Exploring physical processes related to past climate proxies: lake sediments and stable water isotopes

Proxy data are essential for the investigation of climate variability on time scales larger than the historical meteorological observation period. The potential value of a proxy depends on our ability to understand and quantify the physical processes that relate the corresponding climate parameter and the signal in the proxy archive. These processes can be explored under present-day conditions. In this thesis, both statistical and physical models are applied for their analysis, focusing on two specific types of proxies, lake sediment data and stable water isotopes.rnIn the first part of this work, the basis is established for statistically calibrating new proxies from lake sediments in western Germany. A comprehensive meteorological and hydrological data set is compiled and statistically analyzed. In this way, meteorological times series are identified that can be applied for the calibration of various climate proxies. A particular focus is laid on the investigation of extreme weather events, which have rarely been the objective of paleoclimate reconstructions so far. Subsequently, a concrete example of a proxy calibration is presented. Maxima in the quartz grain concentration from a lake sediment core are compared to recent windstorms. The latter are identified from the meteorological data with the help of a newly developed windstorm index, combining local measurements and reanalysis data. The statistical significance of the correlation between extreme windstorms and signals in the sediment is verified with the help of a Monte Carlo method. This correlation is fundamental for employing lake sediment data as a new proxy to reconstruct windstorm records of the geological past.rnThe second part of this thesis deals with the analysis and simulation of stable water isotopes in atmospheric vapor on daily time scales. In this way, a better understanding of the physical processes determining these isotope ratios can be obtained, which is an important prerequisite for the interpretation of isotope data from ice cores and the reconstruction of past temperature. In particular, the focus here is on the deuterium excess and its relation to the environmental conditions during evaporation of water from the ocean. As a basis for the diagnostic analysis and for evaluating the simulations, isotope measurements from Rehovot (Israel) are used, provided by the Weizmann Institute of Science. First, a Lagrangian moisture source diagnostic is employed in order to establish quantitative linkages between the measurements and the evaporation conditions of the vapor (and thus to calibrate the isotope signal). A strong negative correlation between relative humidity in the source regions and measured deuterium excess is found. On the contrary, sea surface temperature in the evaporation regions does not correlate well with deuterium excess. Although requiring confirmation by isotope data from different regions and longer time scales, this weak correlation might be of major importance for the reconstruction of moisture source temperatures from ice core data. Second, the Lagrangian source diagnostic is combined with a Craig-Gordon fractionation parameterization for the identified evaporation events in order to simulate the isotope ratios at Rehovot. In this way, the Craig-Gordon model can be directly evaluated with atmospheric isotope data, and better constraints for uncertain model parameters can be obtained. A comparison of the simulated deuterium excess with the measurements reveals that a much better agreement can be achieved using a wind speed independent formulation of the non-equilibrium fractionation factor instead of the classical parameterization introduced by Merlivat and Jouzel, which is widely applied in isotope GCMs. Finally, the first steps of the implementation of water isotope physics in the limited-area COSMO model are described, and an approach is outlined that allows to compare simulated isotope ratios to measurements in an event-based manner by using a water tagging technique. The good agreement between model results from several case studies and measurements at Rehovot demonstrates the applicability of the approach. Because the model can be run with high, potentially cloud-resolving spatial resolution, and because it contains sophisticated parameterizations of many atmospheric processes, a complete implementation of isotope physics will allow detailed, process-oriented studies of the complex variability of stable isotopes in atmospheric waters in future research.rn

Speleogenesis and secondary cave minerals in quartz-sandstone and quartzite environment

The main objective of this research is to improve the comprehension of the processes controlling the formation of caves and karst-like morphologies in quartz-rich lithologies (more than 90% quartz), like quartz-sandstones and metamorphic quartzites. In the scientific community the processes actually most retained to be responsible of these formations are explained in the “Arenisation Theory”. This implies a slow but pervasive dissolution of the quartz grain/mineral boundaries increasing the general porosity until the rock becomes incohesive and can be easily eroded by running waters. The loose sands produced by the weathering processes are then evacuated to the surface through processes of piping due to the infiltration of waters from the fracture network or the bedding planes. To deal with these problems we adopted a multidisciplinary approach through the exploration and the study of several cave systems in different tepuis. The first step was to build a theoretical model of the arenisation process, considering the most recent knowledge about the dissolution kinetics of quartz, the intergranular/grain boundaries diffusion processes, the primary diffusion porosity, in the simplified conditions of an open fracture crossed by a continuous flow of undersatured water. The results of the model were then compared with the world’s widest dataset (more than 150 analyses) of water geochemistry collected till now on the tepui, in superficial and cave settings. All these studies allowed verifying the importance and the effectiveness of the arenisation process that is confirmed to be the main process responsible of the primary formation of these caves and of the karst-like superficial morphologies. The numerical modelling and the field observations allowed evaluating a possible age of the cave systems around 20-30 million of years.

Building Information Modelling (BIM) Effectiveness in Performing Life Cycle Assessment of Building

The scope of this project is to study the effectiveness of building information modelling (BIM) in performing life cycle assessment in a building. For the purposes of the study will be used “Revit” which is a BIM software and Tally which is an LCA tool integrated in Revit. The project is divided in six chapters. The first chapter consists of a theoretical introduction into building information modelling and its connection to life cycle assessment. The second chapter describes the characteristics of building information modelling (BIM). In addition, a comparison has been made with the traditional architectural, engineering and construction business model and the benefits to shift into BIM. In the third chapter it will be a review of the most well-known and available BIM software in the market. In chapter four life cycle assessment (LCA) will be described in general and later on specifically for the purpose of the case study that will be used in the following chapter. Moreover, the tools that are available to perform an LCA will be reviewed. Chapter five will present the case study that consists of a model in a BIM software (Revit) and the LCA performed by Tally, an LCA tool integrated into Revit. In the last chapter will be a discussion of the results that were obtained, the limitation and the possible future improvement in performing life cycle assessment (LCA) in a BIM model.

