In this thesis, the optimum design algorithm is presented for reinforced concrete special moment frames. The objective function is considered as the total cost of reinforced concrete frame which includes the cost of concrete, formwork and reinforcing steel bars. The cost of any component is inclusive of material, fabrication and labor. The design variables in beams are selected as the width and the depth of beams in each span, the diameter and the number of longitudinal reinforcement bars along the span and supports. In columns the width and the depth of the column section, the number and the diameter of bars in x and y directions are selected as design variables. The column section database is prepared which includes the width and height of column section, the diameter and the number of reinforcing bars in the column section is constructed. This database is used by the design algorithm to select appropriate sections for the columns of the frame under consideration. The design constraints are implemented from ACI 318-05 which covers the flexural and shear strength, serviceability, the minimum and maximum steel percentage for flexural and shear reinforcement, the spacing requirements for the reinforcing bars and the upper and lower bound requirements for the concrete sections. The optimum design problem formulated according to ACI 318-05 provisions with the design variables mentioned above turns out to be a combinatorial optimization problem. The solution of the design problem is obtained by using the harmony search algorithm (HS) which is one of the recent additions to meta-heuristic optimization techniques which are widely used in obtaining the solution of combinatorial optimization problems. The HS algorithm is quite simple and has few parameters to initialize and consists of simple steps which make it easy to implement. Number of design examples is presented to demonstrate the efficiency and robustness of the optimum design algorithm developed.

The distribution system which forms the final connection between customers and power source plays a vital role in an electrical network. Different studies show that substantial proportion of the customer interruptions occurs due to the failures on distribution network. The ongoing privatization process of the electrical distribution services in Turkey raises the importance of reliable and continuous electricity supply significantly. The new regulations come up with this privatization process and the electrical distribution companies are strictly required to comply with these regulations to ensure the reliability of the distribution network. The legal framework and severe punishments applied to the electrical distribution companies exceeding the continuity of supply indices force them to invest on their network in order to increase the reliability of their system. As the reliability of electricity supplied increases, investment cost also increases. However, low system reliability causes higher outage frequency and duration which will increase the damage of these outages to customers and also increases the cost of the distribution company as a result of the penalty payments. This tradeoff between Outage Cost and Utility Cost requires consideration of an optimization when determining the optimal reliability level. In rural areas where electrical distribution network consists of long radial overhead lines in arborescent structure, continuity of supply is a major problem due to the high failure rates. The implementation of protection devices having reclosing capability and automated sectionalizing switches enhances the continuity of supply on rural networks substantially. The balance between the cost associated with installation of switches and the reduction on Outage Cost is an important optimization issue for distribution network operators. In this thesis study an algorithm is developed in order to determine the optimum number and locations of the sectionalizing switches on a rural electrical distribution network in Turkey which gives an optimum investment level with an optimum Outage Cost.

Aluminum Cross-Car Beam is significantly lighter than the conventional steel counterpart and presents superior energy absorption characteristics. The challenge is however, its considerably higher cost, rendering it difficult for the aluminum one to compete in the automotive market. In this work, using material distribution techniques and stochastic optimization, a Multidisciplinary Design Optimization procedure is developed to optimize an existing Cross-Car Beam model with respect to the cost. Topology, Topography, and gauge optimizations are employed in the development of the optimization disciplines. Based on a qualitative cost assessment, penalty functions are designed to penalize costly designs. Noise-Vibration-Harshness (NVH) performance is the key constraint of the optimization. To fulfill this requirement, natural frequencies are obtained using modal analysis. Undesirable designs with respect to the NVH criteria are gradually eliminated from the optimization cycles. The new design is verified by static loading scenario and evaluated in terms of the cost saving it offers.

