Life Cycle Cost Optimization Research Articles

Probabilistic framework for product design optimization and risk management

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

An asset management approach to optimize water meter replacement

Despite existence of many developed approaches for identifying optimal time of Water Meters (WMs) replacement, less attention has been paid to the impact of WM failure risk on utilities revenues and the proper time of replacement. Here, the Asset Management (AM) approach is introduced as a holistic managing framework optimizing Life Cycle Costs (LCC), especially incorporating WM failure risk in asset replacement decisions. The proposed AM framework is based on four core steps. The application of the proposed framework for a real case study has shown confidence in finding the economical time of WM replacement. It was further shown that the risk costs associated with WM failure have higher impacts on optimal time of WM replacement than the revenue lost due to its inaccuracy. The sensitivity analyses of input data values show that water price, initial investment and accuracy degradation rate have the highest impacts on LCCs amongst other parameters.

BIM-based approach for optimizing life cycle costs of sustainable buildings

Abstract This paper proposes a framework that integrates Building Information Modeling (BIM) with Genetic Algorithm Optimization and Monte-Carlo Simulation. The developed framework helps in implementing a stochastic Life-Cycle Cost (LCC) model for building to select the optimum building materials alternatives and discover the most influential building system in each cost element starting from initial cost to end on life cost. Genetic Algorithms Optimization technique is utilized to select the optimum alternatives of building systems taking in consideration sustainability aspects. The Monte-Carlo Simulation model is used as a fitness function for the optimization model. The environmental aspect of building is achieved by considering the maximum number of points that can be awarded under the Leadership in Energy and Environmental Design (LEED) rating system. Sensitivity analysis is performed on the optimum solutions that are chosen by optimization a model to examine the effect of different building systems on LCC and its components through computing the rank order of building systems and the target output. A case study is presented to demonstrate the practical features of the proposed framework.

An approach for an educational building stock energy retrofits through life-cycle cost optimization

ABSTRACTImprovement of energy efficiency applications through public buildings can play a leadership role demonstrating best practice in environmental sustainability for the wider population. Therefore, this study was conducted on an educational building stock in Istanbul for a year. A selected energy classification method was applied in order to designate the energy classes and related future target level assumption, which was assigned by EPBD Recast (2010). A representative base case from the stock was determined to analyse the cost-optimal levels of the energy retrofits. GenOpt optimization tool was used to apply the energy retrofit scenarios in order to achieve a set of optimum scenarios in terms of energy and cost (energy frontiers) and determine the cost-optimal energy efficiency level through a calibrated energy model. Finally, results were evaluated from energy efficiency and cost-optimal point of views.

Comparing life cycle cost and environmental impact optimizations of a low voltage dry type distribution transformer

PurposeLife cycle analysis (LCA) is more and more used in the context of electromagnetic product design. But it is often used to check a design solution regarding environmental impacts after technical and economical choices. This paper aims to investigate life cycle impact optimization (LCIO) and compare it with the classical life cycle cost optimization (LCCO).Design/methodology/approachFirst, a model of a dry-type transformer using different materials for windings and the magnetic core is presented. LCCO, which is a mixed continuous-discrete, multi-objective technico-economic optimization, is done using both deterministic and genetic algorithms. LCCO results and optimization performances are analyzed, and an LCA is presented for a set of optimal solutions. The final part is dedicated to LCIO, where the paper shows that these optimal solutions are close to those obtained with LCCO.FindingsThis paper investigated LCIO using an environmental impacts model that has been introduced in the optimization framework Component Architecture for the Design of Engineering Systems. The paper shows how a mixed continuous-discrete, multi-objective technico-economic optimization can be done using an efficient deterministic optimization algorithm such as Sequential Quadratic Programming. Thanks to the technico-economic-environmental model and the efficient optimization algorithm, both LCCO and LCIO were performed separately and together. It has been shown that optimal solutions are similar, leading to the conclusion that only one modeling is required (economic or environmental) but on the life cycle.Originality/valueThe classical sequential methodology of design is improved here by the use of a model of calculation of the environmental impacts allowing the optimization. This original optimization allowed the authors to show that an analysis of the life cycle from an economic point of view or from an environmental point of view led to quasi-equivalent technical solutions. The key is to take into account the life cycle of the product.

