The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter-dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.

Checkpointing is a technique widely used in parallel/distributed computers for rollback error recovery. Checkpointing is defined as the coordinated saving of process state information at specified time instances. Checkpoints help in restoring the computation from the latest saved state, in case of failure. In addition to fault recovery, checkpointing has applications in fault detection, distributed debugging and process migration. Checkpointing in uniprocessor systems is easy due to the fact that there is a single clock and events occur with respect to this clock. There is a clear demarcation of events that happens before a checkpoint and events that happens after a checkpoint. In parallel computers a large number of computers coordinate to solve a single problem. Since there might be multiple streams of execution, checkpoints have to be introduced along all these streams simultaneously. Absence of a global clock necessitates explicit coordination to obtain a consistent global state. Events occurring in a distributed system, can be ordered partially using Lamport's happens before relation. Lamport's happens before relation ->is a partial ordering relation to identify dependent and concurrent events occurring in a distributed system. It is defined as follows: ·If two events a and b happen in the same process, and if a happens before b, then a->b ·If a is the sending event of a message and b is the receiving event of the same message then a -> b ·If neither a à b nor b -> a, then a and b are said to be concurrent. A consistent global state may have concurrent checkpoints. In the first chapter of the thesis we discuss issues regarding ordering of events in a parallel computer, need for coordination among checkpoints and other aspects related to checkpointing. Checkpointing locations can either be identified statically or dynamically. The static approach assumes that a representation of a program to be checkpointed is available with information that enables a programmer to specify the places where checkpoints are to be taken. The dynamic approach identifies the checkpointing locations at run time. In this thesis, we have proposed algorithms for both static and dynamic checkpointing. The main contributions of this thesis are as follows: 1. Parallel computers that are being built now have faster communication and hence more efficient clock synchronisation compared to those built a few years ago. Based on efficient clock synchronisation protocols, the clock drift in current machines can be maintained within a few microseconds. We have proposed a dynamic checkpointing algorithm for parallel computers assuming bounded clock drifts. 2. The shared memory paradigm is convenient for programming while message passing paradigm is easy to scale. Distributed Shared Memory (DSM) systems combine the advantage of both paradigms and can be visualized easily on top of a network of workstations. IEEE has recently proposed an interconnect standard called Scalable Coherent Interface (SCI), to con6gure computers as a Distributed Shared Memory system. A periodic dynamic checkpointing algorithm has been proposed in the thesis for a DSM system which uses the SCI standard. 3. When information about a parallel program is available one can make use of this knowledge to perform efficient checkpointing. A static checkpointing approach based on task graphs is proposed for parallel programs. The proposed task graph based static checkpointing approach has been implemented on a Parallel Virtual Machine (PVM) platform. We now give a gist of various chapters of the thesis. Chapter 2 of the thesis gives a classification of existing checkpointing algorithms. The chapter surveys algorithm that have been reported in literature for checkpointing parallel/distributed systems. A point to be noted is that most of the algorithms published for checkpointing message passing systems are based on the seminal article by Chandy & Lamport. A large number of checkpointing algorithms have been published by relaxing the assumptions made in the above mentioned article and by extending the features to minimise the overheads of coordination and context saving. Checkpointing for shared memory systems primarily extend cache coherence protocols to maintain a consistent memory. All of them assume that the main memory is safe for storing the context. Recently algorithms have been published for distributed shared memory systems, which extend the cache coherence protocols used in shared memory systems. They however also include methods for storing the status of distributed memory in stable storage. Chapter 2 concludes with brief comments on the desirable features of a checkpointing algorithm. In Chapter 3, we develop a dynamic checkpointing algorithm for message passing systems assuming that the clock drift of processors in the system is bounded. Efficient clock synchronisation protocols have been implemented on recent parallel computers owing to the fact that communication between processors is very fast. Based on efficient clock synchronisation protocols, clock skew can be limited to a few microseconds. The algorithm proposed in the thesis uses clocks for checkpoint coordination and vector counts for identifying messages to be logged. The algorithm is a periodic, distributed algorithm. We prove correctness of the algorithm and compare it with similar clock based algorithms. Distributed Shared Memory (DSM) systems provide the benefit of ease of programming in a scalable system. The recently proposed IEEE Scalable Coherent Interface (SCI) standard, facilitates the construction of scalable coherent systems. In Chapter 4 we discuss a checkpointing algorithm for an SCI based DSM system. SCI maintains cache coherence in hardware using a distributed cache directory which scales with the number of processors in the system. SCI recommends a two phase transaction protocol for communication. Our algorithm is a two phase centralised coordinated algorithm. Phase one initiates checkpoints and the checkpointing activity is completed in phase two. The correctness of the algorithm is established theoretically. The chapter concludes with the discussion of the features of SCI exploited by the checkpointing algorithm proposed in the thesis. In Chapter 5, a static checkpointing algorithm is developed assuming that the program to be executed on a parallel computer is given as a directed acyclic task graph. We assume that the estimates of the time to execute each task in the task graph is given. Given the timing at which checkpoints are to be taken, the algorithm identifies a set of edges where checkpointing tasks can be placed ensuring that they form a consistent global checkpoint. The proposed algorithm eliminates coordination overhead at run time. It significantly reduces the context saving overhead by taking checkpoints along edges of the task graph. The algorithm is used as a preprocessing step before scheduling the tasks to processors. The algorithm complexity is O(km) where m is the number of edges in the graph and k the maximum number of global checkpoints to be taken. The static algorithm is implemented on a parallel computer with a PVM environment as it is widely available and portable. The task graph of a program can be constructed manually or through program development tools. Our implementation is a collection of preprocessing and run time routines. The preprocessing routines operate on the task graph information to generate a set of edges to be checkpointed for each global checkpoint and write the information on disk. The run time routines save the context along the marked edges. In case of recovery, the recovery algorithms read the information from stable storage and reconstruct the context. The limitation of our static checkpointing algorithm is that it can operate only on deterministic task graphs. To demonstrate the practical feasibility of the proposed approach, case studies of checkpointing some parallel programs are included in the thesis. We conclude the thesis with a summary of proposed algorithms and possible directions to continue research in the area of checkpointing.

