Complex Industrial Sites Research Articles

A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization

At complex industrial sites, the high number of large consumers that make the technological process chain requires direct supply from the main high-voltage grid. Often, for operational flexibility and redundancy, the main external supply is complemented with small local generation units. When a contingency occurs in the grid and the main supply is cut off, the local generators are used to keep in operation the critical consumers until the safe shutdown of the entire process can be achieved. In these scenarios, in order to keep the balance between local generation and consumption, the classic approach is to use under-frequency load-shedding schemes. This paper proposes a new load-shedding algorithm that uses particle swarm optimization and forecasted load data to provide a low-cost alternative to under-frequency methods. The algorithm is built using the requirements and input data provided by a real industrial site from Romania. The results show that local generation and critical consumption can be kept in stable operation for the time interval required for the safe shutdown of the running processes.

High-resolution 3D geological modelling of heterogeneity in poorly exposed glacial deposits using sedimentary and glaciotectonic architectural element analysis: a case example from Sellafield in west Cumbria, UK

Three-dimensional modelling of superficial geology is challenging, particularly for complex industrial sites such as the Sellafield nuclear site, Cumbria, UK. A lithostratigraphic approach is sufficient to show distribution of key units where only a general understanding of hydrogeology is required. For many sites, however, a much higher-resolution understanding is needed to better characterize heterogeneity and identify potential pathways for contaminant transport within safety case development and remediation planning. Models that focus on often thin, laterally discontinuous, heterogeneous sedimentary units are beset with issues including (1) a lack of exposure coupled with a dearth of data gathered by low-intrusive and intrusive means, (2) structural, stratigraphic and sedimentological complexities making correlation between data points difficult and (3) uncertainties associated with data quality. However, these problems may be overcome by combining land-system-based sedimentary and glaciotectonic architectural analysis of local field analogues with the creation of a portfolio of generic unit-bounding surface geometries. We test this through the development of a high-resolution 3D geological model of Sellafield nuclear site, where exposures are sparse, but shallow site-investigation boreholes are many. The results demonstrate that land-system-based sedimentary and glaciotectonic architectural element analysis can be applied to capture substantial subsurface heterogeneity resulting from dynamic glacial processes.

Optimal positioning of terrestrial LiDAR scanner stations in complex 3D environments with a multiobjective optimization method based on GPU simulations

Currently, the scanning of complex industrial sites is commonly performed using terrestrial LiDAR scanners. As the quality of the resulting point cloud depends mainly on the number and positions of LiDAR stations, this scanning process can be preliminarily optimized by means of a 3D model. A previous study proposed multiobjective optimization based on the linear scalarization of three functions to maximize coverage and overlapping of point cloud stations while minimizing their number. Because these objectives conflict, this study proposes the use of MO-CMA-ES, a global multiobjective optimization algorithm, to provide a full Pareto front and allow the user to make an informed decision. Our method is the first to rely on realistic LiDAR simulations that operate in fully 3D complex environments and provide point clouds with optionally noisy coordinates. For performance considerations, ray-traced simulations and objective evaluations were performed using a GPU. Furthermore, clash detection in the proximity of station positions was also considered. After validating our method’s behavior and demonstrating its superiority over the conventional approach in a simple case, we conducted a study on an industrial-grade case based on a 2.7-million-triangle model, further demonstrating our method’s effectiveness by producing a minimal 15-station solution with optimal coverage and overlapping.

Machine-learning-based top-view safety monitoring of ground workforce on complex industrial sites