Near Zero Energy House (NZEH) Design Optimization to Improve Life Cycle Cost Performance Using Genetic Algorithm

Near Zero Energy House (NZEH) is a housing building that provides energy efficiency by using renewable energy technologies and passive house design. Currently, the costs for NZEH are quite expensive due to the high costs of the equipment and materials for solar panel, insulation, fenestration and other renewable energy technology. Therefore, a study to obtain the optimum design of a NZEH is necessary. The aim of the optimum design is achieving an economical life cycle cost performance of the NZEH. One of the optimization methods that could be utilized is Genetic Algorithm. It provides the method to obtain the optimum design based on the combinations of NZEH variable designs. This paper discusses the study to identify the optimum design of a NZEH that provides an optimum life cycle cost performance using Genetic Algorithm. In this study, an experiment through extensive design simulations of a one-level house model was conducted. As a result, the study provide the optimum design from combinations of NZEH variable designs, which are building orientation, window to wall ratio, and glazing types that would maximize the energy generated by photovoltaic panel. Hence, the design would support an optimum life cycle cost performance of the house.

On the performance of LCC optimization software OPERA-MILP by comparison with building energy simulation software IDA ICE

From an economic point of view, it is crucial to minimize the life cycle costs (LCC) of buildings undergoing energy renovations, hence an optimization approach is needed. Building energy use and power demand as well as energy efficiency measures are important issues while performing an LCC optimization. Thus it is of great importance to accurately predict the building energy use and power demand before and after energy renovation.This paper aims to address the performance of an in-house LCC optimization software, OPERA-MILP, which has a rather fast optimization procedure. The aim is fulfilled through comparison with building energy simulation software IDA ICE before and after cost-optimal energy renovation. Three historic buildings with different layout and construction properties are used as a case study.The results show good agreement in the calculations of buildings' power demand and energy use between OPERA-MILP and IDA ICE. The percentage difference in calculated annual energy use and buildings' power demand with OPERA-MILP compared to IDA ICE is shown to be maximum 11% and 8% for the studied climate zones, respectively. Total impact on LCC is estimated to be equal to or less than 8%.

Lifecycle cost optimization of tuned mass dampers for the seismic improvement of inelastic structures

SummaryThe seismic performance of tuned mass dampers (TMDs) on structures undergoing inelastic deformations may largely depend on the ground motion intensity. By estimating the impact of each seismic intensity on the overall cost of future seismic damages, lifecycle cost (LCC) proves a rational metric for evaluating the benefits of TMDs on inelastic structures. However, no incorporation of this metric into an optimization framework is reported yet. This paper presents a methodology for the LCC‐optimal design of TMDs on inelastic structures, which minimizes the total seismic LCC of the combined building‐TMD system. Its distinctive features are the assumption of a mass‐proportional TMD cost model, the adoption of an iterative suboptimization procedure, and the initialization of the TMD frequency and damping ratios according to a conventional linear TMD design technique. The methodology is applied to the seismic improvement of the SAC‐LA benchmark buildings, taken as representative of standard steel moment‐resisting frame office buildings in LA, California. Results show that, despite their limited performance at the highest intensity levels, LCC‐optimal TMDs considerably reduce the total LCC, to an extent that depends on both the building vulnerability and the TMD unit cost. They systematically present large mass ratios (around 10%) and frequency and damping ratios close to their respective linearly designed optima. Simulations reveal the effectiveness of the proposed design methodology and the importance of adopting a nonlinear model to correctly evaluate the cost‐effectiveness of TMDs on ordinary structures in highly seismic areas.

