Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.

Strategies for minimising the whole of life cycle cost of reinforced concrete bridge exposed to aggressive environments

n design of bridge structures, it is common to adopt a 100 year design life. However, analysis of a number of case study bridges in Australia has indicated that the actual design life can be significantly reduced due to premature deterioration resulting from exposure to aggressive environments. A closer analysis of the cost of rehabilitation of these structures has raised some interesting questions. What would be the real service life of a bridge exposed to certain aggressive environments? What is the strategy of conducting bridge rehabilitation? And what are the life cycle costs associated with rehabilitation? A research project funded by the CRC for Construction Innovation in Australia is aimed at addressing these issues. This paper presents a concept map for assisting decision makers to appropriately choose the best treatment for bridge rehabilitation affected by premature deterioration through exposure to aggressive environments in Australia. The decision analysis is referred to a whole of life cycle cost analysis by considering appropriate elements of bridge rehabilitation costs. In addition, the results of bridges inspections in Queensland are presented

Risk assessment in life-cycle costing for road asset management

Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

Life cycle inventory for Australian building materials

This paper discusses challenges to developers of a national Life Cycle Inventory (LCI) database on which to base assessment of building environmental impacts and a key to development of a fully integrated eco-design tool created for automated eco-efficiency assessment of commercial building design direct from 3D CAD. The scope of this database includes Australian and overseas processing burdens involved in acquiring, processing, transporting, fabricating, finishing and using metals, masonry, timber, glazing, ceramics, plastics, fittings, composites and coatings. Burdens are classified, calculated and reported for all flows of raw materials, fuels, energy and emissions to and from the air, soil and water associated with typical products and services in building construction, fitout and operation. The aggregated life cycle inventory data provides the capacity to generate environmental impact assessment reports based on accepted performance indicators. Practitioners can identify hot spots showing high environmental burdens of a proposed design and drill down to report on specific building components. They can compare assessments with case studies and operational estimates to assist in eco-efficient design of a building, fitout and operation.

Redefining life cycle for a building sustainability assessment framework

Understanding the differences between the temporal and physical aspects of the building life cycle is an essential ingredient in the development of Building Environmental Assessment (BEA) tools. This paper illustrates a theoretical Life Cycle Assessment (LCA) framework aligning temporal decision-making with that of material flows over building development phases. It was derived during development of a prototype commercial building design tool that was based on a 3-D CAD information and communications technology (ICT) platform and LCA software. The framework aligns stakeholder BEA needs and the decision-making process against characteristics of leading green building tools. The paper explores related integration of BEA tool development applications on such ICT platforms. Key framework modules are depicted and practical examples for BEA are provided for: • Definition of investment and service goals at project initiation; • Design integrated to avoid overlaps/confusion over the project life cycle; • Detailing the supply chain considering building life cycle impacts; • Delivery of quality metrics for occupancy post-construction/handover; • Deconstruction profiling at end of life to facilitate recovery.

Doped poly(vinylidene fluoride) as solid polymer electrolyte in nanocrystalline dye-sensitized solar cell

A new solid composite polymer electrolyte was reported by incorporating Azino-bis-(3-ethyl benzo thiazoline-6-sulphonate) ion [ABTS] as dopant in poly(vinylidene flouride) along with redox couple (1-/13-). Under certain conditions, the electrolyte composition forms brush like nano-rods while it is doped with Azino-bis-(3-ethly) benzo thiazoline-6-sulphonate) ion [ABTS], a pi-electron donor. The polymer electrolyte forms nanoscale interpenetrating network with the crystalline order of the polymer electrolyte that seems to be a desirable architecture for the active layer of the photoelectrochemical cell. With this new polymer electrolyte, dye-sensitized solar cell was fabricated using N3 dye absorbed over Ti02- nonoparticles (photoanode) and conducting carbon cement coated on the conducting press (FTO, photocathode). This polymer composite has been successfully used as a promising candidate as solid polymer electrolyte in nanocrystalline dye-sensitized solar cell.

Solid-state nanocrystalline dye-sensitized solar cell using 2-mercapto benzimidazole doped poly(ethylene oxide) as a new polymer electrolyte

New composite doped poly (ethylene oxide) polymer electrolyte was developed using 2-mercapto benzimidazole as plasticizer and iodide/triiodide as redox couple. The fabrication of the cell involves Poly(ethylene oxide)/ 2-mercapto benzimidazole / iodide/triiodide as polymer electrolyte in dye-sensitized solar cell fabricated with N3 dye and TiO2 nanoparticles as the photoanode and Platinum coated FTO (fluorine doped SnO2) as counter electrode. The current-volatage characteristics under simulated sunlight AM1.5 shows a short circuit current Isc of 8.7mA and open circuit photovoltage 508 mV. The conductivity measurements for the new polymer electrolyte and the photoelectrochemical measurments were carried out systematically. In 2-mercapto benzimidazole the electron rich sulphur and nitrogen atoms, act as pi-electron donors that form good interaction with iodine which plays a vital role in the performance of the fabricated dye-sensitized solar cells. The resonance effect increases the stability of the cell to a considerable extent. These results suggest that the new composite polymer electrolyte performs as a promising new doped polymer-electrolyte.

