Application of multivariate statistical methods to the modelling of a flue gas treatment stage in a waste-to-energy plant

Among all the macro-pollutants released by waste combustion, acid contaminants such as sulphur dioxide, hydrogen chloride and hydrogen fluoride have the lowest emission standards in environmental regulations in EU, USA and China. Their removal is thus a key step of flue gas treatment in waste-to-energy (WtE) plants. A widespread approach for acid gas removal is by in-duct injection of dry powdered sorbents, which neutralize the acid pollutants by gas-solid reaction. However, systems based on dry injection, albeit cost-effective and easy to operate, suffer from a limited knowledge of the gas-solid reaction process at industrial operating conditions. High excess of sorbent feed rate is generally required to obtain high acid gas removal efficiencies. The present study proposes a multivariate statistical approach to the modelling of acid gas treatment units, with the aim of extracting information from real process data in order to derive a predictive model of dynamic acid gas removal efficiency. Specifically, process data regarding the composition of the flue gas, the sorbent feed and other operating conditions were elaborated to characterise the different phenomena that influence acid gas abatement. Eventually, a partial least squares (PLS) regression was set up to predict the outlet concentration of hydrogen chloride as a function of the measured process variables. The resulting model is a step forward with respect to previously available stationary models. Its simplicity and low computational cost could make PLS a promising candidate for model-based process control. Nonetheless, a linear approach such as PLS still comes short of predicting large instantaneous deviations from the typical range of operation (e.g. abrupt peaks in inlet acid gas load), for which a modification of the PLS model to incorporate non-linear behaviour is envisaged

Domino effects related to explosions in the framework of land use planning

The present study analyses the possible escalation due to the damage of industrial equipment containing hazardous materials loaded by pressure waves produced either by an accidental source as a Vapour Cloud Explosion, or by a voluntary external attack such as the explosion of a TNT charge located nearby the industrial facility. The results obtained evidence the similarities and the differences for the two explosion sources in terms of structural damage, loss of containment and of expected impacts on the population. In particular, a specific vulnerability assessment was carried out defining a case-study in order to evidence the different potential impact of domino effect triggered by internal process causes respect to escalation scenarios caused by external acts of interference. © 2013, AIDIC Servizi S.r.l

Controlled targeting of different subcellular sites by porphyrins in tumour-bearing mice.

Unilamellar liposomes of dipalmitoyl-phosphatidylcholine can incorporate various porphyrins in either the phospholipid bilayer or the internal aqueous compartment depending on the water-/lipo-solubility of the drug. Intraperitoneal injection of the liposome-bound porphyrins to mice bearing a MS-2 fibrosarcoma results in remarkably more efficient tumour targeting than that obtained by administration of the same porphyrins dissolved in homogeneous aqueous solution. Moreover, also water-insoluble porphyrins can be transported to the tumour via liposomes. Fractionation of liver and neoplastic cells indicates that the subcellular distribution of liposome-delivered porphyrins is also dependent on their solubility properties: thus, relatively polar porphyrins, such as tetra(4-sulfonatophenyl)porphine and uroporphyrin, are mainly recovered from the soluble fraction, whereas hydrophobic porphyrins, such as haematoporphyrin or porphyrin esters, preferentially partition in the cytoplasmic membrane. As a consequence, different subcellular sites can be targeted by porphyrins and possibly photodamaged through a suitable choice of the drug-carrier system

Damage models for storage and process equipment involved in flooding events

The present study focuses on the accidents caused by the impact of floods on storage and process equipment. This type of accident is classified as a NaTech (Natural-Technological) event and resulted in severe consequences in several past accidents. A methodology was developed for the determination of vulnerability models aimed at the estimation of equipment damage probability on the basis of severity or intensity parameters of the flooding. A mechanical model was developed, based on the comparison between the flooding intensity and the resistance of a vessel and/or its support. Simplified vulnerability functions were derived. Finally, a case-study was set up and analysed to show the potentialities of the methodology and the implementation of results in quantitative risk analysis. © 2013, AIDIC Servizi S.r.l

A data-driven approach to improve control room operators' response

Digitalization has significantly improved productivity and efficiency within the chemical industry. Distributed Control Systems and extensive use of sensor networks enable advanced control strategies and increase optimization opportunities. On the other hand, chemical plants are increasingly complex, equipment is highly interlinked, and it is more difficult to describe the system dynamics through first principles. Finding the root causes of process upsets and predicting dangerous deviations in process conditions is often challenging. Advanced and dynamic tools are needed to grant safe and stable operations in such a complex and multivariate environment. In this context, Machine Learning techniques may be used to exploit and retrieve knowledge from the large amount of data that chemical plants produce and store on a daily basis. Data-driven methods may be adopted to develop predictive models and support a proactive approach to process safety. The study aims to develop Machine Learning techniques to improve the response of control room operators during critical events. Specifically, alarm data originated in an upper-tier Seveso site have been collected, cleaned, and analyzed to identify periods of intense alarm activity. Alarm behavior following operator responses has been evaluated to assess whether the actions were adequate to prevent future alarm occurrences. In doing so, alarm events that reoccur within 30 minutes after an operator acknowledgment have been identified and labeled. Subsequently, a hybrid classification algorithm was trained to predict the probability that a critical alarm reoccurs after being acknowledged by the operator. This predictive tool might be used to support the operator's decision-making process and focus his/her attention on critical alarms that are more likely to occur again in the near future