Aluminum Cross-Car Beam is significantly lighter than the conventional steel counterpart and presents superior energy absorption characteristics. The challenge is however, its considerably higher cost, rendering it difficult for the aluminum one to compete in the automotive market. In this work, using material distribution techniques and stochastic optimization, a Multidisciplinary Design Optimization procedure is developed to optimize an existing Cross-Car Beam model with respect to the cost. Topology, Topography, and gauge optimizations are employed in the development of the optimization disciplines. Based on a qualitative cost assessment, penalty functions are designed to penalize costly designs. Noise-Vibration-Harshness (NVH) performance is the key constraint of the optimization. To fulfill this requirement, natural frequencies are obtained using modal analysis. Undesirable designs with respect to the NVH criteria are gradually eliminated from the optimization cycles. The new design is verified by static loading scenario and evaluated in terms of the cost saving it offers.

Thesis (MScEng)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: The various applications of Information and Communication Technologies (ICTs) in healthcare are increasingly effective to improve the cost-effectiveness and quality of healthcare service delivery. Telemedicine is such an application, using ICTs to provide health services over a distance. Since 1997, the South African Department of Health has invested large amounts of capital to implement telemedicine systems in South Africa. Unfortunately, telemedicine programs have had little success since, leading to many workstations standing dormant. Telemedicine implementation decision making that is based on insufficient evidence is identified as one of the underlying problems that cause telemedicine programs to fail. It is proposed that implementation decisions should be based on quantifiable evidence regarding the potential benefits of telemedicine. A decision support system is developed that can be used to quantify potential benefits and plan telemedicine implementation programs accordingly. The decision support system is modelled and demonstrated using data from the Eastern Cape public health sector. The first phase of the system guides decision makers to identify potential telemedicine benefits as well as data sources that can be used to measure these benefits. The system is scoped to focus on the application of telemedicine to support patient referrals between hospitals. Data sources are considered accordingly, with electronic health record (EHR) data proving to be a feasible primary source for needs assessments, however limiting the benefits that can be quantified. The analysis of the needs assessment is included in the second phase of the decision support system. Data are extracted, transformed and loaded into a data warehouse from where it can be analysed. The system includes three analysis steps to: map referral patterns, analyse potential benefits of telemedicine programs and determine cost-effective telemedicine solutions by allocating equipment at different hospitals. Analysis techniques used in the system include Pareto analysis, economic analysis, linear programming and the use of a genetic algorithm. It is proposed that the potential benefit results and equipment allocation algorithm be used to plan telemedicine programs for continuous evaluation. The final phase of the system therefore guides decision makers to use the results for implementation planning as well as evaluability assessments, for future management and evaluation of telemedicine programs. The decision support system is validated using patient referral data from the Western Cape public health sector. The case study proved that the system is applicable to the real-world and could be a valuable tool for decision makers to base telemedicine implementation planning on quantifiable evidence. The limitation on size and quality of both the Eastern Cape and Western Cape data sets, caused that the full potential of the system could not be demonstrated and validated. It is recommended that the quality standards of EHR referral reports be improved, to ensure more accurate benefit results. Future work is recommended to include qualitative needs assessments in the scope of the decision support system, hereby increasing the amount of benefits to be assessed. Although it is expected that the developed system is capable to support even better resolution decisions with more detailed data sets, the system developed in this study proved already adequate for improved implementation decision making. This could lead to higher success rates of telemedicine programs and ultimately better quality healthcare for all. / AFRIKAANSE OPSOMMING: Die verskillende toepassings van Informasie en Kommunikasie Tegnologie (IKT) in gesondheidsorg, speel ʼn rol in toenemende doeltreffendheid om die koste-effektiwiteit en kwaliteit van gesondheidsorg dienslewering te verbeter. Tele-geneeskunde is een van hierdie toepassings, wat IKT gebruik om gesondheidsdienste oor ʼn afstand te kan voorsien. Die Suid-Afrikaanse Departement van Gesondheid belê sedert 1997, groot bedrae kapitaal in die implementering van tele-geneeskunde stelsels, in Suid-Afrika. Ongelukkig het tele-geneeskunde programme min sukses behaal sedertdien, wat veroorsaak dat vele werkstasies dormant is. Die basering van implementeringsbesluite op onvoldoende getuienis, is geïdentifiseer as een van die onderliggende probleme wat veroorsaak dat tele-geneeskunde programme misluk. Daar word voorgestel dat implementeringsbesluite gebaseer moet word op kwantifiseerbare getuienis ten opsigte van die potensiële voordele van telemedisyne. ʼn Besluitnemingsondersteuning stelsel is ontwikkel wat gebruik kan word om die potensiële voordele te kwantifiseer en dienooreenkomstig implementering van tele-geneeskunde programme te beplan. Die stelsel is gemodelleer en gedemonstreer aan die hand van data uit die Oos-Kaap publieke gesondheidsektor. Die eerste fase van die stelsel begelei besluitnemers om potensiële voordele van telegeneeskunde, sowel as data-bronne wat gebruik kan word om hierdie voordele te meet, te identifiseer. Die stelsel is beperk tot ʼn fokus op die ondersteuning wat tele-geneeskunde aan hospitaal pasiënt verwysingstelsels, kan bied. Data bronne is dienooreenkomstig oorweeg: elektroniese mediese rekords (EMR) word erken as ʼn gunstige primêre databron, maar veroorsaak egter beperkings op die aantal voordele wat gekwantifiseer kan word. Die behoeftebepaling word uitgevoer in die tweede fase van die besluitnemingsondersteuning stelsel. Data is onttrek, getransformeer is en gelaai in 'n data stoor, vanwaar dit ontleed kan word. Die stelsel sluit drie analisestappe in: verwysingspatroon analise, berekening van potensiële voordele vir tele-geneeskunde programme en die bepaling van koste-effektiewe oplossings deur toekenning van toerusting by verskillende hospitale. Die analise tegnieke wat in die stelsel gebruik word, sluit die volgende in: Pareto analise, ekonomiese analise, lineêre programmering en 'n genetiese algoritme. Die gebruik van potensiële voordeel resultate en die toerusting toekenning algoritme word voorgestel vir die beplanning vir deurlopende evaluering in tele-geneeskunde programme. Die finale fase van die stelsel is gestruktureer, om besluitnemers te begelei in die gebruik van analise resultate, vir implementering beplanning sowel as evalueerbaarheid studies, wat sodoende deurlopende evaluering en bestuur van tele-geneeskunde programme sal verbeter.Die besluitnemingsondersteuning stelsel is gevalideer deur pasiënt verwysings data van die Wes-Kaap publieke gesondheidsektor, te gebruik. Die gevallestudie het bewys dat die stelsel toepaslik is in die werklike wêreld en kan as ʼn waardevolle hulpmiddel vir besluitnemers dien om tele-geneeskunde implementering beplanning op kwantifiseerbare bewyse te baseer. Die beperkings op die grootte en gehalte van beide die Oos-Kaap en Wes-Kaap datastelle het veroorsaak dat die stelsel nie tot sy volle reg gedemonstreer en gevalideer kon word nie. Verbeterings in kwaliteit standaarde van EMR verwysing data word aanbeveel om meer akkurate resultate te bekom. Verdere studies wat die byvoeg van kwalitatiewe meetings in die stelsel ondersoek, sal die omvang van potensiële voordele verbeter en dus die algehele waarde van die stelsel verbeter. Alhoewel die ontwikkelde stelsel in staat is om beter resolusie besluite te kan ondersteun met meer gedetailleerde data, is dit bewys dat die huidige stelsel reeds voldoende is om besluitneming te verbeter. Beter besluitneming gevolglik lei tot hoër sukseskoerse van tele-geneeskunde programme en uiteindelik verbeterde gehalte gesondheidsorg vir almal.