Telescopic cranes are powerful lifting facilities employed in construction, transportation, manufacturing and other industries. Since the ground workforce cannot be aware of their surrounding environment during the current crane operations in busy and complex sites, accidents and even fatalities are not avoidable. Hence, deploying an automatic and accurate top-view human detection solution would make significant improvements to the health and safety of the workforce on such industrial operational sites. The proposed method (CraneNet) is a new machine learning empowered solution to increase the visibility of a crane operator in complex industrial operational environments while addressing the challenges of human detection from top-view on a resource-constrained small-form PC to meet the space constraint in the operator’s cabin. CraneNet consists of 4 modified ResBlock-D modules to fulfill the real-time requirements. To increase the accuracy of small humans at high altitudes which is crucial for this use-case, a PAN (Path Aggregation Network) was designed and added to the architecture. This enhances the structure of CraneNet by adding a bottom-up path to spread the low-level information. Furthermore, three output layers were employed in CraneNet to further improve the accuracy of small objects. Spatial Pyramid Pooling (SPP) was integrated at the end of the backbone stage which increases the receptive field of the backbone, thereby increasing the accuracy. The CraneNet has achieved 92.59% of accuracy at 19 FPS on a portable device. The proposed machine learning model has been trained with the Standford Drone Dataset and Visdrone 2019 to further show the efficacy of the smart crane approach. Consequently, the proposed system is able to detect people in complex industrial operational areas from a distance up to 50 meters between the camera and the person. This system is also applicable to the detection of any other objects from an overhead camera.

Design and Implementation of the Universal Servo Control Algorithm Verification System Based on High-Speed Communication Fieldbus

In recent years, there have been several breakthroughs in the theoretical research of servo control algorithms. However most of these control algorithms remain in the simulation stage. They are difficult to be applied directly to practical platforms or complex industrial sites because of the lack of an experimental system suitable for the verification of their effectiveness. To address this problem, we designed a multi-function servo control algorithm verification experiment system (MVES) within the MATLAB/Simulink theoretical simulation model directly to communicate with the TwinCAT 3 PLC master program to perform different servo control experiments. The MVES supports various Simulink models. However, its and the operation is simple and convenient, which greatly reduces the workload of the algorithm test and has important practical value. Two sets of comparative experiments were used to verify the versatility and superiority of MVES.

Multi-sensor core logging (MSCL) and X-ray computed tomography imaging of borehole core to aid 3D geological modelling of poorly exposed unconsolidated superficial sediments underlying complex industrial sites: An example from Sellafield nuclear site, UK

The 3D characterisation of geology underlying complex industrial sites such as nuclear plants is problematic due to the presence of the built infrastructure that restricts or in some cases completely prevents access for geologists to the subsurface environment. Outcrops are rare, geophysics surveys are often impossible (particularly at nuclear plants where activities such as vibroseis are frowned upon due to their effect on the infrastructure itself), and boreholes are often the only way to obtain subsurface data. Yet, with sedimentary deposits in particular, geotechnical logging undertaken to specific standards sometimes misses key information that could have been used to directly inform the creation of geological 3D models.Multi-sensor core logging (MSCL) and X-ray computed tomography (XCT) undertaken on core obtained from a borehole within the Sellafield nuclear plant, is used to illustrate the potential for the techniques to contribute significantly to the creation of 3D subsurface geological models, particularly where access is restricted, such as within nuclear industry locations. Geophysical characteristics are recorded and used to reassess and enhance geotechnical descriptions, leading to the modification of existing unit boundaries or the creation of new ones. A new sedimentary log was created and this was used in a comparison with existing logs and nearby historic exposures, and as the basis for an illustration of industrial site to regional correlation.

Groundwater characterization and monitoring at a complex industrial waste site using electrical resistivity imaging

A contaminated industrial waste site in Washington State (USA) containing buried, metallic-waste storage tanks, pipes, and wells, was evaluated to determine the feasibility of monitoring groundwater remediation activities associated with an underlying perched aquifer system using electrical resistivity tomography. The perched aquifer, located ~65 m below ground surface and ~10 m above the regional water table, contains high concentrations of nitrate, uranium, and other contaminants of concern from past tank leaks and intentional releases of wastes to surface disposal sites. The extent of the perched water aquifer is not well known, and the effectiveness of groundwater extraction for contaminant removal is uncertain, so supplemental characterization and monitoring technologies are being evaluated. Numerical simulations of subsurface flow and contaminant transport were performed with a highly resolved model of the hydrogeologic system and waste site infrastructure, and these simulations were used as the physical basis for electrical resistivity tomography modeling. The modeling explicitly accounted for metallic infrastructure at the site. The effectiveness of using surface electrodes versus surface and horizontal subsurface electrodes, for imaging groundwater extraction from the perched water aquifer, was investigated. Although directional drilling is a mature technology, its use for electrode emplacement in the deep subsurface under a complex industrial waste site via horizontal wells has not yet been demonstrated. Results from this study indicate that using horizontal subsurface electrode arrays could significantly improve the ability of electrical resistivity tomography to image deep subsurface features and monitor remediation activities under complex industrial waste sites.

