336 resultados para Optimal solutions


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A new approach of integrated design and delivery solutions (IDDS) aims to radically improve the performance of the construction industries. IDDS builds upon recent trends in the construction industries that have seen the widespread adoption of technologies such as building information modelling (BIM) and innovative processes such as integrated project delivery. However, these innovations are seen to develop in isolation, with little consideration of the overarching interactions between people, process and technology. The IDDS approach is holistic in that it recognizes that it is only through a combination of initiatives such as skill development, process re-engineering, responsive information technology, enhanced interoperability and integrating knowledge management, among others, that radical change can be achieved. To implement IDDS requires step changes in many project aspects, and this gap between current performance and that required for IDDS is highlighted. The research required to bridge the gaps is identified in four major aspects of collaborative processes, workforce skills, integrated information and knowledge management.

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CIB is developing a priority theme, now termed Improving Construction and Use through Integrated Design & Delivery Solutions (IDDS). The IDDS working group for this theme adopted the following definition: Integrated Design and Delivery Solutions use collaborative work processes and enhanced skills, with integrated data, information, and knowledge management to minimize structural and process inefficiencies and to enhance the value delivered during design, build, and operation, and across projects. The design, construction, and commissioning sectors have been repeatedly analysed as inefficient and may or may not be quite as bad as portrayed; however, there is unquestionably significant scope for IDDS to improve the delivery of value to clients, stakeholders (including occupants), and society in general, simultaneously driving down cost and time to deliver operational constructed facilities. Although various initiatives developed from computer‐aided design and manufacturing technologies, lean construction, modularization, prefabrication and integrated project delivery are currently being adopted by some sectors and specialisations in construction; IDDS provides the vision for a more holistic future transformation. Successful use of IDDS requires improvements in work processes, technology, and people’s capabilities to span the entire construction lifecycle from conception through design, construction, commissioning, operation, refurbishment/ retrofit and recycling, and considering the building’s interaction with its environment. This vision extends beyond new buildings to encompass modifications and upgrades, particularly those aimed at improved local and area sustainability goals. IDDS will facilitate greater flexibility of design options, work packaging strategies and collaboration with suppliers and trades, which will be essential to meet evolving sustainability targets. As knowledge capture and reuse become prevalent, IDDS best practice should become the norm, rather than the exception.

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Changes in the construction sector are creating opportunities in research to maximise the benefits of those changes and to continue the exciting developments in improved people skills, new processes and developing technologies. There are many research centres around the world investigating aspects of the current changes to drive their particular expertise forward. However, the CIB Integrated Design and Delivery Solutions (IDDS) priority research theme takes a higher-level view of the changes and then focuses down on a prioritised set of research targets. These targets have been investigated, re-focussed and validated over a period of four years through many workshops, conferences and meetings by a wide ranging group of representatives from approximately 90 industry and research organisations. This roadmap prioritises and details the research to be performed, why and by whom. In particular, some 25 CIB Working Commissions and Task Groups are explained as having potential roles in the delivery of this research theme. We are extremely privileged to have been urged on by such distinguished construction professionals in their forewords and the case for research. The outcomes of such research, once put into practice should be significantly shortened timespans from conception of need to occupation of new or revised structures. As time is money, the owners will get their investments into productive use sooner, which means a shorter payback time. In addition, there will inevitably be a reduction in construction costs as productivity increases. The improvements in reliable delivery and improved quality currently being seen in relatively simplistic use of Building information Modelling (BIM) (compared to full IDDS) will inevitably continue its on-going trajectory of improvement. We should also consider the wider economic contribution to society that will stem from such improvements and, finally, and by no means unimportantly, the reliable modelling and delivery of sustainability at both the building and estate/ area scale will significantly improve carbon footprints and other sustainable outcomes. Whilst there are huge opportunities for early adopters, the primary risk will be the expansion of the gap between those working in this way and those who are not so advanced or who even refuse to progress1. However, a similar issue arises between industry, clients, educators and trainers; the latter have particular challenges, having existed for many years in a sector that has had relatively few technological changes. However, the opportunities to address the significant and widely varying wastes within the structure of the construction sector and within and across projects are huge and timely. Whilst this Roadmap is specifically targeted at the Standing Commissions and Task Groups of the CIB, it is hoped that there are elements for research and applied research across academia and industry.