Energy conversion devices using solid-state magnetocaloric materials have the potential to reduce energy consumption and mitigate environmental pollutants. To overcome the limited magnetic entropy change of magnetocaloric materials, magnetic refrigeration devices typically use the active magnetic regenerator (AMR) cycle. AMR devices have demonstrated promising performance, however costs must be reduced for broad market penetration. Although the magnet cost is of greatest importance for commercialization, literature has decoupled magnet design from AMR optimization. And while multilayered regenerators can improve performance without increasing cost, a number of questions remain unanswered as a result of the prohibitive parameter space. This dissertation explores methods of improving AMR performance and decreasing cost both at the subsystem level, namely the magnetocaloric regenerator, fluid flow system and magnetic field source, and the device level by coupling the regenerator and magnet design problems in a cost optimization framework. To improve AMR performance, multilayered regenerators with second-order magnetocaloric materials are experimentally and numerically investigated, yielding insight on how individual layers behave and interact over a wide range of regenerator compositions and operating parameters. An efficient AMR modeling approach is presented where individual layers are treated as cascaded AMR elements, and simulations are in excellent agreement with experiments. Insights from the computationally efficient model are used to inform device modifications, and a no-load temperature span of 40 K is measured in close proximity to the simulated optimum; one of the highest in literature. To simultaneously decrease AMR costs, a permanent magnet optimization framework is explored that is conducive to nonlinear objectives and constraints. This is used to investigate the optimal design of permanent magnet structures with reduced rare-earth permanent magnet materials. The regenerator and magnet design problems are then coupled in a permanent magnet topology optimization to minimize the combined capital and operating costs of an AMR. The optimal magnetic field waveform and the optimal means of producing this waveform are simultaneously obtained. The lifetime ownership costs of the optimized AMR device are shown to be in the realm of existing entry-level cooling devices. The presented cost optimization framework is of interest to both scientists and engineers, and demonstrates the importance of fast AMR models in identifying system designs, regenerator compositions and operating regimes that increase AMR performance and decrease cost. / Graduate