Marine Sediments from a Contaminated Site: Geotechnical Properties and Chemo-Mechanical Coupling Processes

The city of Taranto in the south of Italy is one of the areas declared as “at high risk of environmental crisis” by the Italian government because it represents one of the most complex industrial sites in Europe, located near urban areas of high population density. The rich ecosystem of the Mar Piccolo basin, located at north of Taranto, started exhibiting unconfutable signs of environmental pollution, confirmed by the high concentrations of organic and inorganic contaminants. Among the different aspects involved in the environmental studies aiming at the basin remediation, this paper focuses on submarine sediments and reports some results of the geotechnical laboratory investigations which made also use of non-standard equipment and revised procedures for data interpretation in order to take account of the sediments’ contamination and heterogeneities. The geotechnical laboratory tests show that, despite the Mar Piccolo recent Holocene sediments having similar origin and composition to those of the Sub-Apennine clay basic formation, their behavioral facets appear to be altered by the presence of contaminants of both natural and anthropogenic origin. Results of washing tests are also presented as a first attempt to quantify the effects of chemo-mechanical coupling processes on the plasticity properties of the shallow sediments.

A framework addressing a safe ageing management in complex industrial sites: The Italian experience in «Seveso» establishments

In Europe, the Directive 2012/18/EU (Seveso III) strengthens the obligation to adopt a program assuring the integrity of critical equipment at major hazard establishments, by taking into account actual deterioration mechanisms (internal and external corrosion, erosion, thermal and mechanical fatigue, etc.). The program must cover all phases of the lifecycle and ensure a safe ageing of equipment, particularly when these are reaching the final stage of life. The effectiveness of the integrity program must be carefully assessed during the audits planned by the establishment's operator as well as by inspectors on behalf of the Competent Authorities. The adoption of a Risk Based Inspection scheme provides a valuable help to face this matter. The operator is, anyway, required a considerable effort to face at least three issues related to: (i) the understanding of concurring physical and chemical phenomena; (ii) the management of information associated with each individual component and its history, (iii) the appropriate measurement, including acquisition and management of data. There is a considerable difficulty in understanding these issues during Seveso inspections and external audits, because time and resources are often limited. For this reason, models and methods supporting the definition of the ageing status and trend in industrial sites are needed. This paper analyses the main factors affecting ageing. A framework for “ageing” assessment in complex industrial sites, including “Seveso” establishments, is proposed; then, its validation, by means of data collected during a testing phase carried out in Italy, is also given.

Demonstration of spatial greenhouse gas mapping using laser absorption spectrometers on local scales

A system for measuring the two-dimensional (2-D) spatial distribution of atmospheric CO2 over complex industrial sites and urban areas on the order of 1 to 30 km2 every few minutes with a spatial resolution as high as tens of meters has been developed and demonstrated over the past 3 years. The greenhouse gas (GHG) laser imaging tomography experiment (GreenLITE™) provides improved measurement capabilities for applications ranging from automated 24/7 monitoring of ground carbon storage/sequestration (GCS) sites to long-duration real-time analyses of GHG sources and sinks in urban environments. GreenLITE combines a set of sensors based on an intensity modulated continuous wave approach with 2-D sparse tomographic reconstruction mechanisms to compute a 2-D map of CO2 concentrations over the area of interest. GreenLITE systems have recently been deployed at a number of test facilities, including a 4000-h demonstration at a GCS site in Illinois and an urban deployment in Paris, France, from November 2015 to the present. This paper describes the GreenLITE concept and the associated measurement capabilities and provides proof of concept results and analyses of observations from both short-term tests as well as longer-term industrial and urban deployments.