Analysis of the impact of wildland-urban-interface fires on LPG domestic tanks

Managing Wildland-Urban-Interface (WUI) fires is a challenging task due to the inherent complexity of the WUI environment. To ensure the success of strategies for the protection of population and structures, safety measures have to be implemented at different scales (landscape, community and homeowner). The present study is focused on the homeowner scale and deals with the threat related to the presence of LPG domestic tanks in a WUI fire scenario. Recent accidents have demonstrated that the risk associated with this type of installation is real, but often disregarded by residents. A methodology was developed, providing a set of indicators that may easily be compared with risk acceptance criteria, assessing whether the integrity of an LPG tank exposed to WUI fire scenarios is compromised or not. The methodology is applicable to a vast range of situations and at a different level of detail according to available data. A number of case studies were carried out, showing that WUI fire scenarios impacting on domestic LPG tanks complying with regulations currently adopted in several Mediterranean countries cannot be deemed safe. The methodology proposed represents an advanced tool to assist on safety distances sizing to be prescribed by standards, driving regulators towards better-informed decision-making

Fragments Generated during Liquid Hydrogen Tank Explosions

Liquid hydrogen (LH2) may be employed to transport large quantities of pure hydrogen or be stored onboard of ships, airplanes and trains fuelled by hydrogen, thanks to its high density compared to gaseous compressed hydrogen. LH2 is a cryogenic fluid with an extremely low boiling point (-253°C at atmospheric pressure) that must be stored in double-walled vacuum insulated tanks to limit the boil-off formation. There is limited knowledge on the consequences of LH2 tanks catastrophic rupture. In fact, the yield of the consequences of an LH2 tank explosion (pressure wave, fragments and fireball) depend on many parameters such as tank dimension, filling degree, and tank internal conditions (temperature and pressure) prior the rupture. Only two accidents provoked by the rupture of an LH2 tank occurred in the past and a couple of experimental campaigns focussed on this type of accident scenario were carried out for LH2. The aim of this study is to analyse one of the LH2 tank explosion consequences namely the fragments. The longest horizontal and vertical ranges of the fragments thrown away from the blast wave are estimated together with the spatial distribution around the tank. Theoretical models are adopted in this work and validated with the experimental results. The proposed models can aid the risk analysis of LH2 storage technologies and provide critical insights to plan a prevention and mitigation strategy and improve the safety of hydrogen applications

Data-driven Models for Advanced Control of Acid Gas Treatment in Waste-to-energy Plants

This paper presents a study of identification and validation of data-driven models for the description of the acid gas treatment process, a key step of flue gas cleaning in waste-to-energy plants. The acid gas removal line of an Italian plant, based on the injection of hydrated lime, Ca(OH)2, for the abatement of hydrogen chloride, HCl, is investigated. The final goal is to minimize the feed rate of reactant needed to achieve the required HCl removal performance, also reducing as a consequence the production of solid process residues. Process data are collected during dedicated plant tests carried out by imposing Generalized Binary Noise (GBN) sequences to the flow rate of Ca(OH)2. Various input-output and state-space models are identified with success, and related model orders are optimized. The models are then validated on different datasets of routine plant operation. The proposed modeling approach appears reliable and promising for control purposes, once implemented into advanced model-based control structures

Vulnerability Assessment of Industrial Sites to Interface Fires and Wildfires

In the framework of climate change, the hazard caused by wildfires approaching the anthropic settlements is raising an increasing concern. Fatalities and relevant damage to properties were recently caused by wildfires affecting the Wildland-Urban and Wildland-Industrial Interfaces. Industrial sites storing large quantities of hazardous materials are vulnerable to interface fires, which have the potential to trigger specific cascading events such as Natech scenarios followed by domino effects. The present study aims at providing a methodology for the quantitative assessment of the vulnerability of industrial sites exposed to wildfires. The approach provides a novel framework for the identification and quantification of all the chains of failures that may occur due to wildfires or interface fires approaching industrial sites. The methodology accounts for the thermal radiation from fires in both primary Natech scenarios and cascading scenarios triggered by domino effects. The dynamic features of interface fires and the synergistic effects of multiple fires are also taken into account. The results of a case study demonstrated the importance of considering the dynamic behavior of wildfire, which strongly affects the vulnerability of industrial structures. The results also evidence the importance of emergency management and first response on the overall vulnerability figures

New insights into the pathogenesis of bullous pemphigoid: 2019 update

There are several lines of evidence indicating that the physiopathological bases of bullous pemphigoid (BP), the most common subepidermal autoimmune bullous disease, are hallmarked by the production of autoantibodies directed against the hemidesmosomal anchoring proteins BP180 and BP230. In contrast to the robustness of the latter assumption, the multifaceted complexity of upstream and downstream mechanisms implied in the pathogenesis of BP remains an area of intense speculation. So far, an imbalance between T regulatory cells and autoreactive T helper (Th) cells has been regarded as the main pathogenic factor triggering the autoimmune response in BP patients. However, the contributory role of signaling pathways fostering the B cell stimulation, such as Toll-like receptor activation, as well as that of ancillary inflammatory mechanisms responsible for blister formation, such as Th17 axis stimulation and the activation of the coagulation cascade, are still a matter of debate. In the same way, the pathomechanisms implied in the loss of dermal-epidermal adhesion secondary to autoantibodies binding are not fully understood. Herein, we review in detail the current concepts and controversies on the complex pathogenesis of BP, shedding light on the most recent theories emerging from the literature