Optimization of Leak Detectors’ Positioning in a Hydrogen Refueling Station

Hydrogen has the potential to promote sustainable road transport in the forthcoming years, thus significantly reducing the human impact on the environment. This energy carrier can be produced by renewable energy through water electrolysis and used in fuel cell-powered vehicles (FCVs) with elevated efficiency and no pollutant emissions. The number of FCVs being used around the world is rapidly increasing, reaching 34,804 vehicles and 540 refueling stations by the end of 2020. Nevertheless, hydrogen is highly flammable and can permeate and embrittle most metallic materials, making its containment extremely challenging. A leak in a hydrogen refueling station can rapidly escalate to a major disaster if not promptly detected and addressed. In this perspective, gas sensors play a critical role in detecting leakages and undesired hydrogen releases. When selecting a hydrogen gas detector, it is important to consider the environmental conditions in which it is expected to operate, its performance, reliability, and cost, as well as the optimal positioning within the refueling station. This study analyzes several hydrogen releases from a high-pressure storage tank to optimize sensor positioning, given a certain detection probability. This research contributes towards advancing the modelling of safety barriers in hydrogen refueling stations considering accident scenarios. In this vein, this study aims at expanding the current knowledge of facility operators and stakeholders for related risks, thus enabling the widespread utilization of hydrogen in road transport

Lessons learned from HIAD 2.0. Inspection and maintenance to avoid hydrogen-induced material failures

Hydrogen has the potential to make countries energetically self-sufficient and independent in the long term. Nevertheless, its extreme combustion properties and its capability of permeating and embrittling most metallic materials produce significant safety concerns. The Hydrogen Incidents and Accidents Database 2.0 (HIAD 2.0) is a public repository that collects data on hydrogen-related undesired events mainly occurred in chemical and process industry. This study conducts an analysis of the HIAD 2.0 database, mining information systematically through a computer science approach known as Business Analytics. Moreover, several hydrogen-induced material failures are investigated to understand their root causes. As a result, a deficiency in planning effective inspection and maintenance activities is highlighted as the common cause of the most severe accidents. The lessons learned from HIAD 2.0 could help to promote a safety culture, to improve the abnormal and normal events management and to stimulate a widespread rollout of hydrogen technologies

Safety Evaluation of Hydrogen Pipeline Transport: an Approach Based on Machine Learning

The issue of global warming imposes a change of paradigm in the energy sector to mitigate the human impact on the environment. In this perspective, hydrogen can be produced through water electrolysis and used in fuel-cell systems with near-zero pollutant emissions. Nevertheless, the distribution system represents one of the main bottlenecks for a future transition to a hydrogen economy. The possibility of transporting hydrogen through the existing pipeline network is economically attractive. Nevertheless, most pipeline steels are prone to hydrogen-induced damage, and their mechanical properties are degraded by hydrogen gas to an extent that could result in sudden component failures. Hydrogen embrittlement can be responsible for undesired releases with potentially catastrophic consequences. This study evaluates the safety of existing European natural gas pipelines for hydrogen transport through machine learning tools. The material susceptibility to hydrogen embrittlement is predicted under different working conditions in order to prevent loss of material integrity and eventual releases. This study aims at bridging the gap between safety and material science, as it can optimize predictive maintenance of hydrogen pipelines, thus promoting the widespread utilization of hydrogen in the forthcoming years

