, fPV was estimated with higher accuracy compared to fNPV and fBS. At a larger pixel size, in areas with dominant woody vegetation, fPV was overestimated at the cost of mainly underestimating fBS; in contrast, in areas with dominant herbaceous vegetation, fNPV was overestimated with a corresponding underestimation of both fPV and fBS. These results underscore that structural and functional heterogeneity in savannas impact retrieval of fractional cover, suggesting that comprehensive remote sensing of savannas needs to take both structure and cover into account. / text

Physical and chemical heterogeneities cause the porous media transport parameters to vary with scale, and between these two types of heterogeneities geological heterogeneity is considered to be the most important source of scale-dependence of transport parameters. Subsurface processes associated with chemical alterations result in changing reservoir properties with interlinked spatial and temporal scale, and there is uncertainty in the evolution of those properties and the chemical processes. This dissertation provides a framework and procedures to quantify the spatiotemporal scaling characteristics of reservoir attributes and transport processes in heterogeneous media accounting for chemical alterations in the reservoir. Conventional flow scaling groups were used to assess their applicability in scaling of recovery and Mixing Zone Length (MZL) in presence of chemical reactivity and permeability heterogeneity through numerical simulations of CO₂ injection. It was found out that these scaling groups are not adequate enough to capture the scaling of recovery and transport parameters in the combined presence of chemical reactivity and physical heterogeneity. In this illustrative example, MZL was investigated as a function of spatial scale, temporal scale, multi-scale heterogeneity, and chemical reactivity; key conclusions are that 1) the scaling characteristics of MZL distinctly differ for low permeability and high permeability media, 2) heterogeneous media with spatial arrangements of both high and low permeability regions exhibit scaling characteristics of both high and low permeability media, 3) reactions affect scaling characteristics of MZL in heterogeneous media, 4) a simple rescaling can combine various MZL curves by merging them into a single MZL curve irrespective of the correlation length of heterogeneity, and 5) estimates of MZL (and consequently predictions of oil recovery) will fluctuate corresponding to displacements in a permeable medium whose lateral length is smaller than the correlation length of geological formation. We illustrate and extend the procedure of estimating Representative Elementary Volume (REV) to include temporal scale by coupling it with spatial scale. The current practice is to perform spatial averaging of attributes and account for residual variability by calibration and history matching. This results in poor predictions of future reservoir performance. The proposed semi-analytical technique to scale-up in both space and time provides guidance for selection of spatial and temporal discretizations that takes into account the uncertainties due to sub-processes. Finally, a probabilistic particle tracking (PT) approach is proposed to scale-up flow and transport of diffusion-reaction (DR) processes while addressing multi-scale and multi-physics nature of DR mechanisms and also maintaining consistent reservoir heterogeneity at different levels of scales. This multi-scale modeling uses a hierarchical approach which is based on passing the macroscopic subsurface heterogeneity down to the finer scales and then returning more accurate reactive flow response. This PT method can quantify the impact of reservoir heterogeneity and its uncertainties on statistical properties such as reaction surface area and MZL, at various scales. / text

An interesting problem in computer vision is that of image registration, which plays an important role in many vision-based recognition and motion analysis applications. Of particular interest among data registration problems are multimodal image registration problems, where the image data sets are acquired using different imaging modalities. There are several important issues that make real-world multimodal registration a difficult problem to solve. First, images are often characterized by illumination and contrast non-uniformities. Such image non-uniformities result in local minima along the convergence plane that make it difficult for local optimization schemes to converge to the correct solution. Second, real-world images are often contaminated with signal noise, making the extraction of meaningful features for comparison purposes difficult to accomplish. Third, feature space differences make performing direct comparisons between the different data sets with a reasonable level of accuracy a challenging problem. Finally, solving the multimodal registration problem can be computationally expensive for large images. This thesis presents a probabilistic complex phase representation (PCPR) objective function for registering images acquired using different imaging modalities. A probabilistic multi-scale approach is introduced to create image representations based on local phase relationships extracted using complex wavelets. An objective function is introduced for assessing the alignment between the images based on a Geman-McClure error distribution model between the probabilistic complex phase representations of the images. Experimental results show that the proposed PCPR objective function can provide improved registration accuracies when compared to existing objective functions.