abstract: Schools all around the country are improving the performance of their buildings by adopting high performance design principles. Higher levels of energy efficiency can pave the way for K-12 Schools to achieve net zero energy (NZE) conditions, a state where the energy generated by on-site renewable sources are sufficient to meet the cumulative annual energy demands of the facility. A key capability for the proliferation of Net Zero Energy Buildings (NZEB) is the need for a design methodology that identifies the optimum mix of energy efficient design features to be incorporated into the building. The design methodology should take into account the interaction effects of various energy efficiency measures as well as their associated costs so that life cycle cost can be minimized for the entire life span of the building. This research aims at developing such a methodology for generating cost effective net zero energy solutions for school buildings. The Department of Energy (DOE) prototype primary school, meant to serve as the starting baseline, was modeled in the building energy simulation software eQUEST and made compliant with the requirement of ASHRAE 90.1-2007. Commonly used efficiency measures, for which credible initial cost and maintenance data were available, were selected as the parametric design set. An initial sensitivity analysis was conducted by using the Morris Method to rank the efficiency measures in terms of their importance and interaction strengths. A sequential search technique was adopted to search the solution space and identify combinations that lie near the Pareto-optimal front; this allowed various minimum cost design solutions to be identified corresponding to different energy savings levels. Based on the results of this study, it was found that the cost optimal combination of measures over the 30 year analysis span resulted in an annual energy cost reduction of 47%, while net zero site energy conditions were achieved by the addition of a 435 kW photovoltaic generation system that covered 73% of the roof area. The simple payback period for the additional technology required to achieve NZE conditions was calculated to be 26.3 years and carried a 37.4% premium over the initial building construction cost. The study identifies future work in how to automate this computationally conservative search technique so that it can provide practical feedback to the building designer during all stages of the design process. / Dissertation/Thesis / Masters Thesis Built Environment 2016

L’optimisation de la maintenance industrielle revêt différents aspects suivant les objectifs fixés par l’exploitant industriel. L’objectif le plus courant est la réduction des arrêts et des pannes. Le but est d’assurer une disponibilité élevée de l’équipement. Nous allons plus loin en nous posant la question de l’efficience des coûts de maintenance et de la rentabilité. La réponse donnée ici à cette question provient des résultats d’une fonction de coût associée à une plateforme de simulation basée sur les systèmes multiagents. Le choix du paradigme Agent est motivé par l’utilisation des SMA à d’autres fins de simulation et qu’ils garantissent une forme de souplesse quant à l’évolution du contexte métier. La thèse porte sur un modèle de systèmes multiagents destiné à améliorer la gestion des parcs éoliens à travers la définition d'un ensemble de critères financiers propres à l’exploitant éolien. / Optimization & maintenance in the Industrial sector covers different aspects according to the objectives set by the industrial operator. Their common goal is to reduce downtime and failures. For the windfarm operators the goal is to ensure the wind farms high availibility. We went one step further by asking the question of the efficiency of maintenance costs and the profitability. The answer to this question comes from the results of a cost function associated to a simulation model based on multiagents systems. The choice of the multiagent paradigm is motivated by the use of MAS for other simulation purposes and the fact that they guarantee a kind of flexibility regarding the evolution in a moving business context. This Phd thesis focuses on a multi-agent systems model designed to improve the management of wind farms through the definition of a set of financial criteria specific to the wind farm operators.

