Predicting chattering alarms: A machine Learning approach

Abstract Alarm floods represent a widespread issue for modern chemical plants. During these conditions, the number of alarms may be unmanageable, and the operator may miss safety-critical alarms. Chattering alarms, which repeatedly change between the active and non-active states, are responsible for most of the alarm records within a flood episode. Typically, chattering alarms are only addressed and removed retrospectively (e.g. during periodic performance assessments). This study proposes a Machine-Learning based approach for alarm chattering prediction. Specifically, a method for dynamic chattering quantification has been developed, whose results have been used to train three different Machine Learning models – Linear, Deep, and Wide&Deep models. The algorithms have been employed to predict future chattering behavior based on actual plant conditions. Performance metrics have been calculated to assess the correctness of predictions and to compare the performance of the three models

Learning from Major Accidents: a Machine Learning Approach

A B S T R A C T Learning from past mistakes is crucial to prevent the reoccurrence of accidents involving dangerous sub-stances. Nevertheless, historical accident data are rarely used by the industry, and their full potential is largely unexpressed. In this setting, this study set out to take advantage of improvements in data sci-ence and Machine Learning to exploit accident data and build a predictive model for severity prediction. The proposed method makes use of classification algorithms to map the features of an accident to the corresponding severity category (i.e., the number of people that are killed and injured). Data extracted from existing databases is used to train the model. The method has been applied to a case study, where three classification models - i.e., Wide, Deep Neural Network, and Wide&Deep - have been trained and evaluated on the Major Hazard Incident Data Service database (MHIDAS). The results indicate that the Wide&Deep model offers the best performance.(c) 2022 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/

identification of hazards and environmental impact assessment for an integrated approach to emerging risks of co2 capture installations

Abstract New and intensified technologies are being defined within the field of Carbon Capture and Sequestration (CCS) and the uptake is set to increase dramatically. This contribution focuses on three representative installations for CCS capture, whose safety and environmental issues might potentially be underestimated based on their presence in other industrial fields, but with different scales and uses. A simplified Life Cycle Assessment (LCA) and the new hazard identification technique denominated DyPASI (Dynamic Procedure for Atypical Scenarios Identification) were used to identify respectively environmental impact and atypical accident scenarios and add a useful dimension to risk information that can particularly help in determining the best technological options

Assessment of Safety Barrier Performance in Environmentally Critical Facilities: Bridging Conventional Risk Assessment Techniques with Data-Driven Modelling

The failure of emission control systems in industrial processes undergoing emission regulations can cause severe harm to the environment. In this context, safety engineering principles can be applied to analyze process deviations and identify suitable safety barriers to mitigate harmful emissions during critical events. However, the selection, design, and assessment of proper safety barriers may be complex due to several contingencies such as the inability to perform extensive field tests on systems under strict emission regulations. In this study, an approach is proposed to couple conventional hazard identification techniques with a digital model of a flue gas treatment system to support the identification and performance assessment of safety barriers for emission control. Resilience analysis is used to evaluate the behavior of the most relevant safety barrier options, selected through a screening with conventional hazard identification tools. Barriers are simulated using the digital model of the system, gathering key information for their design and evaluation, and overcoming the limitations to field tests at the real plant. The methodology is illustrated with reference to acid gas removal in waste-to-energy facilities, a relevant example of an emission control system that is typically exposed to significant process deviations