Zirconium and its alloys have been extensively used in both heavy and light water nuclear reactors. Like other Hexagonal Close-Packed (HCP) materials, e.g. magnesium, zirconium alloys develop different textures during manufacturing process which result in highly anisotropic materials with different responses under different loading conditions. Slip and twinning are two major deformation mechanisms during plastic deformation of zirconium. This dissertation uses various experimental techniques and a crystal plasticity scheme in the finite element framework to study deformation mechanisms in HCP materials with an emphasis on twinning in Zircaloy-2. The current study is presented as a manuscript format dissertation comprised of four manuscript chapters. After a literature review in Chapter 2, Chapter 3 reports steps in developing a crystal plasticity finite element user material subroutine for modeling deformation in Zircaloy-2 at room temperature. It is shown in Chapter 3 that the developed rate dependent equations are capable of capturing evolution of key features, e.g., texture, lattice strains, and twin volume fractions, during deformation by twinning and slip. Chapter 4 reports various assumptions and approaches in modeling twinning where results are compared against neutron diffraction measurements from the literature. It is shown in Chapter 4 that the predominant twin reorientation scheme can explain texture development more precisely than the other schemes discussed. Chapter 5 and 6 are two connected chapters where in the first one the formation of twins is studied statistically and in the second one, local inception and propagation of twins is studied. Numerical results of these two chapters are compared with 2D electron backscattered diffraction measurements, both carried out by the author and from the literature. Results from these two connected chapters emphasize the important role of grain boundary geometry and stress concentration sites on twin nucleation and growth. The four manuscript chapters are followed by summarizing conclusions and suggestions for future work in Chapter 7. / Thesis (Ph.D, Mechanical and Materials Engineering) -- Queen's University, 2012-04-23 11:50:33.751

Doctor of Philosophy (PhD) / The aim of this thesis is to understand what drives the evolution of industrial networks and how such understanding can be used to stimulate sustainable development. A complex adaptive systems perspective has been adopted to analyse the complex interaction between organisational behaviour and industrial network evolution. This analysis has formed the basis for the development of a modelling approach that allows for quantitative exploration of how different organisational perceptions about current and future uncertainty affect their behaviour and therefore the network evolution. This analysis results in a set of potential evolutionary pathways for an industrial network and their associated performance in terms of sustainable development. Subsequently, this modelling approach has been used to explore the consequences of interventions in the network evolution and to identify robust interventions for stimulating sustainable development of industrial networks. The analysis, modelling approach and development of interventions has been developed in the context of a bioenergy network in the region of KwaZulu-Natal in South Africa. Industrial networks are an important aspect of today’s life and provide many goods and services to households and individuals all over the world. They consist of a large number of autonomous organisations, where some organisations contribute by transforming or transacting natural resources, such as oil, agricultural products or water, while other organisations contribute to networks by providing information or setting regulation or subsidies (local or national governments) or by influencing decision making processes of other organisations in networks (advocacy groups). Throughout the process from natural resource to product or service, industrial networks have important economic, environmental and social impacts on the socio-economic and biophysical systems in which they operate. The sum of complex interactions between organisations affects the rate in which natural resources are used, environmental impacts associated with transformation and transaction of resources and social impacts on local communities, regions or countries as a whole. The aim of this thesis is to understand how industrial networks evolve and how they can be stimulated towards sustainable development. The first question that has been addressed in this thesis is how to understand the complex interaction between organisational behaviour and industrial network evolution. Organisational behaviour is affected by many functional and implicit characteristics within the environment in which the organisation operates, while simultaneously the environment is a function of non-linear relationships between individual organisational actions and their consequences for both the function and structure of the network. This thesis has identified four different characteristics of industrial networks that affect organisational behaviour: 1) Functional characteristics 2) Implicit behavioural characteristics 3) Implicit relational characteristics 4) Implicit network characteristics. Functional characteristics are those characteristics that are formally recognised by all organisations within an industrial network and which affect their position within the network. Examples of functional characteristics are the price and quantity of resources available, the location and distance of organisations within a network, infrastructure availability or regulation. Implicit characteristics, on the other hand, are those characteristics that impact the decision making process of organisations, but which are not formally part of the network. From an organisational perspective, implicit characteristics are the rules, heuristics, norms and values that an organisation uses to determine its objectives, position and potential actions. Implicit relational characteristics, most importantly trust and loyalty, affect an organisations choice between potential partners and implicit network characteristics are those social norms and values that emerge through social embeddedness. Collectively, these functional and implicit characteristics and their interactions determine the outcome of organisational decisions and therefore the direction of the industrial network evolution. The complex interaction between these large numbers of characteristics requires quantitative models to explore how different network characteristics and different interactions result in different network evolutions. This thesis has developed an agent-based simulation model to explore industrial network evolutions. To represent the multi-scale complexity of industrial networks, the model consists of four scales. Each scale represents different processes that connect the functional and implicit characteristics of an industrial network