Modelling of complex corroding industrial systems is ritical to effective inspection and maintenance for ssurance of system integrity. Wall thickness and corrosion rate are modelled for multiple dependent corroding omponents, given observations of minimum wall thickness per component. At each inspection, partial observations of the system are considered. A Bayes Linear approach is adopted simplifying parameter estimation and avoiding often unrealistic distributional assumptions. Key system variances are modelled, making exchangeability assumptions to facilitate analysis for sparse inspection time-series. A utility based criterion is used to assess quality of inspection design and aid decision making. The model is applied to inspection data from pipework networks on a full-scale offshore platform.

Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. The state space approach is then extended to discuss direct and indirect seasonal adjustments. This is achieved by applying a seasonal level model with no trend and some specific input variances that render different signal-to-noise ratios. This is illustrated for a system consisting of two artificial time series. Relative efficiencies between direct, indirect and multivariate, i.e. optimal, variances are then analyzed. In practice, standard seasonal adjustment packages do not support optimal/multivariate seasonal adjustments, so a univariate approach to simultaneous estimation is presented by specifying a Holt-Winters exponential smoothing method. This is applied to two sets of time series systems by defining a total loss function that is specified with a trade-off weight between the individual series’ loss functions and their aggregate loss function. The loss function is based on either the more conventional squared errors loss or on a robust Huber loss. The exponential decay parameters are then estimated by minimizing the total loss function for different trade-off weights. It is then concluded what approach, direct or indirect seasonal adjustment, is to be preferred for the two time series systems. The dynamic linear modeling approach is also applied to Swedish political opinion polls to assert the true underlying political opinion when there are several polls, with potential design effects and bias, observed at non-equidistant time points. A Wiener process model is used to model the change in the proportion of voters supporting either a specific party or a party block. Similar to stock market models, all available (political) information is assumed to be capitalized in the poll results and is incorporated in the model by assimilating opinion poll results with the model through Bayesian updating of the posterior distribution. Based on the results, we are able to assess the true underlying voter proportion and additionally predict the elections. / <p>At the time of doctoral defence the following papers were unpublished and had a status as follows: Paper 3: Manuscript; Paper 4: Manuscripts</p>

<p>The purpose of this master thesis was to study if the drain efficiency of power amplifiers can be maintained at power back off using a technique called load modulation.</p><p>The amplifier classes studied are E, F and D-1. The target figure was to obtain a 10 to 12 dB dynamic range of amplitude with reasonable efficiency. Studies of power amplifiers have been made to understand how power is generated. Several different load modulation networks have been evaluated. Attempts to derive design equations for the modulation networks have also been done.</p><p>The thesis work was carried out with simulations in ADS 2006. As active devices commercially available bare-die transistor models have been used. The power rating of the dies are 15 W.</p><p>A dynamic range of amplitude of over 15 dB has been achieved with drain efficiency greater than 60 percent. The peak output power is in the 40 – 45 dBm range.</p>

The purpose of this master thesis was to study if the drain efficiency of power amplifiers can be maintained at power back off using a technique called load modulation. The amplifier classes studied are E, F and D-1. The target figure was to obtain a 10 to 12 dB dynamic range of amplitude with reasonable efficiency. Studies of power amplifiers have been made to understand how power is generated. Several different load modulation networks have been evaluated. Attempts to derive design equations for the modulation networks have also been done. The thesis work was carried out with simulations in ADS 2006. As active devices commercially available bare-die transistor models have been used. The power rating of the dies are 15 W. A dynamic range of amplitude of over 15 dB has been achieved with drain efficiency greater than 60 percent. The peak output power is in the 40 – 45 dBm range.

Exactly constrained (EC) design is a robust design method which can be used for mechanical assemblies. It entails using the minimum number of constraints to eliminate all desired motion. While found by some engineers in industry to have many benefits (including robust assembly, no binding or play, ease of assembly, and the ability to tolerate the wear of parts), EC designs remain somewhat unrecognized by academia. One reason for this minimal exposure may be the lack of a quantitative foundation for such designs. This thesis describes the history and current background for EC designs, and it also begins to develop a quantitative foundation for EC design based on several mathematical methods. EC designs can be analyzed quite simply by understanding that they are statically determinate. Because of this, the equations of equilibrium can be used to validate the rules and the nesting force window that have been defined by Blanding [1999]. In addition, a generalized method using the equations of equilibrium has been developed in this thesis to analyze an EC design based on the locations of the constraints and to find the nesting force window. The direct linearization method (DLM) is another mathematical method used to quantify information in an EC design. While EC designs provide many advantages, some EC assemblies may be "better" than others. A quantitative measure of goodness is developed in this thesis using the DLM. The goodness value assigned to each design through this process can either be used to make a decision on an individual design, or it can be used to compare similar EC designs. Finally, the robust nature of EC design is examined using a Monte Carlo simulation. In general, the results show that EC designs have a higher rate of assembly than similar designs that are over-constrained. They are more robust. In addition, EC designs have lower assembly error than the similarly over-constrained assemblies.