Cryogenic Hydrogen Storage Tanks Exposed to Fires: a CFD study

Hydrogen is one of the most suitable candidates in replacing heavy hydrocarbons. Liquefaction of fuels is one of the most effective processes to increase their low density. This is critical especially in large-scale or mobile applications such as in the maritime or aeronautical fields. A potential loss of integrity of the cryogenic storage equipment might lead to severe consequences due to the properties of these substances (e.g. high flammability). For this reason, this critical event must be avoided. The aim of this study is to analyse the behaviour of the cryogenic vessel and its lading when it is exposed to a fire and understand how to prevent a catastrophic rupture of the tank during this accident scenario. A two-dimensional computational fluid dynamic (CFD) analysis is carried out on a cryogenic liquid hydrogen (LH2) vessel to investigate its thermal response when engulfed in a fire. The model accounts for the evaporation and condensation of the substance and can predict the tank pressurization rate and temperature distribution. It is assumed that the vessel is completely engulfed in the fire (worst-case scenario). The CFD model is validated with the outcomes of a small-scale fire test of an LH2 tank. Critical indications on the dynamic response of the cryogenic tank involved in a worst-case accident scenario are provided. Tank pressurisation and temperature distributions of the case study can be exploited to provide conservative estimations of the time to failure (TTF) of the vessel. These outcomes represent useful information to support the emergency response to this type of accident scenario and can aid the selection of appropriate and effective safety barriers to prevent the complete destruction of the tank

Birth month and adult lifespan : a within-family, cohort, and spatial examination using FamiLinx data in the United States (1700-1899)

Background: Research has shown that the circumstances surrounding birth may influence the timing of death. In the northern hemisphere, children born in spring and summer have a shorter lifespan than those born in fall and winter. Objective: We describe the effect of month of birth on adult lifespan (50+) in the United States in three ways. First, we estimate it between and within groups of siblings, accounting for unobserved factors at the family level. Second, we estimate the effect of birth month across a period of about 200 years (1700‒1899). Third, we examine geographical variation in the effect of birth month across US census areas. Method: We estimate descriptive statistics and OLS regression models between and within sibling groups.Results: we find an effect of birth month on lifespan. Individuals born in spring and summer have on average a shorter lifespan than those born in fall and winter. The effect is relatively consistent across cohorts, geographical census areas, and between and within families. We test different possible explanations for this result and find residual evidence that in utero debilitation may account for this result

Birth month and adult lifespan: A within-family, cohort, and spatial examination using FamiLinx data in the United States (1700-1899)

Background: Research has shown that the circumstances surrounding birth may influence the timing of death. In the northern hemisphere, children born in spring and summer have a shorter lifespan than those born in fall and winter. Objective: We describe the effect of month of birth on adult lifespan (50+) in the United States in three ways. First, we estimate it between and within groups of siblings, accounting for unobserved factors at the family level. Second, we estimate the effect of birth month across a period of about 200 years (1700‒1899). Third, we examine geographical variation in the effect of birth month across US census areas. Methods: We estimate descriptive statistics and OLS regression models between and within sibling groups. Results: We find an effect of birth month on lifespan. Individuals born in spring and summer have on average a shorter lifespan than those born in fall and winter. The effect is relatively consistent across cohorts, geographical census areas, and between and within families. We test different possible explanations for this result and find residual evidence that in utero debilitation may account for this result. Contribution: Twenty years ago, Gabriele Doblhammer and James W. Vaupel published an influential paper, showing the importance of birth month for lifespan and arguing that circumstances experienced in utero are the likely explanation for this result. We extend these insights by exploiting new crowdsourced data that allows us to study the phenomena over 200 years, across space, and between and within families

European achievements in soil remediation and brownfield redevelopment

With the aim of sharing best practices of soil restoration and management of contaminated sites among European countries and to raise awareness of the enormous efforts made to succeed in such difficult commitment, the experts of the EIONET Soil working group on contaminated sites and brownfields agreed to gather their country's interesting cases and successful stories of recovery of contaminated areas. This second edition of the monograph presents seventeen new cases from eight European countries and its Regions of how polluted sites and brownfields have been remediated like new methodologies of sustainable restoration of the subsoil, development of innovative technologies, and funding mechanisms etc. These stories have been compiled to present what national, regional or local governments are doing to improve the quality of the environment and the living conditions of their population. A second aim is the promotion of best practices among industry, consultancies and business operators.JRC.D.3-Land Resource

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)