to each other. The two basic scales represent the strategic actions of the organisations on the one hand and the industrial network function and structure on the other. The third scale represents the processes that take place within the mental models of organisations describing how they make sense of their environment and inform their strategic decision making process. The fourth scale represents the social embeddedness of organisations and how social processes create and destroy social institutions. The model has been developed such that it allows for exploring how changes in different network characteristics or processes affect the evolution of the network as a whole. The second question that has been addressed in this thesis is how to evaluate sustainable development of different evolutionary pathways of industrial networks. First of all, a systems approach has been adopted to explore the consequences of an industrial network to the larger socio-economic and biophysical system in which the network operates. Subsequently, a set of structural indicators has been proposed to evaluate the dynamic performance of industrial networks. These four structural indicators reflect the efficiency, effectiveness, resilience and adaptiveness of industrial networks. Efficiency and effectiveness relate to the operational features by which industrial networks provides a particular contribution to society. Resilience and adaptiveness relate to the system’s capacity to maintain or adapt its contribution to society while under stress of temporary shocks or permanent shifts, respectively. Finally, different multi-criteria decision analysis (MCDA) tools have been applied to provide a holistic evaluation of sustainable development of industrial networks. The third important question that is addressed in this thesis is how to systematically explore the potential evolutionary pathways of an industrial network, which has led to the development of agent-based scenario analysis. Agent-based scenario analysis systematically explores how industrial network evolutions might evolve depending on the perceptions of organisations towards the inherent uncertainty associated with strategic decision making in networks. The agent-based scenario analysis consists of two steps. Firstly, analysts develop a set of coherent context scenarios, which represents their view on the context in which an industrial network will operate within the future. For a bioenergy network, for example, this step results in a set of scenarios that each represent a coherent future of the socio-economic system in which the network might evolve. The second step is the development of a set of ‘agent scenarios’. Each agent-based scenario is based on a different ‘mental model’ employed by organisations within the network about how to deal with the inherent ambiguity of the future. The organisational perspective towards uncertainty is of major importance for the evolution of industrial networks, because it determines the innovative behaviour of organisations, the structure of the network and the direction in which the network evolves. One the one hand, organisations can ignore future ambiguity and base their actions on the environment that they can observe in their present state. On the other extreme, organisations can adopt a view that the future is inherently uncertain and in which they view social norms and values more important than functional characteristics to make sense of their environment. The mental models are differentiated according to two dimensions: 1) different mental representation of the world and 2) different cognitive processes that can be employed to inform strategic actions. Along these dimensions, different processes can be employed to make sense of the environment and to inform decision making. The thesis has shown that by systematically exploring the different perceptions possible, an adequate understanding of the different evolutionary pathways can be gained to inform the evaluation and development of interventions to stimulate sustainable development. The final part of this thesis has applied the analysis and methodology developed throughout this thesis to a bioenergy network in the province of Kwazulu-Natal in South Africa. The bioenergy network consists of a set of existing sugar mills with large quantities of bagasse, a biomass waste product, available. Bagasse is currently burned inefficiently to produce steam for the sugar mills, but can potentially be used for the production of green electricity, biodiesel, bioethanol or gelfuel. All of these products have important consequences for the region in terms of associated reductions in CO2 emissions, electrification of and/or energy provision for rural households and local economic development of the region. This thesis has modelled strategic decisions of the sugar mills, the existing electricity generator, potential independent energy producers, local and national governments and how their actions and interactions can lead to different evolutionary pathways of the bioenergy network. The agent-based scenario analysis has been used to explore how different perceptions of organisations can lead to different network evolutions. Finally, the model has been used to explore the consequences of two categories of interventions on stimulating sustainable development. The conclusions are that both categories of interventions, financial interventions by national government and the introduction of multi-criteria decision analysis (MCDA) tools to aid strategic decision making, can have both positive and negative effects on the network evolutions, depending on what ‘mental models’ are employed by organisations. Furthermore, there is no single intervention that outperforms the others in terms of stimulating both functional and structural features of sustainable development. The final conclusion is that instead of focusing on individual or collective targets, emphasis should be placed on the development of interventions that focus on evolutionary aspects of industrial networks rather than functional performance criteria. This thesis has also highlighted interesting research questions for future investigation. The methodology developed in this thesis is applied to a single case study, but there are still many questions concerning how different industrial networks might benefit from different organisational perceptions towards uncertainty. Furthermore, the role between the mental models and sustainable development requires further investigation, especially in the light of globalisation and the interconnectiveness of industrial networks in different countries and continents. Finally, this methodology has provided a platform for investigating how new technologies might be developed that anticipate needs of future generations. This thesis has provided a first and important step in developing a methodology that addresses the complex issues associated with sustainable development, benefiting both academics and practitioners that aim to stimulate sustainable development.