Performance analysis of an air quality CFD model in complex environments: Numerical simulation and experimental validation with EMU observations

Assessment of air quality in complex industrial and urban regions is essential in setting effective policies for sustainable development of society and assisting to improve the environment and thereby support health and safety. In this study, a CFD model fluidyn-PANACHE, dedicated to the dispersion of hazardous gases in complex industrial and urban sites, is critically validated with tracer observations from EMU experiment for two distinct types of sources in two geometrically different environments: (i) Case-A1 (release from an open door in courtyard area of a simple L-shaped building), and (ii) Case-C1 (continuous release over the larger distances around an industrial site featuring numerous buildings and complex local topography). The steady RANS solution is used first to get quick results and comparison with the experimental data shows a good agreement between the modelled and measured concentrations. Nevertheless, in order to examine the performance of the solver, unsteady RANS simulations are performed. A detailed statistical analysis shows that the performance of fluidyn-PANACHE against both Cases of EMU observations is well within the acceptable bounds of statistical measures for air quality applications. It is observed that in a simple geometry with lesser complexity in Case-A1, steady and unsteady simulations give similar performance against the tracer observations and predicts ≈68% points within a factor of two. In a more complex industrial site in Case-C1, unsteady RANS is performing slightly better than the steady simulation and it predicts ≈80.0% points within factor of two, which is higher than ≈67.0% points from the steady simulation.

Targeting capital cost of excess heat collection systems in complex industrial sites for district heating applications

The objective of this study is to develop a methodology for estimating the investment costs for heat collection systems gathering excess heat from complex industrial sites and delivering it to a DH (district heating) network. The paper presents a case study conducted on Sweden's largest chemical cluster. In a previous paper, the economic feasibility of delivering heat from the cluster to a regional DH system proved to be favorable under a wide range of price conditions. We develop the methodology used previously in order to identify how each of the plants should contribute to the heat delivery in order to achieve the lowest total investment cost within the cluster. The optimization problem is formulated with the constraint that each plant delivers heat to the DH network separately and at the temperature required by the network.Investments for heat collection systems were estimated for the current configuration of the cluster's energy system (Base case) and for two possible future configurations with increased levels of internal heat recovery. The resulting optimal contribution mix provides a detailed overview of how the plants compete at different specified levels of DH delivery. In the Base case, two plants strongly compete due to similar investment costs.

Network design and planning of wireless embedded systems for industrial automation

The widespread adoption of wireless systems for industrial automation calls for the development of efficient tools for virtual planning of network deployments similarly as done for conventional Fieldbus and wired systems. In industrial sites the radio signal propagation is subject to blockage due to highly dense metallic structures. Network planning should therefore account for the number and the density of the 3D obstructions surrounding each link. In this paper we address the problem of wireless node deployment in wireless industrial networks, with special focus on WirelessHART IEC 62591 and ISA SP100 IEC 62734 standards. The goal is to optimize the network connectivity and develop an effective tool that can work in complex industrial sites characterized by severe obstructions. The proposed node deployment approach is validated through a case study in an oil refinery environment. It includes an ad-hoc simulation environment (RFSim tool) that implements the proposed network planning approach using 2D models of the plant, providing connectivity information based on user-defined deployment configurations. Simulation results obtained using the proposed simulation environment were validated by on-site measurements.

Field-testing a new directional passive air sampler for fugitive dust in a complex industrial source environment

Quantifying the sources of fugitive dusts on complex industrial sites is essential for regulation and effective dust management. This study applied two recently-patented Directional Passive Air Samplers (DPAS) to measure the fugitive dust contribution from a Metal Recovery Plant (MRP) located on the periphery of a major steelworks site. The DPAS can collect separate samples for winds from different directions (12 × 30° sectors), and the collected dust may be quantified using several different measurement methods. The DPASs were located up and down-prevailing-wind of the MRP processing area to (i) identify and measure the contribution made by the MRP processing operation; (ii) monitor this contribution during the processing of a particularly dusty material; and (iii) detect any changes to this contribution following new dust-control measures. Sampling took place over a 12-month period and the amount of dust was quantified using photographic, magnetic and mass-loading measurement methods. The DPASs are able to effectively resolve the incoming dust signal from the wider steelworks complex, and also different sources of fugitive dust from the MRP processing area. There was no confirmable increase in the dust contribution from the MRP during the processing of a particularly dusty material, but dust levels significantly reduced following the introduction of new dust-control measures. This research was undertaken in a regulatory context, and the results provide a unique evidence-base for current and future operational or regulatory decisions.