The thesis consists of three parts. In the first part, we introduce the notion of device-cache-aware schedulers. Modern disk subsystems have many megabytes of memory for various purposes such as prefetching and caching. Current disk scheduling algorithms make decisions oblivious of the underlying device cache algorithms. In this thesis, we propose a scheduler architecture that is aware of underlying device cache. We also describe how the underlying device cache parameters can be automatically deduced and incorporated into the scheduling algorithm. In this thesis, we have only considered adaptive caching algorithms as modern high end disk subsystems are by default configured to use such algorithms. We implemented a prototype for Linux anticipatory scheduler, where we observed, compared with the anticipatory scheduler, upto 3 times improvement in query execution times with Benchw benchmark and upto 10 percent improvement with Postmark benchmark. The second part deals with implementing cooperative caching for the Redhat Global File System. The Redhat Global File System (GFS) is a clustered shared disk file system. The coordination between multiple accesses is through a lock manager. On a read, a lock on the inode is acquired in shared mode and the data is read from the disk. For a write, an exclusive lock on the inode is acquired and data is written to the disk; this requires all nodes holding the lock to write their dirty buffers/pages to disk and invalidate all the related buffers/pages. A DLM (Distributed Lock Manager) is a module that implements the functions of a lock manager. GFS’s DLM has some support for range locks, although it is not being used by GFS. While it is clear that a data sourced from a memory copy is likely to have lower latency, GFS currently reads from the shared disk after acquiring a lock (just as in other designs such as IBM’s GPFS) rather than from remote memory that just recently had the correct contents. The difficulties are mainly due to the circular relationships that can result between GFS and the generic DLM architecture while integrating DLM locking framework with cooperative caching. For example, the page/buffer cache should be accessible from DLM and yet DLM’s generality has to be preserved. The symmetric nature of DLM (including the SMP concurrency model) makes it even more difficult to understand and integrate cooperative caching into it (note that GPFS has an asymmetrical design). In this thesis, we describe the design of a cooperative caching scheme in GFS. To make it more effective, we also have introduced changes to the locking protocol and DLM to handle range locks more efficiently. Experiments with micro benchmarks on our prototype implementation reveal that, reading from a remote node over gigabit Ethernet can be upto 8 times faster than reading from a enterprise class SCSI disk for random disk reads. Our contributions are an integrated design for cooperative caching and lock manager for GFS, devising a novel method to do interval searches and determining when sequential reads from a remote memory perform better than sequential reads from a disk. The third part deals with selecting a primary network partition in a clustered shared disk system, when node/network failures occur. Clustered shared disk file systems like GFS, GPFS use methods that can fail in case of multiple network partitions and also in case of a 2 node cluster. In this thesis, we give an algorithm for fault-tolerant proactive leader election in asynchronous shared memory systems, and later its formal verification. Roughly speaking, a leader election algorithm is proactive if it can tolerate failure of nodes even after a leader is elected, and (stable) leader election happens periodically. This is needed in systems where a leader is required after every failure to ensure the availability of the system and there might be no explicit events such as messages in the (shared memory) system. Previous algorithms like DiskPaxos are not proactive. In our model, individual nodes can fail and reincarnate at any point in time. Each node has a counter which is incremented every period, which is same across all the nodes (modulo a maximum drift). Different nodes can be in different epochs at the same time. Our algorithm ensures that per epoch there can be at most one leader. So if the counter values of some set of nodes match, then there can be at most one leader among them. If the nodes satisfy certain timeliness constraints, then the leader for the epoch with highest counter also becomes the leader for the next epoch (stable property). Our algorithm uses shared memory proportional to the number of processes, the best possible. We also show how our protocol can be used in clustered shared disk systems to select a primary network partition. We have used the state machine approach to represent our protocol in Isabelle HOL logic system and have proved the safety property of the protocol.