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Journal articles on the topic 'Environmental engineering modelling'

To see the other types of publications on this topic, follow the link: Environmental engineering modelling.

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Janowski, Artur, Jakub Szulwic, and Paweł Tysiąc. "Spatial Modelling in Environmental Analysis and Civil Engineering." Applied Sciences 11, no. 9 (April 27, 2021): 3945. http://dx.doi.org/10.3390/app11093945.

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2

Wang, Julian Z. "Statistical modelling for extreme observations in environmental engineering." Environmetrics 9, no. 1 (January 1998): 31–36. http://dx.doi.org/10.1002/(sici)1099-095x(199801/02)9:1<31::aid-env283>3.0.co;2-d.

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3

Hoti, Suhejla, Michael McAleer, and Laurent L. Pauwels. "Modelling environmental risk." Environmental Modelling & Software 20, no. 10 (October 2005): 1289–98. http://dx.doi.org/10.1016/j.envsoft.2004.08.010.

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4

Schulin, Rainer. "Advances in Environmental Modelling (Developments in Environmental Modelling, Vol. 13)." Journal of Environmental Quality 19, no. 3 (July 1990): 631–32. http://dx.doi.org/10.2134/jeq1990.00472425001900030049x.

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5

Krzywanski, Jaroslaw. "Advanced AI Applications in Energy and Environmental Engineering Systems." Energies 15, no. 15 (August 3, 2022): 5621. http://dx.doi.org/10.3390/en15155621.

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6

Jolma, A., A. Altartouri, and I. Ferencik. "GIS, Environmental Modeling and Engineering." Environmental Modelling & Software 25, no. 12 (December 2010): 1915–16. http://dx.doi.org/10.1016/j.envsoft.2010.06.007.

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7

Hobbs, S. E. "Modelling change in environmental systems." Applied Ocean Research 17, no. 5 (October 1995): 323. http://dx.doi.org/10.1016/0141-1187(95)90002-0.

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8

Li, Qiuying, and Ruize Sun. "Environmental Engineering with Software Environment Modelling Based on Threat Model." IOP Conference Series: Earth and Environmental Science 706, no. 1 (March 1, 2021): 012020. http://dx.doi.org/10.1088/1755-1315/706/1/012020.

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9

Matei, Ion Viorel, and Laura Ungureanu. "SURVEY ON INTEGRATED MODELLING APPLIED IN ENVIRONMENTAL ENGINEERING AND MANAGEMENT." Environmental Engineering and Management Journal 13, no. 4 (2014): 1027–38. http://dx.doi.org/10.30638/eemj.2014.107.

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10

Souto González, J. A., P. M. Bello Bugallo, and J. J. Casares Long. "Evaluation of air pollution modelling tools as environmental engineering courseware." Water Science and Technology 49, no. 8 (April 1, 2004): 57–64. http://dx.doi.org/10.2166/wst.2004.0487.

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The study of phenomena related to the dispersion of pollutants usually takes advantage of the use of mathematical models based on the description of the different processes involved. This educational approach is especially important in air pollution dispersion, when the processes follow a non-linear behaviour so it is difficult to understand the relationships between inputs and outputs, and in a 3D context where it becomes hard to analyze alphanumeric results. In this work, three different software tools, as computer solvers for typical air pollution dispersion phenomena, are presented. Each software tool developed to be implemented on PCs, follows approaches that represent three generations of programming languages (Fortran77, VisualBasic and Java), applied over three different environments: MS-DOS, MS-Windows and the world wide web. The software tools were tested by students of environmental engineering (undergraduate) and chemical engineering (postgraduate), in order to evaluate the ability of these software tools to improve both theoretical and practical knowledge of the air pollution dispersion problem, and the impact of the different environment in the learning process in terms of content, ease of use and visualization of results.

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11

Carmo, José Simão Antunes do. "Numerical modelling and its physical modelling support in Civil Engineering." Research, Society and Development 9, no. 10 (October 5, 2020): e5019108409. http://dx.doi.org/10.33448/rsd-v9i10.8409.