Energy efficiency measurement in industrial processes

Although the meaning of energy efficiency is clear, different definitions exist and important issues relating to its implementation still need to be addressed. It is now recognised that complicating factors – such as complex industrial sites and energy flows, multiple products and fuels, and the influence of production rate on energy efficiency – render it necessary to adopt a structured framework to define and measure energy efficiency more precisely. In this paper, a methodology is proposed to build such a framework. The whole energy system of a site is represented using a single matrix equation, which expresses the relationship between imported energies and energy drivers. The elements of the matrix are the specific energy consumptions of each single process. Mathematical process modelling, through statistical analysis of energy consumption data, is used to quantify the specific energy consumption as a function of the output. The results of this structured approach are relevant for energy benchmarking, budgeting and targeting purposes. Furthermore, this approach is suitable for implementation in an energy management system standard (e.g. EN 16001, ISO 50001) or LCA standard (e.g. ISO 14044). Glass and cast iron melting processes are presented in order to illustrate the application of the method.

AN APPROACH TO STUDY HEALTH EFFECTS OF ENVIRONMENTAL CONTAMINATION FROM OIL REFINERIES IN A LONGITUDINAL PERSPECTIVE

Background and Aims: In 2010 the world total number of oil refineries was more than 650, about 200 in Europe. Oil refineries are complex industrial sites that manage large amounts of raw materials and products. Refineries generate emissions of many different pollutants. Most of the emissions are into the air. The aim of this contribution is to describe an approach developed to study the relationship between over-time emissions from oil refineries and over-time health profiles of populations living near the plants. This approach was used to study refineries spread over the Italian territory. Methods: For each plant constructed in Italy, the following data were collected: year of operation start off and close down; annual oil consumption; and, where available, type of refinery cycle. Estimates of emissions into the air of several pollutants were used to categorize plants. Populations to be studied through a small-area approach were identified by an ad hoc GIS model. Outcomes of a priori interest were selected through a review of the available epidemiological evidence. Results: Forty-five refinery plants were constructed in Italy in the last century. Most of the plants started operations in the ’60s, and some were closed down after one or more decades of activity. Oil consumption from 1948 up to 2007 was collected for each plant. Nearly 15 plants were selected to study time trends and time-related variables for risk of lung cancer, some hematopoietic neoplasms, respiratory system diseases, neurological diseases and perinatal conditions in selected populations. Conclusions: The proposed approach has the potential to go beyond the limits of previous studies that could not evaluate refineries health impact over time. It could be used in other countries and is suitable to meta-analyses.

Effect modelling and optimization, a new methodology for combined energy and environment synthesis of industrial processes

Combining mathematical programming and thermodynamic analysis for solving energy integration of industrial processes appears to be a very powerful tool to target minimum energy cost requirements. Defining the role played by thermodynamic analysis and numerical methods allowed us to define a generic method for calculating the energy integration even of complex industrial sites. The method has been adapted to solve combined energy and environments synthesis of industrial processes. In the approach, different alternative process schemes are included in this superstructure, the optimal structure being extracted using MILP optimization that minimizes the cost of energy, including raw materials, fuels and electricity, rather than just thermal energy. This new modelling approach, that allowed us to target process modifications and improvements has been named EMO (effect modelling and optimization). In the paper, we discuss how the approach has been extended to represent the environmental and energy interactions both in terms of objective functions and constraints. Having developed the mathematical tool, we discuss the role that this tool plays in the engineering method developed to reach combined energy and environmental targets in industrial processes. The generic method has been validated on applications in two major industries: one from the pulp and paper industry and one from the brewing industry. The example of the Kraft pulp process is used to illustrate the application of the approach.