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Environmental engineers are increasingly being required to have knowledge about sustainability in their professional careers. Accreditation mechanisms for including sustainability in degree program requirements exist and are gradually being implemented by Engineers Australia. However, true integration of sustainability material into higher and vocational education curricula is still low, particularly outside the environmental engineering degree programs. In addition to environmental engineering, it is crucial for engineering across the specialisations, to be exposed to sustainability concepts and theories. This paper will demonstrate how sustainability as a ‘critical literacy’ can be designed for teaching within mainstream engineering education, using a current Australian project as a case study. The project demonstrates that sustainability education for all engineers is not only possible, but that there is international interest in collaborating in such an educational initiative. A pilot trial of the Introductory Module was undertaken in Semester 1 2004 and Version 2 trials are now proceeding with a number of universities and organisations nationally and internationally. Further modules are currently being developed in collaboration with Engineers Australia and UNESCO. The program is a finalist in the 2005 Banksia Awards (Category 11, Environmental Leadership Education and Training).

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Similarity solutions are carried out for flow of power law non-Newtonian fluid film on unsteady stretching surface subjected to constant heat flux. Free convection heat transfer induces thermal boundary layer within a semi-infinite layer of Boussinesq fluid. The nonlinear coupled partial differential equations (PDE) governing the flow and the boundary conditions are converted to a system of ordinary differential equations (ODE) using two-parameter groups. This technique reduces the number of independent variables by two, and finally the obtained ordinary differential equations are solved numerically for the temperature and velocity using the shooting method. The thermal and velocity boundary layers are studied by the means of Prandtl number and non-Newtonian power index plotted in curves.

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Physical activity (PA) parenting research has proliferated over the past decade, with findings verifying the influential role that parents play in children's emerging PA behaviors. This knowledge, however, has not translated into effective family-based PA interventions. During a preconference workshop to the 2012 International Society for Behavioral Nutrition and Physical Activity annual meeting, a PA parenting workgroup met to: (1) Discuss challenges in PA parenting research that may limit its translation, (2) identify explanations or reasons for such challenges, and; (3) recommend strategies for future research. Challenges discussed by the workgroup included a proliferation of disconnected and inconsistently measured constructs, a limited understanding of the dimensions of PA parenting, and a narrow conceptualization of hypothesized moderators of the relationship between PA parenting and child PA. Potential reasons for such challenges emphasized by the group included a disinclination to employ theory when developing measures and examining predictors and outcomes of PA parenting as well as a lack of agreed-upon measurement standards. Suggested solutions focused on the need to link PA parenting research with general parenting research, define and adopt rigorous standards of measurement, and identify new methods to assess PA parenting. As an initial step toward implementing these recommendations, the workgroup developed a conceptual model that: (1) Integrates parenting dimensions from the general parenting literature into the conceptualization of PA parenting, (2) draws on behavioral and developmental theory, and; (3) emphasizes areas which have been neglected to date including precursors to PA parenting and effect modifiers.

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In 2009, BJSM's first editorial argued that ‘Physical inactivity is the greatest public health problem of the 21st century’.1 The data supporting that claim have not yet been challenged. Now, 5 years after BJSM published its first dedicated ‘Physical Activity is Medicine’ theme issue (http://bjsm.bmj.com/content/43/1.toc) we are pleased to highlight 23 new contributions from six countries. This issue contains an analysis of the cost of physical inactivity from the US Centre for Diseases Control.2 We also report the cost-effectiveness of one particular physical activity intervention for adults.3