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Currently, there is a progressive divestment of some institutions with strong traditions and skills in physical modelling and their consequent impoverishment, to the detriment of numerical modelling. For many reasons, the economic imperatives and the exponential growth of computational means and numerical methods should certainly not be excluded. In this work, the author aimed to highlight the new requirements of the recent sophisticated developments in physical modelling, precisely due to the new needs imposed on them by mathematical and numerical modelling and the growing risks in civil construction works. In this context, reflections are reported, justified by scientific and real-world examples, on the need for maintenance and reinforcement of investments in physical modelling, both to support the scientific community and to design buildings of significant economic, social and environmental impact.

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12

Hamilton, E. I. "Advances in environmental modelling." Science of The Total Environment 92 (March 1990): 287–88. http://dx.doi.org/10.1016/0048-9697(90)90344-t.

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13

Starodub, Yu, A. Havrys, and O. Kozionova. "MODELLING OF THE EFFECTS OF THE ENVIRONMENTAL-GEOPHYSICAL STATE OF SOILS ON ENGINEERING BUILDING OBJECTS." Visnyk of Taras Shevchenko National University of Kyiv. Geology, no. 3 (90) (2020): 97–103. http://dx.doi.org/10.17721/1728-2713.90.14.

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The article deals with the method of the reaction modelling of soil strata under engineering objects to ecological and geophysical state in the problems of studying the negative influence of loads on a stress-strain state of soil under engineering objects. The problem of stability study is considered and the behaviour of soil in a vicinity of bridge-engineering structures is investigated. To solve the problems of emergency protection, a method of modelling the reaction of the soil layer under the load on the engineering objects due to tectonic influences to study the stress-strain state of the ground crust in a vicinity of engineering objectsis used. An algorithm of the finite element method in the problem of studying the stress-strain state of soil base under engineering objects has been developed. The physical and mathematical formulation of the problem is carried out. The modelling problem is solved by test cases. Models of continuous environment of functioning engineering structures for which stress-strain characteristics of the soil massif modelled are developed. The theoretical definition and modelling of critical values of the stress-strain state of the soil mass under the influence of loads are carried out. Modelling allows to predict the nature of the influence of mechanical processes on the ecological and geophysical state of the environment and to study the stability of engineering structures. Stress-deformation processes of the rock massif are investigated, as a result of which emergencies of natural and man-made characters can arise.

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14

Stive, M. J. F. "Computer modelling in ocean engineering 91." Coastal Engineering 20, no. 1-2 (July 1993): 183. http://dx.doi.org/10.1016/0378-3839(93)90061-c.

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15

Rasinmäki, Jussi. "Modelling spatio-temporal environmental data." Environmental Modelling & Software 18, no. 10 (December 2003): 877–86. http://dx.doi.org/10.1016/s1364-8152(03)00106-3.

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16

McAleer, Michael. "Modelling economic and environmental systems." Environmental Modelling & Software 20, no. 11 (November 2005): 1365–67. http://dx.doi.org/10.1016/j.envsoft.2004.09.009.

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17

LUX, T., and W. MATTHEWS. "Advanced technology for environmental modelling." Environmental Modelling & Software 22, no. 3 (March 2007): 279–80. http://dx.doi.org/10.1016/j.envsoft.2005.07.027.

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18

Landström, Catharina, Sarah J. Whatmore, and Stuart N. Lane. "Virtual Engineering." Science & Technology Studies 24, no. 2 (January 1, 2011): 3–22. http://dx.doi.org/10.23987/sts.55261.

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This paper discusses computer simulation modelling in the context of environmental risk management. Approaching computer simulation as practice, performed in networks of heterogeneous elements, we examine the modelling undertaken by engineering consultants commissioned to provide knowledge about local flood risk to the Environment Agency of England and Wales (EA), the public body responsible for flood risk management. We propose that this simulation modelling is best understood as a form of engineering, work geared to solving the problems of clients. It is also a ‘virtual’ activity, articulating risks and possibilities in the digital space of the computer. We find that this ‘virtual engineering’ is shaped by the demands and protocols of the EA, first, by the establishment of long-term contractual agreements for delivering knowledge and second, by an EA requirement to use particular software packages. Fashioned between long-term contracts and black-boxed software virtual engineering becomes stabilised as ‘the’ way in which knowledge about flood risk in actual localities is generated and, consequently, becomes ‘hard-wired’ into flood risk management in England.