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

The energy provider in South Africa, Eskom, faces an increasing electricity demand. The need to ensure sufficient supply gave rise to Demand Side Management (DSM) projects scheme. The DSM focus has shifted to the mining sector in South Africa. The large electricity use of the mining sector ensured the need for Energy Services Companies (ESCo’s). The ESCo is contracted to ensure energy savings of DSM projects implemented within the multiple sectors such as mining industry. The mining sector business model has the constant pressure to increase gold production. This pressure to expand has led to rapid expansion plans to increase the gold output for the relevant company. The expansion process and production increase in turn increases the electricity consumption. Compressed air use is a large contributing factor to the monthly electricity use as it is widely used within the mine sector. The implementation of a DSM project on the compressed air ring of an expanding gold mine was the focus of the study. This case study focused on an expanding gold mine within South Africa. The DSM lifecycle was followed to initially determine the DSM saving potential. The possible control strategies were investigated with simulation models and savings calculations. The viable option was to be implemented with a preliminary control philosophy. Results were in turn compared with the initial investigations and control philosophy. The deviations as experienced with implementation were addressed and a potential sustainable control philosophy for an expanding gold mine was constructed. The results indicated, verified Eskom peak clip electricity savings of 2.165 MW of the 2.4 MW target. The energy efficiency component for these performance assessment months was 1.944 MW of the targeted 1.5 MW. The sustainability of the system was proven with production increase on an expanding gold mine. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2013

Various commercial software packages are available for simulating compressed air network operations. However, none of these software packages are able to dynamically prioritise compressor selection on large compressed air networks in the mining industry. In this dissertation, a dynamic compressor selector (DCS) will be developed that will actively and continuously monitor system demand. The software will ensure that the most suitable compressors, based on efficiency and position in the compressed air network, are always in operation. The study will be conducted at a platinum mine. Compressed air flow and pressure requirements will be maintained without compromising mine safety procedures. Significant energy savings will be realised. DCS will receive shaft pressure profiles from each of the shafts’ surface compressed air control valves. These parameters will be used to calculate and predict the compressed air demand. All pipe friction losses and leaks will be taken into account to determine the end-point pressure losses at different flow rates. DCS will then prioritise the compressors of the compressed air network based on the overall system requirement. This software combines the benefits of supply-side and demand-side management. Potential energy savings with DCS were proven and compressor cycling reduced. A DCS user-friendly interface was created to easily set up any mine’s compressed air network. / Thesis (MIng (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