Investigating cost-optimal refurbishment strategies for the medieval district of Visby in Sweden

This paper presents a methodology, using Life Cycle Cost (LCC) optimization and building categorization, to achieve a systematic study of the cost-optimal energy efficiency potential (CEEP) for 920 listed buildings in the medieval district of Visby in Sweden. The aim is to study the CEEP and CO2 emission reductions for this city that is included in the World Heritage List by UNESCO. The total CEEP is found to be 31% (20.6 GWh) resulting in a CO2 reduction of 57% (33.3 kton). The categorization method showed that the buildings could be divided in four clusters depending on building material, geometry and layout. The LCC analysis revealed that the energy efficiency measure packages were cluster specific. It is shown that multi-story wood buildings (Cluster II) have lowest specific LCC, and would arguably be the starting point for a renovation process. Presently most of the studied buildings are connected to the district heating (DH). The results show that heat pump (HP) and wood boiler (WB) is cost-optimal heating system for multi-story stone and wood buildings, respectively. In order for the DH to compete with HP and WB, the DH price needs to be reduced by 23% and 16%.

Challenges And Opportunities in Applying Vibration Based Condition Monitoring in Railways

Electrical rotating machines are among the most common assets used in industry. In railways applications these devices are present in fixed and rolling stock systems, such as turnouts and traction components. Condition based maintenance (CBM) of rotating machines may significantly improve the availability of critical railway assets. Moreover, by efficiently assessing the state of health of targeted components, it becomes possible to introduce advanced asset management strategies for life cycle cost optimization. In comparison with traditional maintenance approaches, health monitoring enables better maintenance scheduling, fleet size optimization and maintenance costs reduction. CBM applied to rotating machines has been actively studied by many researchers in a wide variety of fields such as: signal processing, anomaly detection, failure diagnostic and failure prognostics. However, there is still a considerable gap between the methods studied in research and the ones successfully applied in industry, and especially in the railway field. This paper discusses the challenges and opportunities for application of CBM methods to electrical rotating machines in railway applications. For the purpose of illustration, a case study focusing on traction motor bearings is considered. Time domain and frequencydomain signal processing techniques are employed to extract features from bearing degradation data. The data analyzed in the present study have been obtained in a bearing test bench and during a test conducted on a real traction motor used in trains. The results of the considered methods are discussed and future research directions are suggested.

Fatigue and fracture life-cycle cost assessment of a Miter gate with multiple cracks

Abstract Fatigue cracks in Miter gates are considered a nuisance as they require periodic inspection and repair. If left unattended, the cracks could grow to reach a critical length and threaten the integrity of the structure. Although the cracks are typically characterized by a stable propagation rate, the scatter in fatigue performance is difficult to quantify and could be on the order of thousands or even millions of cycles. The development of maintenance and management programs for Steel Hydraulic Structures (SHSs) should therefore account for the inherent scatter in performance through probabilistic fatigue assessment. The assessment can be performed through conducting large number of numerical (e.g. finite element analysis) or analytical (e.g. mathematical formulation) simulations that account for the inherent statistical scatter in both load and resistance. In this study, a framework for probabilistic assessment of the propagation rate of cracks in Miter gates using finite element Monte Carlo simulations was developed. The parameters influencing the propagation rate were treated as random variables with predefined statistical distributions. In addition, a life-cycle cost optimization framework was devised using the results of the probabilistic assessment to derive optimal inspection/repair schedule patterns such that the service life of the Miter gate could be extended as required. The framework was tested on nine different cases and an optimal schedule is obtained for each case successfully.

Probabilistic Framework for Product Design Optimization

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. Our main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

Hydrogen station siting optimization based on multi-source hydrogen supply and life cycle cost