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The hydrolysis of triasulfuron, metsulfuron-methyl and chlorsulfuron in aqueous buffer solutions and in soil suspensions at pH values ranging from 5.2 to 11.2 was investigated. Hydrolysis of all three compounds in both aqueous buffer and soil suspensions was highly pH-sensitive. The rate of hydrolysis was much faster in the acidic pH range (5.2-6.2) than under neutral and moderately alkaline conditions (8.2-9.4), but it increased rapidly as the pH exceeded 10.2. All three compounds degraded faster at pH 5.2 than at pH 11.2. Hydrolysis rates of all three compounds could be described well with pseudo-first-order kinetics. There were no significant differences (P =0.05) in the rate constants (k, day-1) of the three compounds in soil suspensions from those in buffer solutions within the pH ranges studied. A functional relationship based on the propensity of nonionic and anionic species of the herbicides to hydrolyse was used to describe the dependence of the 'rate constant' on pH. The hydrolysis involving attack by neutral water was at least 100-fold faster when the sulfonylurea herbicides were undissociated (acidic conditions) than when they were present as the anion at near neutral pH. In aqueous buffer solution at pH > 11, a prominent degradation pathway involved O-demethylation of metsulfuron-methyl to yield a highly polar degradate, and hydrolytic opening of the triazine ring. It is concluded that these herbicides are not likely to degrade substantially through hydrolysis in most agricultural (C) 2000 Society of Chemical Industry.

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Methyl orange (MO) is a kind of anionic dye and widely used in industry. In this study, tricalcium aluminate hydrates (Ca-Al-LDHs) are used as an adsorbent to remove methyl orange (MO) from aqueous solutions. The resulting products were studied by X-ray diffraction (XRD), infrared spectroscopy (MIR), thermal analysis (TG-DTA) and scanning electron microscope (SEM). The XRD results indicated that the MO molecules were successfully intercalated into the tricalcium aluminate hydrates, with the basal spacing of Ca-Al-LDH expanding to 2.48 nm. The MIR spectrum for CaAl-MO-LDH shows obvious bands assigned to the N@N, N@H stretching vibrations and S@O, SO_ 3 group respectively, which are considered as marks to assess MO_ ion intercalation into the interlayers of LDH. The overall morphology of CaAl-MOLDH displayed a ‘‘honey-comb’’ like structure, with the adjacent layers expanded.

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This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

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This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

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In this article we obtain closed-form solutions for the combined inflation and axial shear of an elastic tube in respect of the compressible Isotropic elastic material introduced by Levinson and Burgess. Several other boundary-value problems are also examined, including the bending of a rectangular block and straightening of a cylindrical sector, both coupled with stretching and shearing, and an axially varying twist deformation. Some of the solutions appear in closed form, others are expressible in terms of elliptic functions.

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Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

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The efficiency of the nitrogen (N) application rates 0, 120, 180 and 240 kg N ha−1 in combination with low or medium water levels in the cultivation of winter wheat (Triticum aestivum L.) cv. Kupava was studied for the 2005–2006 and 2006–2007 growing seasons in the Khorezm region of Uzbekistan. The results show an impact of the initial soil Nmin (NO3-N + NH4-N) levels measured at wheat seeding on the N fertilizer rates applied. When the Nmin content in the 0–50 cm soil layer was lower than 10 mg kg−1 during wheat seeding in 2005, the N rate of 180 kg ha−1 was found to be the most effective for achieving high grain yields of high quality. With a higher Nmin content of about 30 mg kg−1 as was the case in the 2006 season, 120 kg N ha−1 was determined as being the technical and economical optimum. The temporal course of N2O emissions of winter wheat cultivation for the two water-level studies shows that emissions were strongly influenced by irrigation and N-fertilization. Extremely high emissions were measured immediately after fertilizer application events that were combined with irrigation events. Given the high impact of N-fertilizer and irrigation-water management on N2O emissions, it can be concluded that present N-management practices should be modified to mitigate emissions of N2O and to achieve higher fertilizer use efficiency.