The energy provider in South Africa, Eskom, faces an increasing electricity demand. The need to ensure sufficient supply gave rise to Demand Side Management (DSM) projects scheme. The DSM focus has shifted to the mining sector in South Africa. The large electricity use of the mining sector ensured the need for Energy Services Companies (ESCo’s). The ESCo is contracted to ensure energy savings of DSM projects implemented within the multiple sectors such as mining industry. The mining sector business model has the constant pressure to increase gold production. This pressure to expand has led to rapid expansion plans to increase the gold output for the relevant company. The expansion process and production increase in turn increases the electricity consumption. Compressed air use is a large contributing factor to the monthly electricity use as it is widely used within the mine sector. The implementation of a DSM project on the compressed air ring of an expanding gold mine was the focus of the study. This case study focused on an expanding gold mine within South Africa. The DSM lifecycle was followed to initially determine the DSM saving potential. The possible control strategies were investigated with simulation models and savings calculations. The viable option was to be implemented with a preliminary control philosophy. Results were in turn compared with the initial investigations and control philosophy. The deviations as experienced with implementation were addressed and a potential sustainable control philosophy for an expanding gold mine was constructed. The results indicated, verified Eskom peak clip electricity savings of 2.165 MW of the 2.4 MW target. The energy efficiency component for these performance assessment months was 1.944 MW of the targeted 1.5 MW. The sustainability of the system was proven with production increase on an expanding gold mine. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2013

Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2008.

Electrical energy is commonly used in households and in industry - demand continues to rise due to economic and population growth. This requires that energy suppliers must increase their supply capacity. The result is that end–user energy costs continue to increase, therefore a growing need exists to reduce electrical energy demand in South Africa and internationally. Households account for the majority of electrical energy customers, but they only consume a fraction of the total energy supplied. The industrial sector and mines combined consume approximately 42% of the total electrical energy produced. Approximately 10% of this energy goes into compressed air production. This study focuses on methods of reducing the requirement of compressed air in industry so that the demand for electrical energy can be reduced. Many studies have focused on specific methods of reducing energy usage associated with compressed air production. These methods are categorised into methods of reducing compressed air requirements and methods of increasing compressed air supply efficiency. This study aims to combine these efforts into a single optimised solution. Although this study includes industry in general, the central focus is on the South African mining industry. Two different mining sites are considered and analysed as case studies. Methods of reducing energy required to produce compressed air were applied to each case study. Case Study 1 only allowed limited control of the compressed air system. In Case Study 2 integrated control was realised. Energy usage of compressors was reduced by 18.9% and 42.9% respectively. Results show that system savings can be doubled by combining different methods of reducing energy usage of compressed air. This, however, requires continuous monitoring and control of the air network at each section supplied with compressed air. The study is limited to achieving savings by changing the air system. Additional savings can be achieved by training personnel, altering schedules of production activities and implementing a system designed to locate air leaks. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2012.

Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2008.

Electrical energy is commonly used in households and in industry - demand continues to rise due to economic and population growth. This requires that energy suppliers must increase their supply capacity. The result is that end–user energy costs continue to increase, therefore a growing need exists to reduce electrical energy demand in South Africa and internationally. Households account for the majority of electrical energy customers, but they only consume a fraction of the total energy supplied. The industrial sector and mines combined consume approximately 42% of the total electrical energy produced. Approximately 10% of this energy goes into compressed air production. This study focuses on methods of reducing the requirement of compressed air in industry so that the demand for electrical energy can be reduced. Many studies have focused on specific methods of reducing energy usage associated with compressed air production. These methods are categorised into methods of reducing compressed air requirements and methods of increasing compressed air supply efficiency. This study aims to combine these efforts into a single optimised solution. Although this study includes industry in general, the central focus is on the South African mining industry. Two different mining sites are considered and analysed as case studies. Methods of reducing energy required to produce compressed air were applied to each case study. Case Study 1 only allowed limited control of the compressed air system. In Case Study 2 integrated control was realised. Energy usage of compressors was reduced by 18.9% and 42.9% respectively. Results show that system savings can be doubled by combining different methods of reducing energy usage of compressed air. This, however, requires continuous monitoring and control of the air network at each section supplied with compressed air. The study is limited to achieving savings by changing the air system. Additional savings can be achieved by training personnel, altering schedules of production activities and implementing a system designed to locate air leaks. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2012.