Hydrogen station siting plays an important role in hydrogen-energy infrastructure construction, and it's different from gas station siting. A gas station has a unitary way of fuel transport and a unitary fuel supplier, hence no consideration given to factors like fuel supplier and way of fuel transport at the time of siting it. However, hydrogen for a hydrogen fueling station can be supplied jointly from a couple of different sources nearby. Since there is a diversity of hydrogen price and productivity between different sources, hydrogen fueling station siting also entails consideration of the effect of the proportions of hydrogen supplied by the sources on hydrogen's life cycle cost. With the purpose of minimizing hydrogen's life cycle cost, this paper creates a mathematical model for station siting, largely for the case that each station can get hydrogen supply from combined multiple sources, and considers the effect of geographical information factors on station siting. The effect of geographical information factors on such siting is described herein in two cases to avoid selecting a must-not-build location and rebuilding into a gasoline-hydrogen fueling station at an existing gas station location. The latter can reduce station construction and operating costs. By creating a particle swarm optimization (PSO) example for station siting with Shanghai-Nanjing Expressway and constructing a position particle swarm in the form of 5D vector in order to optimize 5 station locations at the same time as well a weight particle swarm in the form of 2D matrix in order to optimize the multi-source hydrogen supply programs, the paper works out optimal station construction locations on condition of multi-source hydrogen supply, multi-source hydrogen supply programs, ways of storage and transport and corresponding hydrogen's optimal life cycle cost.

Construction Performance Optimization toward Green Building Premium Cost Based on Greenship Rating Tools Assessment with Value Engineering Method

Green building concept becomes important in current building life cycle to mitigate environment issues. The purpose of this paper is to optimize building construction performance towards green building premium cost, achieving green building rating tools with optimizing life cycle cost. Therefore, this study helps building stakeholder determining building fixture to achieve green building certification target. Empirically the paper collects data of green building in the Indonesian construction industry such as green building fixture, initial cost, operational and maintenance cost, and certification score achievement. After that, using value engineering method optimized green building fixture based on building function and cost aspects. Findings indicate that construction performance optimization affected green building achievement with increasing energy and water efficiency factors and life cycle cost effectively especially chosen green building fixture.

Hydrogen refueling station siting of expressway based on the optimization of hydrogen life cycle cost

Hydrogen-energy expressway system planning involves load prediction, hydrogen source planning and hydrogen station planning. Exemplary construction of a run-for-profit hydrogen-energy expressway must attach importance to comprehensive evaluation of the effect of investment. The paper analyzes current situation of hydrogen-energy expressway construction, points out that adequate consideration should be given in all aspects of hydrogen energy's life cycle cost, such as hydrogen production, transport, storage, usage, CO2 disposal, carbon tax, hydrogen station's annual construction investment and annual operating expenses. The paper suggests that hydrogen made from discarded electricity of clean energies and hydrogen produced as byproduct during chemical plant production should be utilized to reduce production cost. On the basis of hydrogen energy's life cycle cost analysis, the paper creates a hydrogen station siting optimization model, with the constraints of hydrogen station's supply radius, hydrogen source's productivity and geographic information factor, so as to increase the applicability and level of hydrogen-energy expressway planning effectively.

Lifetime reliability-based optimization of post-tensioned box-girder bridges

Abstract This paper presents a lifetime reliability-based approach for the optimization of post-tensioned concrete box-girder bridges under corrosion attack. The proposed approach is illustrated by determining the optimal life-cycle cost and CO 2 emissions of several initial designs of post-tensioned box-girder bridges with different objectives, i.e. the lowest initial costs, the longest corrosion initiation time, or the maximum safety. The study was conducted in two steps. Firstly, the Pareto set presents initial designs considering the cross-section geometry, the concrete strength, the reinforcing steel and the prestressing steel. Secondly, the maintenance optimization was conducted with the proposed method, aimed at minimizing the economic, environmental and societal impacts of the bridge while satisfying the reliability target during its life-span. Effective maintenance is able to extend the service life of the bridge with the minimum cost and CO 2 emissions. It is indicated that a durability-conscious initial design is particularly beneficial for life-cycle performance. Besides, the emphasis on the initial design can also have an effect on the life-cycle performance of bridges. It is found that designs with longer corrosion initiation time are associated with lower life-cycle cost, especially when using concrete of higher strength. Findings from the current paper also indicate that optimal maintenance strategies are more likely to be those with fewer maintenance actions that repair all deteriorating structures simultaneously.

