Layout Decision Analysis and Design is a ubiquitous problem in a variety of work domains that is important from both strategic and operational perspectives. It is largely a complex, vague, difficult, and ill-structured problem that requires intelligent and sophisticated decision analysis and design support. <br /><br /> Inadequate information availability, combinatorial complexity, subjective and uncertain preferences, and cognitive biases of decision makers often hamper the procurement of a superior layout configuration. Consequently, it is desirable to develop an intelligent decision support system for layout design that could deal with such challenging issues by providing efficient and effective means of generating, analyzing, enumerating, ranking, and manipulating superior alternative layouts. <br ><br /> We present a research framework and a functional prototype for an interactive Intelligent System for Decision Support and Expert Analysis in Multi-Attribute Layout Optimization (IDEAL) based on soft computing tools. A fundamental issue in layout design is efficient production of superior alternatives through the incorporation of subjective and uncertain design preferences. Consequently, we have developed an efficient and Intelligent Layout Design Generator (ILG) using a generic two-dimensional bin-packing formulation that utilizes multiple preference weights furnished by a fuzzy Preference Inferencing Agent (PIA). The sub-cognitive, intuitive, multi-facet, and dynamic nature of design preferences indicates that an automated Preference Discovery Agent (PDA) could be an important component of such a system. A user-friendly, interactive, and effective User Interface is deemed critical for the success of the system. The effectiveness of the proposed solution paradigm and the implemented prototype is demonstrated through examples and cases. <br /><br /> This research framework and prototype contribute to the field of layout decision analysis and design by enabling explicit representation of experts? knowledge, formal modeling of fuzzy user preferences, and swift generation and manipulation of superior layout alternatives. Such efforts are expected to afford efficient procurement of superior outcomes and to facilitate cognitive, ergonomic, and economic efficiency of layout designers as well as future research in related areas. <br /><br /> Applications of this research are broad ranging including facilities layout design, VLSI circuit layout design, newspaper layout design, cutting and packing, adaptive user interfaces, dynamic memory allocation, multi-processor scheduling, metacomputing, etc.

Detta examensarbete har utförts som en del av högskolutbildningen Maskinteknik vid Linköpings universitet. Rapporten är skriven på uppdrag av Blomberg &amp; Stensson AB i Katrineholm som ingår i en företagsgrupp med företaget X-modul samt Engströms Verkstäder. Företaget erbjuder produkter i stor variation som verktygsvagn, renhetsskåp, arbetsbänk och en flexibel barack som kan byggas som ett boende, fältsjukhus, toaletter med mera. Produktionen i Katrineholm består främst av plåt- och rörbearbetning.Blomberg &amp; Stensson har på våren 2017 flyttat in i nya lokaler och ska därför optimera sina arbetsområden. Området som fokuseras i detta arbete är kapningsområdet där rör- och balkmaterial kapas. För närvarande finns det inget sätt att kapa material längre än sju meter vilket är grundproblemet i detta arbete, eftersom material måste kapas för hand innan den kan tas in i lokalen. Syftet är att skapa en ny layout för kapningsområdet, samt eliminera säkerhetsrisker, ergonomirisker, slöseririsker och miljörisker. Lösningsförslag ska presenteras på en ny layout samt lösningsförslag på åtgärder för eventuella risker som uppkommer.Genom en övergripande kartläggning av området och dess avgränsningar samt datainsamling genom intervjuer, observationer och litteraturstudier har förståelsen av kapningsproduktionen ökat. Tillgång till egen arbetsplats hos företaget har också varit betydande för arbetets resultat. Med närhet till produktionen och kunnig personal har lett till ett effektivare arbete och ökat förståelsen för arbetsprocessen.När kunskap hade samlats in analyserades området och lösningsförslag på layouts skapades. Layouten fokuseras på att utformas med Lean production, bra ergonomi och bra arbetsmiljö. Lösningsförslag skapades och gick igenom en process där de ansvariga på företaget fick säga sina åsikter och kritisera förslagen. Det tredje förslaget blev godkänt och bestämdes som den layout kapningsområdet skulle ha och en renovering tog fart. Under arbetsgången påpekades flertal gånger om att det behövdes ett koncept för att ta upp vätska som spills under rullbanorna. Ett lösningsförslag till detta skapades samtidigt som en riskanalys utfördes med ansvarig operatör när kapningsområdets design var bestämt.Resultatet presenterar layoutens design som gör det möjligt att kapa material på tolv meter vilket löser problemet. Dessutom presenterar den lösningsförslaget på problemet där vätska som spills samt resultatet från en framgångsrik riskanalys.I diskussionskapitlet har jämförelser före och efter arbetet på layouten och hur förändringarna har tillämpats på arbetsstationen dessutom har frågorna från syftet besvarats. I slutsatsen presenteras bidraget som detta arbete har gett. / This project has been carried out as part of the college education Mechanical Engineering at Linköping University. The report is written on behalf of Blomberg &amp; Stensson AB in Katrineholm and who is a part of a company group with the company named X-module and Engströms Verkstäder. The company offers products in a wide variety such as utility wagon, cleaner cabinet, workbench and a flexible shed that can be built as accommodation, field hospital, toilets and more. Katrineholm’s production consist mainly of sheet- and pipe processing.Blomberg &amp; Stensson has in spring 2017 moved into new facilities and therefore shall optimization be done on their work areas. The work area focused on in this paper is the cutting area where pipe- and beam materials are cut. At present time there is no way to cut materials longer than seven meters which is the basic problem in this paper, as materials must be cut by hand before it can be transported inside the facility. The purpose is the create a new layout for the cutting area and to eliminate any security risks, ergonomics, waste risks and environmental risks. Solution proposals will be presented on a new layout and solution proposals for measures on possible risks that have arisen through the steps of the work.Through an overall mapping of the area and its delimitations and data collection through interviews, observations and literature studies, the understanding of the production increased. With access to an own workspace at the company has also been significant for the work’s results. With close proximity to the production and knowledgeable personnel, has led to more efficient work and has increased understanding of the work process.Once knowledge had been gathered the area was analyzed and layout solutions were created. The layout focuses on being designed with Lean production, good ergonomics and good working environment. Solutions proposals were created and went through a process whereby the personnel in charge in the company were allowed to say their opinions and criticism of the proposals. The third proposal was approved and determined as the layout the cutting area should look like and a renovation took off. During the work of the paper, it was pointed out several times that there was a concept needed for taking up liquid that was spilled out under conveyor belts. A solution proposal for the liquid situation was created while a risk analysis was carried out with the main operator when the design of the area was determined.The result presents the layout design that enables cutting of twelve-meter materials which solves the main problem. In addition, it also presents the solution proposal for the problem where liquid spills as well as the result of the successful risk analysis.In the discussion chapter have before and after comparisons of the differences of the layouts and how changes have been applied to the workstation and answers the questions from the purpose. In conclusion, the contribution of the paper is presented.