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19

Tretyakov, Nicodemus. "Introduction of Modelling using MATLAB and SIMULINK for Environmental Engineering Students." Pollution Engineering 49, no. 1 (October 26, 2020): 01–02. http://dx.doi.org/10.17762/pe.v49i1.26.

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A training venture is being created with the point of empowering ecological building understudies to rapidly build up their individual recreation representation of water pedestal eco-frameworks without the need to compose PC programs. The vehicle for this is the business programming MATLAB and SIMULINK. At first, the technique is being applied to display disintegrated O2 and biochemical oxygen request in a water body getting a waste release. Reproductions can incorporate photosynthesis and breath. Understudies are provided with field information and their errand is to recognize the predominant cycles, arrange a proper reproduction, pick qualities for the active constants and complete sculpt runs.

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20

YOUNG, P. "Data-based mechanistic modelling of environmental, ecological, economic and engineering systems." Environmental Modelling and Software 13, no. 2 (April 1998): 105–22. http://dx.doi.org/10.1016/s1364-8152(98)00011-5.

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21

Hutson, John L. "Modelling in Ecotoxicology (Developments in Environmental Modelling 16)." Journal of Environmental Quality 20, no. 4 (October 1991): 879–80. http://dx.doi.org/10.2134/jeq1991.00472425002000040035x.

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22

Hamilton, E. I. "Receptor modelling in environmental chemistry." Science of The Total Environment 57 (December 1986): 269–70. http://dx.doi.org/10.1016/0048-9697(86)90036-7.

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23

Carvalho, I. S., P. Antão, and C. Guedes Soares. "Modelling of environmental impacts of ship dismantling." Ships and Offshore Structures 6, no. 1-2 (February 11, 2011): 161–73. http://dx.doi.org/10.1080/17445301003776233.

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24

O'Brien, R. S., P. McDonald, C. Yu, V. Koukouliou, L. W. Setlow, J. Horyna, D. P. Sanchéz, et al. "Environmental modelling of NORM." Radioprotection 44, no. 5 (2009): 23–28. http://dx.doi.org/10.1051/radiopro/20095011.

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25

Susanto, Ferry, Paulo de Souza, and Jing He. "Spatiotemporal Interpolation for Environmental Modelling." Sensors 16, no. 8 (August 6, 2016): 1245. http://dx.doi.org/10.3390/s16081245.

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26

Al Dianty, Marelianda, Reza Fathurahman, Frederik Joseph Putuhena, Rizka Arbaningrum, and Zuchra Helwani. "Integrated Engineering, Environmental, and Economical Modelling of Micro Hydro Plant (MHP) Production." IOP Conference Series: Earth and Environmental Science 945, no. 1 (December 1, 2021): 012033. http://dx.doi.org/10.1088/1755-1315/945/1/012033.

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Abstract The use of renewable energy has commonly concentrated on energy production through wind engines and solar panels. Nowadays, the micro-hydropower (MHP) plant has a great challenge as an important contributor to energy systems. Indonesia has the potential natural resources to develop that power plant, in the form of the river where is abundant throughout all provinces. The research aims to address solving issues regarding deficit energy by renewable energy production. The environmental and hydrological approaches were used to determine the location to obtain the optimal and proper utilization of MHP. The analysing from all modelling creates an economical assessment of MHP energy production. The result recommends MHP with the capacity of 2 x 4.0 MW and a total discharge of 14.30 m3/second whereas design flood discharge is 813.47 m3/second (Q100 year). The implementation of MHP is an effort to achieve independent energy in the region.