Extending life-cycle costing (LCC) analysis for sustainability considerations in road infrastructure projects

Sustainable development is about making societal investments. These investments should be in synchronization with the natural environment, trends of social development, as well as organisational and local economies over a long time span. Traditionally in the eyes of clients, project development will need to produce the required profit margins, with some degrees of consideration for other impacts. This is being changed as all citizens of our society are becoming more aware of concepts and challenges such as the climate change, greenhouse footprints, and social dimensions of sustainability, and will in turn demand answers to these issues in built facilities. A large number of R&D projects have focused on the technical advancement and environmental assessment of products and built facilities. It is equally important address the cost/benefit issue, as developers in the world would not want to loose money by investing in built assets. For infrastructure projects, due to its significant cost of development and lengthy delivery time, presenting the full money story of going green is of vital importance. Traditional views of life-cycle costing tend to focus on the pure economics of a construction project. Sustainability concepts are not broadly integrated with the current LCCA in the construction sector. To rectify this problem, this paper reports on the progress to date of developing and extending contemporary LCCA models in the evaluation of road infrastructure sustainability. The suggested new model development is based on sustainability indicators identified through previous research, and incorporating industry verified cost elements of sustainability measures. The on-going project aims to design and a working model for sustainability life-cycle costing analysis for this type of infrastructure projects.

Characterization of electron trapping in dye-sensitized solar cells by near-IR transmittance measurements

In situ near-IR transmittance measurements have been used to characterize the density of trapped electrons in dye-sensitized solar cells (DSCs). Measurements have been made under a range experimental conditions including during open circuit photovoltage decay and during recording of the IV characteristic. The optical cross section of electrons at 940 nm was determined by relating the IR absorbance to the density of trapped electrons measured by charge extraction. The value, σn = 5.4 × 10-18 cm2, was used to compare the trapped electron densities in illuminated DSCs under open and short circuit conditions in order to quantify the difference in the quasi Fermi level, nEF. It was found that nEF for the cells studied was 250 meV over wide range of illuminat on intensities. IR transmittance measurements have also been used to quantify shifts in conduction band energy associated with dye adsorption.

A comparison of different methods to determine diffusion length in dye-sensitized solar cells

A new steady state method for determination of the electron diffusion length in dye-sensitized solar cells (DSCs) is described and illustrated with data obtained using cells containing three different types of electrolyte. The method is based on using near-IR absorbance methods to establish pairs of illumination intensity for which the total number of trapped electrons is the same at open circuit (where all electrons are lost by interfacial electron transfer) as at short circuit (where the majority of electrons are collected at the contact). Electron diffusion length values obtained by this method are compared with values derived by intensity modulated methods and by impedance measurements under illumination. The results indicate that the values of electron diffusion length derived from the steady state measurements are consistently lower than the values obtained by the non steady-state methods. For all three electrolytes used in the study, the electron diffusion length was sufficiently high to guarantee electron collection efficiencies greater than 90%. Measurement of the trap distributions by near-IR absorption confirmed earlier observations of much higher electron trap densities for electrolytes containing Li+ ions. It is suggested that the electron trap distributions may not be intrinsic properties of the TiO2 nanoparticles, but may be associated with electron-ion interactions.

Novel ruthenium bipyridyl dyes with s-donor ligands and their application in dye-sensitized solar cells

Two series of novel ruthenium bipyridyl dyes incorporating sulfur-donor bidentate ligands with general formula \[Ru(R-bpy)2C2N2S2] and \[Ru(R-bpy)2(S2COEt)]\[NO3] (where R =H, CO2Et, CO2H; C2N2S2 = cyanodithioimidocarbonate and S2COEt = ethyl xanthogenate) have been synthesized and characterized spectroscopically, electrochemically and computationally. The acid derivatives in both series (C2N2S2 3 and S2COEt 6) were used as a photosensitizer in a dye-sensitized solar cell (DSSC) and the incident photo-to-current conversion efficiency (IPCE), overall efficiency (_) and kinetics of the dye/TiO2 system were investigated. It was found that 6 gave a higher efficiency cell than 3 despite the latter dye’s more favorable electronic properties, such as greater absorption range, higher molar extinction coefficient and large degree of delocalization of the HOMO. The transient absorption spectroscopy studies revealed that the recombination kinetics of 3 were unexpectedly fast, which was attributed to the terminal CN on the ligand binding to the TiO2, as evidenced by an absorption study of R =H and CO2Et dyes sensitized on TiO2, and hence leading to a lower efficiency DSSC.