• Energy Research

Abstract The quantitative tools and methods that have been developed to identify and cultivate industrial symbiotic exchanges in existing industrial parks to minimize overall energy and material consumption are reviewed. The issues relevant to adapting an existing park differs from those associated with constructing a new park using eco-industrial principles. Published literature was surveyed for methodologies which identify and establish viable inter-company exchanges for water, heat, power and materials. Studies which address issues associated with infrastructure alterations are specifically highlighted, as well as methods to quantify and manipulate any potential financial and/or ecological benefits gained by adopting proposed eco-industrial measures. Additional topics, such as network analysis, company motivation, confidentiality issues and introduction of new industries or facilities are included. This review surveys current quantitative methodologies that can be applied to the process of adapting established industrial park networks into eco-industrial park systems and case studies which are pertinent to this type of adaptation.

The wall effect on the settling of cylindrical particles in the inertial regime is revisited. This study covers particle Reynolds number from 600 to 16 100 and particle-length-to-diameter ratios (l/d) from 4 to 21. The wall factor (Ut/Ut,∞) is found to decrease initially as the particle-to-column diameter ratio (d/D) increases. When the wall effect becomes significant, Ut/Ut,∞ starts to increase with an increase in d/D due to a change of the particle orientation during settling. After Ut/Ut,∞ reaches a maximum, it decreases to 0 when d/D increases to 1. A semiempirical model is developed to predict the wall effect of settling of cylindrical particles over the whole range of d/D. The model shows good prediction to the experimental results and matches the wall factor models developed for spherical particles when l/d approaches 1.

Abstract There are a number of shape factors available in the literature to describe the deviation of non-spherical particles to spheres. Dynamic shape factor ( χ ) is the most suitable parameter for flow applications as it takes into account the dynamic properties of the non-spherical particles. In this study, dynamic shape factors for spheres, cubes, cuboids and cylinders settling in the transition regime (2 t χ for spheres and cubes are found to be constant with particle size when conventional wall effect models are followed. χ for cuboids and cylinders, on the other hand, are found to be a function of the particle characteristic length-to-column diameter ratio ( l / D ) and the particle aspect ratio ( l / d ). An empirical correlation is developed to estimate χ for both cuboids and cylinders settling in the intermediate regime. The correlation can provide a low average error of 3% for all the cuboids and cylinders used in this study.

Cultivation of microalgae Chlorella sp. was performed in draft-tube photobioreactors. Effect of light intensity on the microalgae growth performance was conducted under a light intensity range of 82-590 μmol/m(2)s. A lumostatic strategy was proposed based on the light distribution profiles obtained by image analysis and specific chlorophyll a content. The proposed lumostatic strategy allowed a maximum biomass dry weight of 5.78 g/L and a productivity of 1.29 g/Ld, which were 25.7% and 74.3% higher than that achieved by the optimal constant light intensity, respectively. A comparison with other lumostatic strategies reported in the literature indicated that the proposed lumostatic strategy in the current study can be a promising approach in improving the growth of microalgae.

© 2016 Elsevier Ltd. The concept of eco-industrial park (EIP) has recently become the subject of a great deal of attention from industry and academic research groups. This paper proposes a series of systematic approaches for multi-level modelling and optimisation in EIPs. The novelties of this work include, (1) building a four-level modelling framework (from unit level to process level, plant level and industrial network level) for EIP research, (2) applying advanced mathematical modelling methods to describe each level operation, (3) developing efficient methodologies for solving optimisation problems at different EIP levels, (4) considering symbiotic relations amongst the three networks (material, water and energy networks) at the top EIP level with the boundary conditions of economic, social and legal requirements. For methodology demonstration, two cases at process level and industrial network level respectively are tested and solved with the developed modelling and optimisation strategies. Finally, the challenges and applications in future EIP research are also discussed, including data collection, the extension of the current networks to EIPs, and the feasibility of the proposed methodologies for complex EIP problems. The extended EIPs include the combination of material exchanges, energy systems and waste-water treatment networks. The aspects considered for future industrial ecology are carbon emission, by-product reuse, water consumption, and energy consumption. The main object of this paper is to explain the detailed model construction process and the development of optimisation approaches for a complex EIP system. In future work, this system is expected to share services, utility, and product resources amongst industrial plants to add value, reduce costs, improve environment, and consequently achieve sustainable development in a symbiosis community.

AbstractThis paper presents new insights into the implementation of Industry 4.0 technologies (novel mathematical and computer-based methods) for designing and optimising the eco-industrial park (EIP) of Jurong Island in Singapore. The concept of Industry 4.0 translation to an EIP is introduced, which delivers an expert system allowing users to monitor, control, and optimise the social, economic and environmental repercussions of the industrial activities on Jurong Island. This expert system is a cyber-infrastructure making use of the latest advances in high performance computing (HPC), advanced mathematical modelling, and semantic web technologies. The proposed work addresses end-user driven demands by harnessing HPC resources and advanced data analytics to enable intelligent design, operation, and management of all entities on Jurong Island. The outcome of the work can serve stakeholders from both the private and public sectors.

AbstractCarbon dioxide emission is an important parameter for indication of environmental impact of an industrial process. For a process that has known product capacity or revenue information, an Economic Input-Output Life Cycle Assessment (EIO-LCA) model can be applied to estimate the carbon dioxide emission. Due to the difficulty in obtaining such information for many industries, a simple linear correlation was developed using data obtained from applying EIO-LCA model on certain known processes in conjunction with the land area information obtained by ArcGIS, a geographic information software program. Jurong Island, an industrial park housing more than 100 companies in Singapore is chosen as the case study site. Carbon dioxide emission from different industrial sectors in Jurong Island were also compared.