Varje gång en ny byggnad inreds eller renoveras behöver stora, tunga och otympliga föremål som skåp, diskhoar, handfat, fläktar med mera installeras i kök och badrum. Det finns olika system för att montera dessa men det kan ofta vara en komplicerad process. 2Xarm är ett verktyg som gör kök- och badrumsinstallationer säkert och smidigt. Skåp, hyllor och annat lyfts med verktyget för att sedan justeras och hållas på plats där de ska monteras. I nuläget är verktyget för dyrt att tillverka för att kunna säljas med tillräckligt god marginal. Därför var syftet med detta arbete att minska verktygets tillverkningskostnad utan att förändra dess patenterade design och funktion. Arbetet har utförts med hjälp av datorstödd modellering och via informationssökning. En fysisk prototyp lånades och modellerades av. Sedan har tillverkningsmetoder och materialval undersökts varpå tre alternativa konstruktionslösningar togs fram. Dessa anses dock inte ha minskat tillverknigskostnaden nämnvärt. Den huvudsakliga slutsatsen är att verktygets tillverkningskostnad inte gick att minska nämnvärt utan att förändra dess funktionalitet och patenterad design. Alternativt hade även en större produktionsvolym varit en effektiv metod att minska enhetskostnaden. / The 2Xarm tool simplifies kitchen and bathroom installations by securely lifting and installing heavy objects like cabinets and sinks. However, its current manufacturing cost is too high to sell the tool at sufficient profit margains. This report aimed to identify cost-saving measures while preserving the tool’s patented design and functionality. Using computer-aided modeling and research, we analyzed a physical prototype, explored different manufacturing methods, and evaluated material choices. These efforts resulted in three alternative design solutions that aimed to simplify the manufacturing and assembly process. However, these changes ultimately did not significantly reduce the manufacturing cost. In conclusion, achieving substantial cost reduction for the tool without compromising its design and functionality proved difficult. Alternatively, increasing production volume could be an effective approach to lower the unit cost.

This is probably the most appropriate time for the development of robust and reliable structural damage detection systems as aging civil engineering structures, such as bridges, are being used past their life expectancy and beyond their original design loads. Often, when a significant damage to the structure is discovered, the deterioration has already progressed far and required repair is substantial. This is both expensive and has negative impact on the environment and traffic during replacement. For the exposed reasons the demand for efficient Structural Health Monitoring techniques is currently extremely high. This licentiate thesis presents a two-stage model-free damage detection approach based on Machine Learning. The method is applied to data gathered in a numerical experiment using a three-dimensional finite element model of a railway bridge. The initial step in this study consists in collecting the structural dynamic response that is simulated during the passage of a train, considering the bridge in both healthy and damaged conditions. The first stage of the proposed algorithm consists in the design and unsupervised training of Artificial Neural Networks that, provided with input composed of measured accelerations in previous instants, are capable of predicting future output acceleration. In the second stage the prediction errors are used to fit a Gaussian Process that enables to perform a statistical analysis of the distribution of errors. Subsequently, the concept of Damage Index is introduced and the probabilities associated with false diagnosis are studied. Following the former steps Receiver Operating Characteristic curves are generated and the threshold of the detection system can be adjusted according to the trade-off between errors. Lastly, using the Bayes’ Theorem, a simplified method for the calculation of the expected cost of the strategy is proposed and exemplified. / <p>QC 20170420</p>