A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement

Hydrogen is widely considered a promising energy carrier capable of mitigating human environmental impact. Nevertheless, safety aspects represent one of the major bottlenecks for the widespread utilization of hydrogen technologies. Industrial equipment operating in hydrogen environments is prone to hydrogen-induced damages, which may manifest through a reduction of mechanical properties, fracture toughness, and fatigue performance. They may cause component failures at stress levels significantly below the design level, therefore determining loss of containment. The occurrence of hydrogen embrittlement (HE) relies on the synergy of several factors, such as hydrogen concentration, operating conditions, level of internal and applied stress, microstructure and chemical composition of the material. However, the interlinked dependence of these factors makes a direct and clear evaluation challenging, subsequently creating serious difficulties in planning inspection and maintenance activities. In this study, a comprehensive review of the experimental data of tensile tests carried out in hydrogen was performed and analyzed through an advanced machine learning approach. This study can provide critical insights into the susceptibility to hydrogen embrittlement for several materials operating under different environmental conditions. In particular, the Embrittlement Index was estimated and used as determining parameter to predict the likelihood of component failures. The model demonstrated accurate and reliable predicting capabilities. The outcome of this study can increase the understanding of hydrogen-induced material damages and facilitate decision-making processes in planning the inspection and maintenance of hydrogen technologies

The impact of chest CT body composition parameters on clinical outcomes in COVID-19 patients

We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality.We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/ 27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality

Design and optimization of an emergency system for cryogenic fuels

The use of light hydrocarbons is desirable in order to mitigate the human impact on the environment. Besides, this strategy is a forerunner solution for the implementation of a hydrogen economy in the long term. Cryogenic conditions represent an attractive option to make the use of these fuels more sustainable. Since the bottleneck for their large-scale adoption is represented by safety aspects, an emergency auto-thermal burner was designed. This safety system has the purpose to dispose of the content of a tank truck, in order to avoid the loss of containment and the accidental release of LNG or LH2. The disposal of the fuel includes its vaporization, the heating of the vapor phase up to a temperature suitable for combustion, the mixing with ambient air, and the combustion. The most important technical requirements are the duration of the discharge process and the portability of this device. The temperature of flue gases was estimated through numerical methods. Then, inner and outer heat transfer coefficients were determined for each coiled-tube heat exchanger, and their surface was calculated, solving the equation of energy balance along the pipe. Finally, the nozzle was designed in order to slow down the gaseous fuel slightly upstream of the burner. Two variants are proposed for the emergency burner for LNG: one with separate reboiler and another with evaporation in tube. While the former option is suitable for stationary applications, the latter is easy to transport, assemble, and put into operation, since it is lightweight and does not require any heat transfer fluid. The emergency burner for LH2 was designed with evaporation in tube only. The para-to-ortho conversion was considered since it results from the increase in hydrogen temperature. The enthalpy of this endothermic reaction represents an additional energy request. If the decrease of para-hydrogen fraction along the pipe was neglected, the length of the superheater would be significantly underestimated

An Extensive Review of Liquid Hydrogen in Transportation with Focus on the Maritime Sector

The European Green Deal aims to transform the EU into a modern, resource-efficient, and competitive economy. The REPowerEU plan launched in May 2022 as part of the Green Deal reveals the willingness of several countries to become energy independent and tackle the climate crisis. Therefore, the decarbonization of different sectors such as maritime shipping is crucial and may be achieved through sustainable energy. Hydrogen is potentially clean and renewable and might be chosen as fuel to power ships and boats. Hydrogen technologies (e.g., fuel cells for propulsion) have already been implemented on board ships in the last 20 years, mainly during demonstration projects. Pressurized tanks filled with gaseous hydrogen were installed on most of these vessels. However, this type of storage would require enormous volumes for large long-range ships with high energy demands. One of the best options is to store this fuel in the cryogenic liquid phase. This paper initially introduces the hydrogen color codes and the carbon footprints of the different production techniques to effectively estimate the environmental impact when employing hydrogen technologies in any application. Afterward, a review of the implementation of liquid hydrogen (LH2) in the transportation sector including aerospace and aviation industries, automotive, and railways is provided. Then, the focus is placed on the maritime sector. The aim is to highlight the challenges for the adoption of LH2 technologies on board ships. Different aspects were investigated in this study, from LH2 bunkering, onboard utilization, regulations, codes and standards, and safety. Finally, this study offers a broad overview of the bottlenecks that might hamper the adoption of LH2 technologies in the maritime sector and discusses potential solutions