Designing structures for lightness is an intelligent and responsible way for engineers and architects to conceive structural systems. Lightweight structures are able to bridge wide spans with a least amount of material. However, the quest for lightness remains an utopia without the driving constraints that give sense to contemporary structural design.<p><p>Previously proposed computational methods for designing lightweight structures focused either on finding an equilibrium shape, or are restricted to fairly small design applications. In this work, we aim to develop a general, robust, and easy-to-use method that can handle many design parameters efficiently. These considerations have led to truss layout optimization, whose goal is to find the best material distribution within a given design domain discretized by a grid of nodal points and connected by tentative bars. <p><p>This general approach is well established for topology optimization where structural component sizes and system connectivity are simultaneously optimized. The range of applications covers limit analysis and identification of failure mechanisms in soils and masonries. However, to fully realize the potential of truss layout optimization for the design of lightweight structures, the consideration of geometrical variables is necessary. <p><p>The resulting truss geometry and topology optimization problem raises several fundamental and computational challenges. Our strategy to address the problem combines mathematical programming and structural mechanics: the structural properties of the optimal solution are used for devising the novel formulation. To avoid singularities arising in optimal configurations, the present approach disaggregates the equilibrium equations and fully integrates their basic elements within the optimization formulation. The resulting tool incorporates elastic and plastic design, stress and displacements constraints, as well as self-weight and multiple loading.<p><p>Besides, the inherent slenderness of lightweight structures requires the study of stability issues. As a remedy, we develop a conceptually simple but efficient method to include local and nodal stability constraints in the formulation. Several numerical examples illustrate the impact of stability considerations on the optimal design.<p><p>Finally, the investigation on realistic design problems confirms the practical applicability of the proposed method. It is shown how we can generate a range of optimal designs by varying design settings. In that regard, the computational design method mostly requires the designer a good knowledge of structural design to provide the initial guess. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

[pt] À medida que o mundo enfrenta a urgente questão das mudanças climáticas, a energia eólica se destaca como uma fonte crítica de energia limpa. No entanto, realizar seu pleno potencial depende da otimização dos layouts de parques eólicos, especialmente à luz do complexo efeito de esteira. Esta dissertação adentra na Otimização de Layout de Parques Eólicos (WFLO, na sigla em inglês) usando o Modelo de Efeito de Esteira de Bastankhah. O escopo deste estudo vai além do design de layout; abrange a intrincada tarefa de mitigar o impacto do efeito de esteira, juntamente com a busca por uma estratégia de negociação com aversão ao risco e maximização de valor. Para contabilizar a aversão ao risco, uma combinação entre o Valor Esperado e os funcionais de medida de risco baseados no quantil esquerdo, a medida de Valor em Risco Condicional (CVaR). Para apoiar esta pesquisa, um pacote de código aberto OptimalLayout.jl foi desenvolvido. Este pacote co-otimiza o posicionamento das turbinas eólicas para mitigar o impacto do efeito de esteira e a estratégia de contratação de um agente/gerador avesso ao risco. Através de uma série de estudos de casos práticos em diversos ambientes dinâmicos, esta pesquisa ilustra a aplicabilidade do WFLO no mundo real. Estas investigações examinam detalhadamente a sua influência na produção de energia e na dinâmica das receitas, oferecendo informações valiosas sobre soluções energéticas sustentáveis. / [en] As the world confronts the pressing issue of climate change, wind power stands out as a critical source of clean energy. However, realizing its full potential relies on the optimization of wind farm layouts, particularly in light of the complex wake effect. This dissertation delves into Wind Farm Layout Optimization (WFLO) using the Bastankhah Wake Model. The scope of this study goes beyond layout design; it encompasses the intricate task of mitigating the wake effect s impact along with the seek for a risk-averse-value maximizing trading strategy. To account for risk-averseness, a combination between Expected Value and the left-side-quantile-based risk-measure functionals, the Conditional Value-at-Risk (CVaR) measure. To support this research, an opensource package OptimalLayout.jl was developed. This package co-optimizes the positioning of wind turbines to mitigate wake effect impact,and the contracting strategy of a Risk-Averse agent/generator. Through a series of practical case studies across diverse dynamic environments, this research illustrates the real-world applicability of WFLO. These investigations intricately examine its influence on power production and revenue dynamics, offering valuable insights into sustainable energy solutions.