Life Cycle Costing as an Important Contribution to Feasibility Study in Construction Projects

The purpose of this paper is to highlight the role of life cycle cost (LCC) analysis in the feasibility study of construction projects, especially in the public sector. Feasibility study is usually conducted in the early phase of construction projects when the greatest benefit of LCC can be obtained. The commonly used construction cost minimization approach should be replaced with LCC optimization. In order to achieve the maximum value for money, all costs incurred over the whole life span must be evaluated. Life cycle costing is a method of economic analysis directed at all costs related to constructing, operating, and maintaining a construction project over a defined period of time. The optimization of the LCC of a project, construction or equipment, is essential for the complex decision-making process. It is then at this point that the solution with the minimum value of LCC can be chosen. The public sector in the Czech Republic is now beginning to require quantification of LCC when deciding on construction. In addition, LCC has become a criterion in public tenders. This paper summarizes the experience of assessing building designs in terms of LCC. Not only public sector benefits are identified and summarized but also some significant difficulties. Case studies are provided.

Eleven Nearly Zero New Building Life Cycle Cost and Dynamic Performance Optimization by Computer Modeling in Cold Climate

The study aims to generate Building system performance design optimization for 11 nearly zero energy new building (nZEnB) types in the cold climate conditions for decision making. The coupling evolutionary algorithms with a building dynamic simulation engine has been applied to reach the “true” optimal solutions. Life cycle cost and performance modulation was carried out in the multi-objective computer model. The calculation of cost optimality was performed on predefined 11 reference building types by taking into account prices as they have been paid by the end consumer including taxes. 960 000 simulation variants were calculated for each building type. This paper proposes coupling of multivariate engine with the Pareto analysis for reduction of costs and energy use, while taking in consideration fiscal and resource economy long term trends as well as fossil energy replacement with the renewable ones from investment perspective.

Life-cycle cost optimization of the seismic retrofit of existing RC structures

The life-cycle cost analysis of buildings prone to seismic risk is a critical issue in structural engineering. Expected loss, including damage and repair costs, is an important parameter for structural design. The combination of economic theory and computer technology allows for a more developed approach to the design and construction of structures than ever before. In this study, a simplified method based on a semi-probabilistic methodology is developed to evaluate the economic performance of a building prone to seismic risk. The proposed approach aims to identify the most cost-effective strengthening strategies and strengthening levels for existing structures during their structural lifetime. To achieve this, the method identifies the optimal strengthening level, computing on the one hand the costs of strengthening the structure at different performance levels for each strategy, and, on the other, the expected seismic loss during the structure’s lifetime. To assess the expected loss, the building is divided into several components, both structural and non-structural. A set of fragility curves is assigned for each component. Then, once the structural model and the various components of the building, with the corresponding fragility curves, are defined, a loss assessment is performed using a static non-linear analysis. The summation of the strengthening costs and the discounted expected losses produces a relationship between the total costs and the strengthening level. The minimum of this relationship identifies the most cost-effective strengthening intervention. As a case study, this method is applied to an existing reinforced concrete (RC) structure severely damaged by the 2009 earthquake in L’Aquila. Different strategies are analyzed, namely the FRP (fiber reinforced polymer) strengthening of elements, the RC jacketing of columns, RC exterior shear wall insertions, and the base isolation of the building.

LCC assessments and environmental impacts on the energy renovation of a multi-family building from the 1890s

The 2020 and 2050 energy targets increase requirements on energy performance in the building stock, thus affecting both listed and non-listed buildings. It is important to select appropriate and cost-optimal energy efficiency measures, using e.g. Life Cycle Cost (LCC) optimization. The aim of this paper is to find cost-optimal packages of energy efficiency measures (EEMs) as well as to explore the effects of specific predesigned energy target values for a listed Swedish multi-family building from the 1890s. The purpose is also to show the effects on energy use, LCC, primary energy use and CO2 emissions of different energy targets, discount rates, electricity prices and geographic locations. The results show that separate energy targets could be an effective way to simplify the implementation for listed buildings. Furthermore, a cost-optimal package of EEMs is more sensitive to changes in discount rate than in electricity price. The energy renovation has impact on the primary energy use and CO2 emissions. The lower the discount rate is, the more EEMs will be implemented and the easier the national energy targets may be achieved. A higher electricity price also leads to more EEMs being implemented but at the same time higher running costs.