On the Use of Historical Bathymetric Data to Determine Changes in Bathymetry: An Analysis of Errors and Application to Great Bay Estuary, NH

The depth measurements that are incorporated into bathymetric charts have associated errors with magnitudes depending on the survey circumstances and applied techniques. For this reason, combining and comparing depth measurements collected over many years with different techniques and standards is a difficult task which must be done with great caution. In this study we have developed an approach for comparing historical bathymetric surveys. Our methodology uses Monte Carlo modelling to account for the random error components inherited in the data due to positioning and depth measurement uncertainties

Towards a pragmatic approach for dealing with uncertainties in water management practice

Management of water resources is afflicted with uncertainties. Nowadays it is facing more and new uncertainties since pace and dimension of changes (e.g. climatic, demographic) are accelerating and are likely to increase even more in the future. Hence it is crucial to find pragmatic ways to deal with these uncertainties in water management. So far, decision-making under uncertainty in water management is based on either intuition, heuristics and experience of water managers or on expert assessments all of which are only of limited use for water managers in practice. We argue for an analytical yet pragmatic approach to enable practitioners to deal with uncertainties in a more explicit and systematic way and allow for better informed decisions. Our approach is based on the concept of framing, referring to the different ways in which people make sense of the world and of the uncertainties. We applied and tested recently developed parameters that aim to shed light on the framing of uncertainty in two sub-basins of the Rhine. We present and discuss the results of a series of stakeholder interactions in the two basins aimed at developing strategies for improving dealing with uncertainties. The strategies are synthesized in a cross-checking list based on the uncertainty framing parameters as a hands-on tool for systematically identifying improvement options when dealing with uncertainty in water management practice. We conclude with suggestions for testing the developed check-list as a tool for decision aid in water management practice. Key words: water management, future uncertainties, framing of uncertainties, hands-on decision aid, tools for practice, robust strategies, social learnin

Validation of Finite Element Modelling of Multielectrode Capacitive System for Process Tomography Flow Imaging

Finite element modelling of process tomography sensor systems is necessary for their CAD both for performance evaluation and design optimization. This paper involves the validation of finite element models of a 12-electrode capacitive sensor system for multiphase flow imaging. Various results of modelling have been compared in the form of standing mode capacitances and sensor sensitivity distribution with experimental data obtained from UMIST. There is good agreement between simulation results and experiments especially for high sensitivity regions inside the pipe

A hierarchical approach to multi-project planning under uncertainty

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper

Modelling the impact of treatment uncertainties in radiotherapy

Uncertainties are inevitably part of the radiotherapy process. Uncertainty in the dose deposited in the tumour exists due to organ motion, patient positioning errors, fluctuations in machine output, delineation of regions of interest, the modality of imaging used, and treatment planning algorithm assumptions among others; there is uncertainty in the dose required to eradicate a tumour due to interpatient variations in patient-specific variables such as their sensitivity to radiation; and there is uncertainty in the dose-volume restraints that limit dose to normal tissue. This thesis involves three major streams of research including investigation of the actual dose delivered to target and normal tissue, the effect of dose uncertainty on radiobiological indices, and techniques to display the dose uncertainty in a treatment planning system. All of the analyses are performed with the dose distribution from a four-field box treatment using 6 MV photons. The treatment fields include uniform margins between the clinical target volume and planning target volume of 0.5 cm, 1.0 cm, and 1.5 cm. The major work is preceded by a thorough literature review on the size of setup and organ motion errors for various organs and setup techniques used in radiotherapy. A Monte Carlo (MC) code was written to simulate both the treatment planning and delivery phases of the radiotherapy treatment. Using MC, the mean and the variation in treatment dose are calculated for both an individual patient and across a population of patients. In particular, the possible discrepancy in tumour position located from a single CT scan and the magnitude of reduction in dose variation following multiple CT scans is investigated. A novel convolution kernel to include multiple pretreatment CT scans in the calculation of mean treatment dose is derived. Variations in dose deposited to prostate and rectal wall are assessed for each of the margins and for various magnitudes of systematic and random error, and penumbra gradients. The linear quadratic model is used to calculate prostate Tumour Control Probability (TCP) incorporating an actual (modelled) delivered prostate dose. The Kallman s-model is used to calculate the normal tissue complication probability (NTCP), incorporating actual (modelled) fraction dose in the deforming rectal wall. The impact of each treatment uncertainty on the variation in the radiobiological index is calculated for the margin sizes.Thesis (Ph.D.)--Department of Physics and Mathematical Physics, 2002

Thermal Error Modelling of a CNC Machine Tool Feed Drive System using FEA Method

Recirculating ball screw systems are commonly used in machine tools and are one of the major heat sources which cause considerable thermal drift in CNC machine tools. Finite Element Analysis (FEA) method has been used successfully in the past to model the thermal characteristics of machine tools with promising results. Since FEA predictions are highly dependent on the efficacy of numerical parameters including the surrounding Boundary Conditions (BC), this study emphasises on an efficient modelling method to obtain optimised numerical parameters for acquiring a qualitative response from the feed drive system model. This study was performed on a medium size Vertical Machining Centre (VMC) feed drive system in which two parameter dentification methods have been employed; the general prediction method based on formulae provided by OEMs, and the energy balance method. The parameters obtained from both methods were applied to the FEA model of the machine feed drive system and validated against experimental results. Correlation with which was increased from 70 % to 80 % using the energy balance method

On systematic approaches for interpreted information transfer of inspection data from bridge models to structural analysis

In conjunction with the improved methods of monitoring damage and degradation processes, the interest in reliability assessment of reinforced concrete bridges is increasing in recent years. Automated imagebased inspections of the structural surface provide valuable data to extract quantitative information about deteriorations, such as crack patterns. However, the knowledge gain results from processing this information in a structural context, i.e. relating the damage artifacts to building components. This way, transformation to structural analysis is enabled. This approach sets two further requirements: availability of structural bridge information and a standardized storage for interoperability with subsequent analysis tools. Since the involved large datasets are only efficiently processed in an automated manner, the implementation of the complete workflow from damage and building data to structural analysis is targeted in this work. First, domain concepts are derived from the back-end tasks: structural analysis, damage modeling, and life-cycle assessment. The common interoperability format, the Industry Foundation Class (IFC), and processes in these domains are further assessed. The need for usercontrolled interpretation steps is identified and the developed prototype thus allows interaction at subsequent model stages. The latter has the advantage that interpretation steps can be individually separated into either a structural analysis or a damage information model or a combination of both. This approach to damage information processing from the perspective of structural analysis is then validated in different case studies

Increasing the Numeric Expressiveness of the Planning Domain Definition Language

The technology of artificial intelligence (AI) planning is being adopted across many different disciplines. This has resulted in the wider use of the Planning Domain Definition Language (PDDL), where it is being used to model planning problems of different natures. One such area where AI planning is particularly attractive is engineering, where the optimisation problems are mathematically rich. The example used throughout this paper is the optimisation (minimisation) of machine tool measurement uncertainty. This planning problem highlights the limits of PDDL's numerical expressiveness in the absence of the square root function. A workaround method using the Babylonian algorithm is then evaluated before the extension of PDDL to include more mathematics functions is discussed