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27

Moore, R. V., and A. G. Hughes. "Integrated environmental modelling: achieving the vision." Geological Society, London, Special Publications 408, no. 1 (May 23, 2016): 17–34. http://dx.doi.org/10.1144/sp408.12.

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28

Chen, Qiuwen, Yenory Morales-Chaves, Hong Li, and Arthur E. Mynett. "Hydroinformatics techniques in eco-environmental modelling and management." Journal of Hydroinformatics 8, no. 4 (December 1, 2006): 297–316. http://dx.doi.org/10.2166/hydro.2006.011.

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The high complexity of aquatic ecosystems and the multiple processes involved, make the development of ecohydraulics and eco-environmental models a challenging subject. Conventionally, computer-based models use a mathematical formulation for the processes involved which are then solved by numerical methods. These models are often derived based on the assumption of spatial homogeneity and conservation principles of mass, momentum and energy. Development of these models often demands a clear understanding of the processes involved. However, the above assumptions are easily violated when spatial heterogeneity, individual species behaviour and local interactions play a significant role in the system dynamics. In particular for eco-environmental systems, knowledge on local interactions that determine the overall system behaviour is not always available. Although the rapid advances of data-driven techniques have recently made great contributions to water-environment related research, data on ecosystems are often quite limited, which restricts the application of data mining methods to eco-environmental system modelling. In addition, no modelling – also not black-box modelling – can be undertaken without having at least some understanding of the basic processes and mechanisms involved. It is always advisable to start exploring any dataset using conventional statistical techniques, as elaborated in this paper for a case study on Western Xiamen Bay, China. Neural network trimming was then used to establish the dominant factors; it was shown that a relatively simple ANN model was quite capable of capturing the essential features, provided the right input parameters are chosen. Examples of integrated approaches to ecohydraulics modelling coupling formulations with cellular automata and physical equations with fuzzy rules are presented for applications on eutrophication modelling of Taihu Lake in China, competitive growths and colonization of two underwater macrophytes in Lake Veluwe in The Netherlands, and forecasting of algal blooms in the Dutch coastal waters on the North Sea. A mussel dynamics model developed for the Upper Mississippi River in the USA demonstrates the feasibility of individual based modelling in ecosystem dynamics. Numerical models are quite capable of simulating the abiotic aquatic environment, including complicated fluid flow and transport mechanisms. However, when it comes to simulating the biotic and ecosystem dynamics, the interaction of individual species with their environment, as well as the interactions amongst species, has to be taken into account. The future of ecohydraulics and eco-environmental modelling thus seems to lie in the integration of different paradigms and techniques, which is the core content of the hydroinformatics discipline.

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29

Benarie, Michel. "Integrated environmental modelling: Design and tools." Science of The Total Environment 71, no. 2 (May 1988): 236. http://dx.doi.org/10.1016/0048-9697(88)90173-8.

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30

Downing, Keith. "Using evolutionary computational techniques in environmental modelling." Environmental Modelling & Software 13, no. 5-6 (October 1998): 519–28. http://dx.doi.org/10.1016/s1364-8152(98)00050-4.

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31

Porter, N. "Modelling of Pollutants in Complex Environmental Systems." Environmental Modelling & Software 25, no. 6 (June 2010): 817. http://dx.doi.org/10.1016/j.envsoft.2009.12.005.

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32

Starkova, Olesja, Abedin I. Gagani, Christian W. Karl, Iuri B. C. M. Rocha, Juris Burlakovs, and Andrey E. Krauklis. "Modelling of Environmental Ageing of Polymers and Polymer Composites—Durability Prediction Methods." Polymers 14, no. 5 (February 24, 2022): 907. http://dx.doi.org/10.3390/polym14050907.