Kinematics and statics of cable-driven parallel robots by interval-analysis-based methods

In the past two decades the work of a growing portion of researchers in robotics focused on a particular group of machines, belonging to the family of parallel manipulators: the cable robots. Although these robots share several theoretical elements with the better known parallel robots, they still present completely (or partly) unsolved issues. In particular, the study of their kinematic, already a difficult subject for conventional parallel manipulators, is further complicated by the non-linear nature of cables, which can exert only efforts of pure traction. The work presented in this thesis therefore focuses on the study of the kinematics of these robots and on the development of numerical techniques able to address some of the problems related to it. Most of the work is focused on the development of an interval-analysis based procedure for the solution of the direct geometric problem of a generic cable manipulator. This technique, as well as allowing for a rapid solution of the problem, also guarantees the results obtained against rounding and elimination errors and can take into account any uncertainties in the model of the problem. The developed code has been tested with the help of a small manipulator whose realization is described in this dissertation together with the auxiliary work done during its design and simulation phases.

A framework for cyber-physical system simulation

In these last years, systems engineering has became one of the major research domains. The complexity of systems has increased constantly and nowadays Cyber-Physical Systems (CPS) are a category of particular interest: these, are systems composed by a cyber part (computer-based algorithms) that monitor and control some physical processes. Their development and simulation are both complex due to the importance of the interaction between the cyber and the physical entities: there are a lot of models written in different languages that need to exchange information among each other. Normally people use an orchestrator that takes care of the simulation of the models and the exchange of informations. This orchestrator is developed manually and this is a tedious and long work. Our proposition is to achieve to generate the orchestrator automatically through the use of Co-Modeling, i.e. by modeling the coordination. Before achieving this ultimate goal, it is important to understand the mechanisms and de facto standards that could be used in a co-modeling framework. So, I studied the use of a technology employed for co-simulation in the industry: FMI. In order to better understand the FMI standard, I realized an automatic export, in the FMI format, of the models realized in an existing software for discrete modeling: TimeSquare. I also developed a simple physical model in the existing open source openmodelica tool. Later, I started to understand how works an orchestrator, developing a simple one: this will be useful in future to generate an orchestrator automatically.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

The examination and identification of bite marks in foods using 3D scanning and 3D comparison methods

Bite mark analysis offers the opportunity to identify the biter based on the individual characteristics of the dentitions. Normally, the main focus is on analysing bite mark injuries on human bodies, but also, bite marks in food may play an important role in the forensic investigation of a crime. This study presents a comparison of simulated bite marks in different kinds of food with the dentitions of the presumed biter. Bite marks were produced by six adults in slices of buttered bread, apples, different kinds of Swiss chocolate and Swiss cheese. The time-lapse influence of the bite mark in food, under room temperature conditions, was also examined. For the documentation of the bite marks and the dentitions of the biters, 3D optical surface scanning technology was used. The comparison was performed using two different software packages: the ATOS modelling and analysing software and the 3D studio max animation software. The ATOS software enables an automatic computation of the deviation between the two meshes. In the present study, the bite marks and the dentitions were compared, as well as the meshes of each bite mark which were recorded in the different stages of time lapse. In the 3D studio max software, the act of biting was animated to compare the dentitions with the bite mark. The examined food recorded the individual characteristics of the dentitions very well. In all cases, the biter could be identified, and the dentitions of the other presumed biters could be excluded. The influence of the time lapse on the food depends on the kind of food and is shown on the diagrams. However, the identification of the biter could still be performed after a period of time, based on the recorded individual characteristics of the dentitions.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.

A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery

A new system for computer-aided corrective surgery of the jaws has been developed and introduced clinically. It combines three-dimensional (3-D) surgical planning with conventional dental occlusion planning. The developed software allows simulating the surgical correction on virtual 3-D models of the facial skeleton generated from computed tomography (CT) scans. Surgery planning and simulation include dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and segment repositioning. By coupling the software with a tracking system and with the help of a special registration procedure, we are able to acquire dental occlusion plans from plaster model mounts. Upon completion of the surgical plan, the setup is used to manufacture positioning splints for intraoperative guidance. The system provides further intraoperative assistance with the help of a display showing jaw positions and 3-D positioning guides updated in real time during the surgical procedure. The proposed approach offers the advantages of 3-D visualization and tracking technology without sacrificing long-proven cast-based techniques for dental occlusion evaluation. The system has been applied on one patient. Throughout this procedure, we have experienced improved assessment of pathology, increased precision, and augmented control.

Design of a lab scale direct-filtration system and its application in process lab

The Environmental Process and Simulation Center (EPSC) at Michigan Technological University started accommodating laboratories for an Environmental Engineering senior level class CEE 4509 Environmental Process and Simulation Laboratory since 2004. Even though the five units that exist in EPSC provide the students opportunities to have hands-on experiences with a wide range of water/wastewater treatment technologies, a key module was still missing for the student to experience a full cycle of treatment. This project fabricated a direct-filtration pilot system in EPSC and generated a laboratory manual for education purpose. Engineering applications such as clean bed head loss calculation, backwash flowrate determination, multimedia density calculation and run length prediction are included in the laboratory manual. The system was tested for one semester and modifications have been made both to the direct filtration unit and the laboratory manual. Future work is also proposed to further refine the module.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.