Les travaux de cette thèse ont porté sur la caractérisation multi-échelle du polyéthylène(PE) en vue d'évaluer l'impact du vieillissement thermo-oxydatif. Cette étude a apporté un premier élément de réponse quant à l'efficacité de quelques méthodes de dosage des hydroperoxydes. Les résultats obtenus ont révélé une différence des concentrations en hydroperoxydes titrées par iodométrie par rapport à celles titrées par SO2 et MDSC lors de la deuxième période c'est-à-dire lors de la décomposition des hydroperoxydes. Cette différence semble directement reliée à l'apparition de double liaison. Les méthodes de dosage par SO2 et MDSC semblent être plus fiables. A l'échelle macromoléculaire, la chute de la masse molaire en poids Mw jusqu'à une valeur asymptotique de deux traduit des phénomènes de coupures de chaînes liés. A l'échelle microstructurale, l'augmentation de Xc est liée aux phénomènes de recuit et de chimicristallisation responsables de la formation et de l'épaississement des lamelles secondaires respectivement. Lors de la seconde période, l'augmentation de Mw liée à la diminution de Xc est due à la réticulation qui est confirmée par l'apparition des doubles liaisons et l'observation d'un gel lors de la dissolution du PEhd. Ces phénomènes de réticulation ont lieu au sein de la phase amorphe mais également à l'interphase avec la phase cristalline / The work of this thesis focused on the multi-scale characterization of polyethylene (PE) to assess the impact of thermo-oxidative aging. This study provided a first answer about the effectiveness of some hydroperoxides titration. The results revealed a difference in hydroperoxides concentrations titrated by iodometry compared to SO2 and MDSC in the second period that correpond to the decomposition of hydroperoxides. This difference appears to be linked to the occurrence of double bond. Titration methods with SO2 and MDSC seem to be more reliable. On the macromolecular scale, the decrease of the molecular weight Mw up to an asymptotic value of two is related to the chain scission process. On the microstructural scale, the increase of Xc is linked to the annealing and the chimicristallisation process which are responsible of the formation and the thickening of secondary lamellae. During the second period, the increase of Mw is related to the decrease of Xc due to crosslinking, which is confirmed by the occurrence of the double bonds and the observation of a gel during the dissolution of HDPE. These crosslinking phenomenon takes place in the amorphous phase but also in the transition region

L’objectif de ce travail est d’obtenir, grâce à un mélange de différentes informations, un monitorage de l’activité du fœtus pour apprécier son état de bien-être ou de souffrance.Actuellement, les paramètres qui caractérisent la souffrance fœtale, issus du rythme cardiaque et des mouvements fœtaux, sont évalués par le médecin et ils sont réunis dans le score de Manning. Deux inconvénients majeurs existent: a) l’évaluation du score est trop longue puisqu’elle dure 1 heure b) il existe des variations inter et intra-opérateur conduisant à différentes interprétations du bilan médical de la patiente.Pour s’affranchir de ces désavantages nous évaluons le bien-être fœtal d’une façon objective, à travers le calcul d’un score. Pour atteindre ce but, nous avons développé une technologie ultrasonore mufti-capteurs permettant de recueillir une soixantaine de signaux Doppler en provenance du cœur, des membres inférieurs et supérieurs. / The objective of this work is to assess the fetal parameters and the fetal well-being using a mixture of fetal parameters. In our days, the parameters derived from heart rate and fetal movements that characterize the fetal distress are assessed by the physician and unified in the score of Manning. Two major disadvantages of Manning’s score exist: a) the assessment of the score is time consuming; b) there are variations inter and intra operators leading to different interpretations of the patients medical record. To overcome these disadvantages we assess the fetal well-being objectively, by computing an automatic/electronic score. To achieve this goal, we developed an ultrasonic multi-sensor unit with 12 sensors allowing to collect sixty Doppler signals from the heart, lower and upper limbs.