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Polymers and polymer composites are negatively impacted by environmental ageing, reducing their service lifetimes. The uncertainty of the material interaction with the environment compromises their superior strength and stiffness. Validation of new composite materials and structures often involves lengthy and expensive testing programs. Therefore, modelling is an affordable alternative that can partly replace extensive testing and thus reduce validation costs. Durability prediction models are often subject to conflicting requirements of versatility and minimum experimental efforts required for their validation. Based on physical observations of composite macroproperties, engineering and phenomenological models provide manageable representations of complex mechanistic models. This review offers a systematised overview of the state-of-the-art models and accelerated testing methodologies for predicting the long-term mechanical performance of polymers and polymer composites. Accelerated testing methods for predicting static, creep, and fatig ue lifetime of various polymers and polymer composites under environmental factors’ single or coupled influence are overviewed. Service lifetimes are predicted by means of degradation rate models, superposition principles, and parametrisation techniques. This review is a continuation of the authors’ work on modelling environmental ageing of polymer composites: the first part of the review covered multiscale and modular modelling methods of environmental degradation. The present work is focused on modelling engineering mechanical properties.

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33

Brenner, Asher, Mordechai Shacham, and Michael B. Cutlip. "Applications of mathematical software packages for modelling and simulations in environmental engineering education." Environmental Modelling & Software 20, no. 10 (October 2005): 1307–13. http://dx.doi.org/10.1016/j.envsoft.2004.09.007.

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34

Baskaran, A., and T. Stathopoulos. "Prediction of wind effects on buildings using computational methods — review of the state of the art." Canadian Journal of Civil Engineering 21, no. 5 (October 1, 1994): 805–22. http://dx.doi.org/10.1139/l94-087.

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Advancements in computer software and hardware technology provide a new direction for analyzing engineering problems. Recently the field of wind engineering has gained significant momentum in the computer modelling process. This paper reviews the state of the art in computational wind engineering, including the finite element method, finite difference method, and control volume technique. A portion of this paper summarizes the research in this area carried out by the authors. Computations have been made for a variety of building configurations, including normal wind flow conditions for a building with different aspect ratios, and modelling wind environmental conditions around groups of buildings. The computer modelling technique may eventually enhance the design of buildings and structures against wind loading and supplement the current design practice of using building codes and standards or performing experiments in wind tunnels. Key words: buildings, computer modelling, pressure, velocity, wind engineering, wind tunnels.

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35

Jović, Jadranka, and Vladimir Đorić. "TRAFFIC AND ENVIRONMENTAL STREET NETWORK MODELLING: BELGRADE CASE STUDY." TRANSPORT 25, no. 2 (June 30, 2010): 155–62. http://dx.doi.org/10.3846/transport.2010.19.

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The paper presents a procedure for modelling transport demand and analyses effects caused by changes in the characteristics of street network exploitation. Based on the effects of the measures predominantly connected with speed restrictions on characteristic sections, the Scenarios resulting in reduced congestion during peak hour and a decrease in harmful effects of traffic were selected. A rough effectivity analysis of transport vehicle kilometres travelled and travel time on the network was carried out. Transportation modeling is the most efficient way to analyze the effects of traffic solutions. Once established, transport model brings only benefits in future projects. Speed reduction strategy was easily simulated using the transportation modeling procedure. Other sustainable transport and mobility management strategies considering sustainable transportation could also be simulated.

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36

Boltz, J. P., E. Morgenroth, and D. Sen. "Mathematical modelling of biofilms and biofilm reactors for engineering design." Water Science and Technology 62, no. 8 (August 1, 2010): 1821–36. http://dx.doi.org/10.2166/wst.2010.076.

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Mathematical models are critical to modern environmental biotechnology—both in research and in the engineering practice. Wastewater treatment plant (WWTP) simulators are used by consulting engineers and WWTP operators when planning, designing, optimizing, and evaluating the unit processes that comprise municipal and industrial WWTPs. Many WWTP simulators have been expanded to include a submerged completely-mixed biofilm reactor module that is based on the mathematical description of a one-dimensional biofilm. Leading consultants, equipment manufacturers, and WWTP modelling software developers have made meaningful contributions to advancing the use of biofilm models in engineering practice, but the bulk of the engineering community either does not use the now readily available biofilm reactor modules or utilizes them as ‘black-box’ design tools. The latter approach results in the mathematical biofilm models being no more useful than the empirical design criteria and formulations that have been historically applied to biofilm reactor design. The present work provides a consensus report on the state-of-the art, areas of uncertainty, and future needs for advancing the use of biofilm models in engineering design.

