Rethinking construction: the Generic Design and Construction Process Protocol

The complexity of construction projects and the fragmentation of the construction industry undertaking those projects has effectively resulted in linear, uncoordinated and highly variable project processes in the UK construction sector. Research undertaken at the University of Salford resulted in the development of an improved project process, the Process Protocol, which considers the whole lifecycle of a construction project whilst integrating its participants under a common framework. The Process Protocol identifies the various phases of a construction project with particular emphasis on what is described in the manufacturing industry as the ‘fuzzy front end’. The participants in the process are described in terms of the activities that need to be undertaken in order to achieve a successful project and process execution. In addition, the decision-making mechanisms, from a client perspective, are illustrated and the foundations for a learning organization/industry are facilitated within a consistent Process Protocol.

Nonlinear model structure design and construction using orthogonal least squares and D-optimality design

A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

Infection Control in design and construction work

Objective: To clarify how infection control requirements are represented, communicated, and understood in work interactions through the medical facility construction project life cycle. To assist project participants with effective infection control management by highlighting the nature of such requirements and presenting recommendations to aid practice. Background: A 4-year study regarding client requirement representation and use on National Health Service construction projects in the United Kingdom provided empirical evidence of infection control requirement communication and understanding through design and construction work interactions. Methods: An analysis of construction project resources (e.g., infection control regulations and room data sheets) was combined with semi-structured interviews with hospital client employees and design and construction professionals to provide valuable insights into the management of infection control issues. Results: Infection control requirements are representationally indistinct but also omnipresent through all phases of the construction project life cycle: Failure to recognize their nature, relevance, and significance can result in delays, stoppages, and redesign work. Construction project resources (e.g., regulatory guidance and room data sheets) can mask or obscure the meaning of infection control issues. Conclusions: A preemptive identification of issues combined with knowledge sharing activities among project stakeholders can enable infection control requirements to be properly understood and addressed. Such initiatives should also reference existing infection control regulatory guidance and advice.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

Safe construction through design: perspectives from the site team

How does the work of designers impact on the safety of operatives at the construction site? Safety research and policy emphasize the importance of designing for safe construction, yet the interface between design and construction is poorly understood: accidents have multiple causes making it hard to establish causal links between design choices and safety outcomes. An in-depth case study of a major station project examines how professionals on the construction site perceive and manage the safety challenges of a building design. Analyses reveal understandings that, on the project studied, design has an impact on safety because of: (1) the timing of design work, where the volume of late design changes increased the difficulty of planning safe procedures, e.g. for working at height, lifting heavy items, refurbishing and demolishing old buildings; and (2) inputs from design stakeholders with insufficient practical knowledge of construction and operation required unplanned work-arounds, e.g. to coordinate different sub-systems, provide maintenance access, and manage loads during construction. These findings suggest that safety suffers where projects are under-designed, and that alongside regulation, there is a need for robust management attention to the contractual structures, incentives, processes and tools that enable clients and designers to understand material practices of construction and operation.

Automated algorithms for multilayer thin film filter design using metamaterials

Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).

Mid-infrared filters for astronomical and remote sensing instrumentation

As improvements to the optical design of spectrometer and radiometer instruments evolve with advances in detector sensitivity, use of focal plane detector arrays and innovations in adaptive optics for large high altitude telescopes, interest in mid-infrared astronomy and remote sensing applications have been areas of progressive research in recent years. This research has promoted a number of developments in infrared coating performance, particularly by placing increased demands on the spectral imaging requirements of filters to precisely isolate radiation between discrete wavebands and improve photometric accuracy. The spectral design and construction of multilayer filters to accommodate these developments has subsequently been an area of challenging thin-film research, to achieve high spectral positioning accuracy, environmental durability and aging stability at cryogenic temperatures, whilst maximizing the far-infrared performance. In this paper we examine the design and fabrication of interference filters in instruments that utilize the mid-infrared N-band (6-15 µm) and Q-band (16-28 µm) atmospheric windows, together with a rationale for the selection of materials, deposition process, spectral measurements and assessment of environmental durability performance.

Design and theoretical study of nickel catalysts for syndiotactic polyolefins

A nickel catalyst was modeled with ligand L-2, [ NH = CH-CH = CH-O](-), which should have potential use as a syndiotactic polyolefin catalyst, and the reaction mechanism was studied by theoretical calculations using the density functional method at the B3LYP/ LANL2MB level. The mechanism involves the formation of the intermediate [(NiLMe)-Me-2](+), in which the metal occuples a T-shaped geometry. - This intermediate has two possible structures with the methyl group trans either to the oxygen or to the nitrogen atom of L-2. The results show that both structures can lead to the desired product via similar reaction paths, A and B. Thus, the polymerization could be considered as taking place either with the alkyl group occupying the position trans to the Ni-O or trans to the Ni-N bond in the catalyst. The polymerization process thus favors the catalysis of syndiotactic polyolefins. The syndiotactic synthesis effects could also be enhanced by variations in the ligand substituents. From energy considerations, we can conclude that it is more favorable for the methyl group to occupy the trans-O position to form a complex than to occupy the trans-N position. From bond length considerations, it is also more favoured for ethene to occupy the trans-O position than to occupy the trans-N position.

Learning across business sectors: facets of innovation in aerospace and construction

Innovation is notoriously difficult to define and is invariably intertwined with issues of knowledge creation, continuous improvement and organisational change. An extensive literature classifies numerous types of innovation and militates against any simplistic attempt at definition. It is widely accepted that innovation is at least partly dependent upon the surrounding environment. Industry recipes and institutionally embedded practices shape the environment within which innovation occurs. Recent research directions have addressed the diffusion of innovation and its dependence upon social and institutional structures. In this respect, it is highly pertinent to compare the way that innovation is interpreted and enacted in different industrial sectors. The comparison between UK aerospace and construction is especially revealing because the two sectors are so different and therefore constitute radically different climates for innovation. Empirical research is reported based on semi-structured interviews with practitioners from both sectors. Interpretations of innovation are found to differ dramatically between aerospace and construction. Within the context of an ongoing struggle to define innovation, both industries are striving to become more innovative. The aerospace sector is found to emphasise technical innovation whereas the construction sector emphasises process innovation. An overriding cultural bias in Western economies towards technological innovation results in the common perception that aerospace is much more innovative than construction. The experienced realities of practitioners in the two sectors are much more complex.