State-of-practice on as-is modelling of industrial facilities

90% of the time needed for the conversion from point clouds to 3D models of industrial facilities is spent on geometric modelling due to the sheer number of Industrial Objects (IOs) of each plant. Hence, cost reduction is only possible by automating modelling. Our previous work has successfully identified the most frequent industrial objects which are in descending order: electrical conduit, straight pipes, circular hollow sections, elbows, channels, solid bars, I-beams, angles, flanges and valves. We modelled those on a state-of-theart software, EdgeWise and then evaluated the performance of this software for pipeline and structural modelling. The modelling of pipelines is summarized in three basic steps: (a) automated extraction of cylinders, (b) their semantic classification and (c) manual extraction and editing of pipes. The results showed that cylinders are modelled with 75 % recall and 62 % precision on average. We discovered that pipes, electrical conduit and circular hollow sections require 80 % of the Total Modelling Hours (TMH) of the 10 most frequent IOs to build the plant model. TMH was then compared to modelling hours in Revit and showed that 67 % of pipe modelling time is saved by EdgeWise. This paper is the first to evaluate state-of-the-art industrial modelling software. These findings help in better understanding the problem and serve as the foundation for researchers who are interested in solving i

Modelling Fresh Strawberry Supply "From-Farm-to-Fork" as a Complex Adaptive Network

 The purpose of this study is to model and thereby enable simulation of the complete business entity of fresh food supply. A case narrative of fresh strawberry supply provides basis for this modelling. Lamming et al. (2000) point to the importance of discerning industry-specific product features (or particularities) regarding managing supply networks when discussing elements in "an initial classification of a supply network" while Fisher (1997) and Christopher et al. (2006, 2009) point to the lack of adopting SCM models to variations in products and market types as an important source of SCM failure. In this study we have chosen to move along a research path towards developing an adapted approach to model end-to-end fresh food supply influenced by a combination of SCM, system dynamics and complex adaptive network thinking...

Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

Resource recovery from wastewater and sludge: modelling and control challenges

Wastewater treatment plants (WWTPs) have been renamed water resource recovery facilities (WRRFs). Our industry is quickly moving from an end-of-pipe environmental protection service to an economic producer of valued products for society. Based on a critical review of resource recovery technologies that are currently applied or in advanced development, it became obvious that most of these technologies are based on physicochemical unit processes (precipitation, volatilization, sorption, …). Current industrial practice for the design and operation of WRRFs is based on mathematical models describing the traditional biological processes. The modeling challenge therefore is to provide practice with proper models for the physicochemical resource recovery processes. The fact that the WRRFs aim at delivering valued products that can partially replace those produced by other means (typically in the chemical industry) leads to a paradigm shift in specifications of the outputs of the facility: no longer treated wastewater and biosolids, but products that have to compete with what is already on the market. The tighter specifications will thus impose a challenge on the process control systems that will be required to guarantee the quality of the products of the WRRFs

Numerical modelling and simulation in sheet metal forming

The application of numerical modelling and simulation in manufacturing technologies is looking back over about a 20–30 years history. In recent years, the role of modelling and simulation in engineering and in manufacturing industry has been continuously increasing. It is well known that during manufacturing processes simultaneous the effect of many different parameters can be observed. This is the reason why in former years, detailed analysis of manufacturing processes could have been done only by time-consuming and expensive trial-and-error methods. Due to the recent developments in the methods of modelling and simulation, as well as in computational facilities, modelling and simulation has become an everyday tool in engineering practice. Besides the aforementioned facts, the emerging role of modelling and simulation can also be explained by the growing globalisation and competition of the world market requiring shorter lead times and more cost effective solutions. In spite the enormous development of hardware and software facilities, the exclusive use of numerical modelling still seems to be very time- and cost consuming, and there is still often a high scepticism about the results among industrialists. Therefore, the purpose of this paper is to overview the present situation of numerical modelling and simulation in sheet metal forming, mainly from the viewpoint of scientific research and industrial applications

The challenges, uncertainties and opportunities of bioaerosol dispersion modelling from open composting facilities

Bioaerosols are ubiquitous organic particles that comprise viruses, bacteria and coarser fractions of organic matter. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific human activities such as water treatment, intensive agriculture and composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosols are not considered ‘traditional’ pollutants in the same way as PM10, PM2.5, and gases such as NO2, and consequently dispersion models do not include a bespoke method for their assessment. As identified in previous studies, priority areas for improving the robustness of these dispersion models include: 1) the development of bespoke monitoring studies designed to generate accurate modelling input data; 2) the publication of a robust emissions inventory; 3) a code of practice to provide guidelines for consistent bioaerosol modelling practices; and 4) a greater understanding of background bioaerosol emissions. The aim of this research project, funded by the Natural Environmental Research Council (NERC), is to address these key areas through a better understanding of the generation, concentration and potential dispersion of bioaerosols from intensive agricultural and biowaste facilities, using case studies developed at specific locations within the UK. The objective is to further refine existing bioaerosol monitoring and modelling guidelines to provide a more robust framework for regulating authorities and site operators. This contribution outlines the gaps that hinder robust dispersion modelling, and describes the on-site bioaerosol data collection methods used in the study, explaining how they might be used to close these gaps. Examples of bioaerosol dispersion modelled using ADMS 5 are presented and discussed