Anthropogenic climate change is approaching predicted tipping points and there is an urgent need to de-carbonize energy systems on a global scale. Generation technologies that do not emit greenhouse gas need to be rapidly deployed, and energy grids need to be updated to accommodate an intermittent fluctuating supply. Rapidly advancing battery technology, cost reduction of solar and wind power and other emerging generation technologies are making the needed changes technically and economically feasible. Extracting energy from fast-flowing tidal currents using turbines akin to those used in wind farms, offers a reliable and predictable source of GHG free energy. The tidal power industry has established the technical feasibility of tidal turbines, and is presently up-scaling deployments from single isolated units to large tidal farms containing many turbines. However there remains significant economic uncertainty in financing such projects, partially due to uncertainty in predicting the long-term energy yield. Since energy yield is used in calculating the project revenue, it is of critical importance. Predicting yield for a prospective farm has not received sufficient attention in the tidal power literature. this task has been the primary motivation for this thesis work, which focuses on establishing and validating simulation-based procedures to predict flows through large tidal farms with many turbines, including the back effects of the turbines. This is a challenging problem because large tidal farms may alter tidal flows on large scales, and the slow-moving wake downstream of each rotor influences the inflow to other rotors, influencing their performance and loading. Additionally, tidal flow variation on diurnal and monthly timescales requires long-duration analysis to obtain meaningful statistics that can be used for forecasting. This thesis presents a hybrid simulation method that uses 2D coastal flow simulations to predict tidal flows over long durations, including the influence of turbines, combined with higher-resolution 3D simulations to predict how wakes and local bathymetry influence the power of each turbine in a tidal farm. The two simulation types are coupled using a method of bins to reduce the computational cost within reasonable limits. The method can be used to compute detailed 3D flow fields, power and loading on each turbine in the farm, energy yield and the impact of the farm on tidal amplitude and phase. The method is demonstrated to be computationally tractable with modest high-performance computing resources and therefore are of immediate value for informing turbine placement, comparing turbine farm-layout cases and forecasting yield, and may be implemented in future automated layout optimization algorithms. / Graduate

As wind energy technology continues to mature, farm sizes grow and wind farm layout design becomes more difficult, in part due to the number of design variables and constraints. Wind farm layout optimization is typically approached using gradient-free methods because of the highly multi-modal shape of the wind farm layout design space. Gradient-free method performance generally degrades with increasing problem size, making it difficult to find optimal layouts for larger wind farms. However, gradient-based optimization methods can effectively and efficiently solve large-scale problems with many variables and constraints. To pave the way for effective and efficient wind farm layout optimization for large-scale wind farms, we have worked to overcome the primary barriers to applying gradient-based optimization to wind farm layout optimization. To improve model/algorithm compatibility, we adjusted wake and wind farm models, adding more realistic curvature and smoothness to enable optimization algorithms to travel through areas in the design space where they had previously gotten stuck. We reduced the number of function calls required for gradient-based wind farm layout optimization by over three orders of magnitude for large farms by using algorithmic differentiation to compute derivatives. We reduced the multi-modality of the wind farm layout design space using wake expansion continuation (WEC). We developed WEC to work with existing optimization algorithms, enabling them to get out of local optima while remaining fully gradient-based. Across four case studies, WEC found results with lower wake loss, on average, than the other methods we tested. To resolve concerns about optimization algorithms exploiting model inaccuracies, we compared the initial and optimized layouts to large-eddy simulation (LES) results. The simple models predicted an AEP improvement of 7.7% for a low-TI case, and LES predicted 9.3%. For a high-TI case, the simple models predicted a 10.0% improvement in AEP and LES predicted 10.7%. To resolve uncertainty regarding relative solution quality for gradient-based and gradient-free methods, we collaborated with seven organizations to compare eight optimization methods. Each method was managed by researchers experienced with them. All methods found solutions of similar quality, with optimized wake loss between 15.48 % and 15.70 %. WEC with SNOPT was the only purely gradient-based method included and found the third-to-best solution.