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37

Almeida, José-Paulo de, and João Coutinho-Rodrigues. "Modelling environmental impacts over urban areas and facilities." Proceedings of the Institution of Civil Engineers - Municipal Engineer 164, no. 2 (June 2011): 103–16. http://dx.doi.org/10.1680/muen.2011.164.2.103.

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38

Morales, Merten, Meriç Ataman, Sara Badr, Sven Linster, Ioannis Kourlimpinis, Stavros Papadokonstantakis, Vassily Hatzimanikatis, and Konrad Hungerbühler. "Sustainability assessment of succinic acid production technologies from biomass using metabolic engineering." Energy & Environmental Science 9, no. 9 (2016): 2794–805. http://dx.doi.org/10.1039/c6ee00634e.

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Innovative pathways for bio-succinic acid production from biomass are investigated regarding their environmental impact, economic feasibility and process hazard by including state of the art metabolic engineering in process modelling.

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39

Walcher, Sebastian, Joachim Altschuh, Karl-Werner Schramm, and Sebastian Mayer. "Estimates in deterministic fate modelling of environmental chemicals☆." Environmental Modelling & Software 18, no. 10 (December 2003): 929–36. http://dx.doi.org/10.1016/s1364-8152(03)00057-4.

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40

Krueger, Tobias, Trevor Page, Klaus Hubacek, Laurence Smith, and Kevin Hiscock. "The role of expert opinion in environmental modelling." Environmental Modelling & Software 36 (October 2012): 4–18. http://dx.doi.org/10.1016/j.envsoft.2012.01.011.

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41

Segarceanu, Svetlana, George Suciu, and Inge Gavăt. "Environmental Acoustics Modelling Techniques for Forest Monitoring." Advances in Science, Technology and Engineering Systems Journal 6, no. 3 (May 2021): 15–26. http://dx.doi.org/10.25046/aj060303.

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42

John, Andrew, Rory Nathan, Avril Horne, Michael Stewardson, and J. Angus Webb. "How to incorporate climate change into modelling environmental water outcomes: a review." Journal of Water and Climate Change 11, no. 2 (March 23, 2020): 327–40. http://dx.doi.org/10.2166/wcc.2020.263.

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Abstract Environmental water represents a key resource in managing freshwater ecosystems against pervasive threats. The impacts of climate change add further pressures to environmental water management, yet anticipating these impacts through modelling approaches remains challenging due to the complexities of the climate, hydrological and ecological systems. In this paper, we review the challenges posed by each of these three areas. Large uncertainties in predicting climatic changes and non-stationarities in hydrological and ecological responses make anticipating impacts difficult. In addition, a legacy of relying on modelling approaches informed by historic dependencies in environmental water science may confound the prediction of ecological responses when extrapolating under novel conditions. We also discuss applying ecohydrological methods to support decision-making and review applications of bottom-up climate impact assessments (specifically eco-engineering decision scaling) to freshwater ecosystems. These approaches offer a promising way of incorporating climatic uncertainty and balancing competing environmental objectives, but some practical challenges remain in their adoption for modelling environmental water outcomes under climate change.

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43

Tezcan, Hüseyin Onur. "Evaluating road pricing with an engineering perspective: aggregate and disaggregate analysis." Canadian Journal of Civil Engineering 36, no. 6 (June 2009): 1028–36. http://dx.doi.org/10.1139/l09-046.

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The aim of this paper is to present the basic premises of modelling road pricing with an engineering perspective at aggregate and disaggregate levels. An engineering perspective is different than economic perspective according to its analytical and deterministic approach. In this paper most of the economic notions are deliberately simplified, especially at the aggregate level, to obtain a simple, easy to understand, and easy to run model. The paper also includes facts about basic theories of road pricing and economic modelling. To demonstrate the modelling approaches presented in this paper, a simple numerical example is assessed. The results show that aggregate analysis provides understanding of the extent of the impacts whereas disaggregate analysis offers more detailed information. Furthermore, analysis at both levels has the potential to perform a combined modelling study as well.