An Extensive Review of Liquid Hydrogen in Transportation with Focus on the Maritime Sector

The European Green Deal aims to transform the EU into a modern, resource-efficient, and competitive economy. The REPowerEU plan launched in May 2022 as part of the Green Deal reveals the willingness of several countries to become energy independent and tackle the climate crisis. Therefore, the decarbonization of different sectors such as maritime shipping is crucial and may be achieved through sustainable energy. Hydrogen is potentially clean and renewable and might be chosen as fuel to power ships and boats. Hydrogen technologies (e.g., fuel cells for propulsion) have already been implemented on board ships in the last 20 years, mainly during demonstration projects. Pressurized tanks filled with gaseous hydrogen were installed on most of these vessels. However, this type of storage would require enormous volumes for large long-range ships with high energy demands. One of the best options is to store this fuel in the cryogenic liquid phase. This paper initially introduces the hydrogen color codes and the carbon footprints of the different production techniques to effectively estimate the environmental impact when employing hydrogen technologies in any application. Afterward, a review of the implementation of liquid hydrogen (LH2) in the transportation sector including aerospace and aviation industries, automotive, and railways is provided. Then, the focus is placed on the maritime sector. The aim is to highlight the challenges for the adoption of LH2 technologies on board ships. Different aspects were investigated in this study, from LH2 bunkering, onboard utilization, regulations, codes and standards, and safety. Finally, this study offers a broad overview of the bottlenecks that might hamper the adoption of LH2 technologies in the maritime sector and discusses potential solutions

Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions

Neuro-Symbolic (NeSy) integration combines symbolic reasoning with Neural Networks (NNs) for tasks requiring perception and reasoning. Most NeSy systems rely on continuous relaxation of logical knowledge and no discrete decisions are made within the model pipeline. Furthermore, these methods assume that the symbolic rules are given. In this paper, we propose Deep Symbolic Learning (DSL), a NeSy system that learns NeSy-functions, i.e., the composition of a (set of) perception functions which map continuous data to discrete symbols, and a symbolic function over the set of symbols. DSL learns simultaneously the perception and symbolic functions, while being trained only on their composition (NeSy-function). The key novelty of DSL is that it can create internal (interpretable) symbolic representations and map them to perception inputs within a differentiable NN learning pipeline. The created symbols are automatically selected to generate symbolic functions that best explain the data. We provide experimental analysis to substantiate the efficacy of DSL in simultaneously learning perception and symbolic functions

Laparoscopic removal of intragastric trichobezoar in a child: A case report

Introduction: A trichobezoar is a mass of indigestible hair in the gastrointestinal tract caused by hair ingestion, usually associated with trichotillomania and trichophagia. Although sometimes asymptomatic, it can become a rare cause of intestinal obstruction and require an emergent surgical intervention. The operative approach of choice, laparotomy versus laparoscopy, is still controversial. Case presentation: A 11-year-old girl was admitted to our institution with abdominal pain, vomiting and anorexia for 3 days. On abdominal examination, she had diffused abdominal pain with tenderness in the mesogastrium, with no palpable mass. Abdominal computed tomography (CT) scan and barium meal study shown a large gastric mass. Upper gastrointestinal (GI) endoscopy identified an enormous trichobezoar, which was later removed laparoscopically. An anterior gastrotomy was performed and the bezoar was then transferred en bloc into the endo-bag. The neck of the endobag was then exteriorized through the umbilical incision and removed by gradual fragmentation. The volume and size of the phytobezoars were 1875 cm3 and 25 × 15 × 5 cm. The patient was discharged on the 5th postoperative day without any complications. Conclusion: Successful laparoscopic management of pediatric trichobezoar may be accomplished by a 4-ports approach. It allows a lower intraoperative risk of contaminations, a rapid recovery and good cosmetic results in children