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44

Simões, Carla L., Lígia M. Costa Pinto, and C. A. Bernardo. "Modelling the economic and environmental performance of engineering products: a materials selection case study." International Journal of Life Cycle Assessment 17, no. 6 (April 3, 2012): 678–88. http://dx.doi.org/10.1007/s11367-012-0414-y.

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45

Suckow, M. "Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering. Von A. K. Verma." Chemie Ingenieur Technik 88, no. 12 (November 23, 2016): 1975. http://dx.doi.org/10.1002/cite.201690094.

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46

Belia, E., Y. Amerlinck, L. Benedetti, B. Johnson, G. Sin, P. A. Vanrolleghem, K. V. Gernaey, et al. "Wastewater treatment modelling: dealing with uncertainties." Water Science and Technology 60, no. 8 (October 1, 2009): 1929–41. http://dx.doi.org/10.2166/wst.2009.225.

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This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model prediction accuracy and uncertainty issues. It also aims to identify future research needs. Ultimately the goal of such a discussion would be to generate transparent and objective methods of explicitly evaluating the reliability of model results, before they are implemented in an engineering decision-making context.

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47

Haq, Hafiz, Petri Välisuo, and Seppo Niemi. "Modelling Sustainable Industrial Symbiosis." Energies 14, no. 4 (February 22, 2021): 1172. http://dx.doi.org/10.3390/en14041172.

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Industrial symbiosis networks conventionally provide economic and environmental benefits to participating industries. However, most studies have failed to quantify waste management solutions and identify network connections in addition to methodological variation of assessments. This study provides a comprehensive model to conduct sustainable study of industrial symbiosis, which includes identification of network connections, life cycle assessment of materials, economic assessment, and environmental performance using standard guidelines from the literature. Additionally, a case study of industrial symbiosis network from Sodankylä region of Finland is implemented. Results projected an estimated life cycle cost of €115.20 million. The symbiotic environment would save €6.42 million in waste management cost to the business participants in addition to the projected environmental impact of 0.95 million tonne of CO2, 339.80 tonne of CH4, and 18.20 tonne of N2O. The potential of further cost saving with presented optimal assessment in the current architecture is forecast at €0.63 million every year.

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48

Hearn, G. J. "Geomorphology in engineering geological mapping and modelling." Bulletin of Engineering Geology and the Environment 78, no. 2 (October 25, 2017): 723–42. http://dx.doi.org/10.1007/s10064-017-1166-5.

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SAVVIDOU, C., and P. J. CULLIGAN. "THE APPLICATION OF CENTRIFUGE MODELLING TO GEO-ENVIRONMENTAL PROBLEMS." Proceedings of the Institution of Civil Engineers - Geotechnical Engineering 131, no. 3 (July 1998): 152–62. http://dx.doi.org/10.1680/igeng.1998.30471.

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Nopens, Ingmar, Elena Torfs, Joel Ducoste, Peter A. Vanrolleghem, and Krist V. Gernaey. "Population balance models: a useful complementary modelling framework for future WWTP modelling." Water Science and Technology 71, no. 2 (December 9, 2014): 159–67. http://dx.doi.org/10.2166/wst.2014.500.

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Abstract:

Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit processes in wastewater treatment plants could potentially benefit from this framework, especially when distributed dynamics have a significant impact on the overall unit process performance. In these cases, current models that rely on average properties cannot sufficiently capture the true behaviour and even lead to completely wrong conclusions. Examples of distributed properties are bubble size, floc size, crystal size or granule size. In these cases, PBMs can be used to develop new knowledge that can be embedded in our current models to improve their predictive capability. Hence, PBMs should be regarded as a complementary modelling framework to biokinetic models. This paper provides an overview of current applications, future potential and limitations of PBMs in the field of wastewater treatment modelling, thereby looking over the fence to other scientific disciplines.

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