Consequence assessment of anhydrous ammonia release using CFD‐probit analysis

Namboothiri, Nandu V.; Soman, A.R.

doi:10.1002/prs.11970

Cited by 13 publications

(6 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this study, Probit model was used to predict the individual death probabilities caused by toxic, overpressure, and thermal radiation. The general form of the Probit model is shown as follows 34 :

P_{e} goodbreak= normala goodbreak+ b \ln ((), V)

P goodbreak= \frac{1}{2} ([], 1 goodbreak+ italicerf ((), \frac{P_{e} - 5}{\sqrt{2}}))

italicerf ((), x) goodbreak= \frac{2}{\sqrt{π}} \int_{0}^{x} e^{- t^{2}} italicdt

where

P_{e}

is Probit value; a and b are constants, which depend on the type of damage; V is the amount of damage received; P is the individual death probabilities; and erf(x) is error function.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Risk assessment of liquid ammonia tanks based on Bayesian network and Probit model

Zhang,

Wang,

Chen

et al. 2023

Process Safety Progress

View full text Add to dashboard Cite

This paper presents a quantitative risk assessment method to predict the potential risks of liquid ammonia tanks. The method combines probabilistic prediction and consequence assessment: the former is predicted by Bayesian networks derived from bow‐tie mapping, in which the conditional probabilities are determined by analytic hierarchy process, the latter is calculated based on numerical simulation of accident consequences and Probit probability model. The application results show that the method can be used for quantitative risk assessment of liquid ammonia storage tank, and the Bayesian network model is efficient and stable, which can realize risk prediction, accident causes analysis and risk mitigation analysis. Human errors during production or maintenance and corrosion are the main causes of liquid ammonia leakage. Toxicity has the greatest effect on the risk of liquid ammonia tanks. Risk mitigation measures can significantly reduce individual risk and societal risk. The obtained results provide meaningful guidance for the prevention and risk mitigation strategies of liquid ammonia leakage accidents, so as to improve the safety level of liquid ammonia during storage.

show abstract

P_{e} goodbreak= normala goodbreak+ b \ln ((), V)

P goodbreak= \frac{1}{2} ([], 1 goodbreak+ italicerf ((), \frac{P_{e} - 5}{\sqrt{2}}))

italicerf ((), x) goodbreak= \frac{2}{\sqrt{π}} \int_{0}^{x} e^{- t^{2}} italicdt

where

P_{e}

is Probit value; a and b are constants, which depend on the type of damage; V is the amount of damage received; P is the individual death probabilities; and erf(x) is error function.…”

Section: Methodsmentioning

confidence: 99%

Section: Probit Vulnerability Modelmentioning

confidence: 99%

Risk assessment of liquid ammonia tanks based on Bayesian network and Probit model

Zhang,

Wang,

Chen

et al. 2023

Process Safety Progress

View full text Add to dashboard Cite

show abstract

“…Human life is considered as the top priority among the various factors; thus, human life is taken as an indicator of the severity of consequence. The probit analysis methodology is used to analyze the impact on people because of hazardous chemical or energy release 39 . The relation between the probability of human death

P_{d}

and the corresponding probit function

P_{r}

is expressed by Equations () and () 32 :

P_{d} goodbreak= 0.5 goodbreak\times ([], 1 goodbreak+ italicerf ((), \frac{P_{r} - 5}{\sqrt{2}})),

where

italicerf ((), x) goodbreak= \frac{2}{\sqrt{π}} \int_{0}^{x} e^{- t^{2}} italicdt,

where

\erf ((), x)

is the Gaussian error function.…”

Section: Methodsmentioning

confidence: 99%

“…The probit analysis methodology is used to analyze the impact on people because of hazardous chemical or energy release. 39 The relation between the probability of human death P d and the corresponding probit function P r is expressed by Equations ( 3) and (4) 32 :…”

Section: Severity Of Consequencesmentioning

confidence: 99%

Quantitative risk assessment for ammonia ship‐to‐ship bunkering based on Bayesian network

Fan

Enshaei

Jayasinghe

et al. 2021

Process Safety Progress

View full text Add to dashboard Cite

The maritime industry is getting prepared for using ammonia as a fuel to meet the decarbonization goal. However, ammonia is toxic, corrosive, and flammable, which poses specific safety challenges during bunkering compared with conventional fuels.The corrosion can be prevented by selecting suitable materials. However, the impact of toxic gas dispersion and fire has high uncertainties, thus risk assessment should be conducted. Currently, there are insufficient risk assessment guidelines for ammonia bunkering available. Therefore, this paper proposes a Bayesian network (BN) based quantitative risk assessment framework to investigate the potential risks of ammonia in ship-to-ship bunkering considering the toxicity and flammability. The study validates the utility of the proposed framework and demonstrates the BN as an efficient model in performing the probabilities calculations and flexible in conducting causal diagnosis. The results show that toxicity has the greatest impact on the risks of ammonia bunkering compared with flammability. The main innovation of this work is realizing the efficient quantification of risks for ammonia ship-to-ship bunkering by using the BN.

show abstract

“…Pulmonary edema, laryngiris, tracheobronchitis, brochiolitis, bronchopneumonia adalah beberapa kasus yang terjadi akibat menghirup amonia secara akut 14 , kulit terbakar, sampai pada kebutaan dan kematian 15 . Ammonia yang digunakan sebagai bahan baku industry X, umumnya disimpan dalam volume yang sangat besar sehingga risiko pelepasan bahan kimia akibat kesalah manusia, kurangnya pelatihan, pengawasan dan inspeksi juga meningkat 13 .…”

Section: Pendahuluanunclassified

Analisis Kesiapsiagaan Bencana Teknologi dari Pabrik X pada Aspek Proyeksi Zona Bahaya

Novrikasari

Lestari

Sudiman

et al. 2022

Jurnal Kesehatan Lingkungan Indonesia

View full text Add to dashboard Cite

Latar belakang: Kegagalan teknologi dalam industri X tidak dapat dihindari terutama karena keadaan pabrik X dengan teknologi tua dan bahan kimia sebagai bahan baku produksi yang dapat menimbulkan berbagai bahaya seperti polusi industri hingga kebakaran sehingga diperlukan manajemen bencana teknologi yang strategis. Penelitian ini bertujuan untuk melakukan analisis kesiapsiagaan bencana teknologi dari pabrik X pada aspek proyeksi zona bahaya.Metode: Penelitian survei dengan rancangan cross-sectional. Sampel penelitian adalah 548 masyarakat yang termasuk dalam area risiko 0-2600 meter dari tangki penyimpanan amonia di sekitar pabrik X yang telah memenuhi kriteria inklusi dan eksklusi penelitian. Data sekunder dari Badan Meteorologi Klimatologi dan Geofisika Stasiun Meteorologi Sultan Mahmud Badaruddin II untuk data meteorologi periode Januari – Desember digunakan untuk proyeksi zona bahaya. Analisis data menggunakan ALOHA (Areal Locations of Hazardous Atmospheres) yang di plot ke Google Earth dan Peta Administrasi Kota Palembang.Hasil: Hasil penelitian disajikan dalam distribusi frekuensi dan proyeksi zona bahaya disajikan dalam gambar yang sudah dipetakan dengan Google Earth. Analisis konsekuensi dari 4 skenario kasus terburuk ketika terjadi rupture tangki amonia, menjelaskan bahwa area risiko rupture di bawah tangki (skenario 2) 3 kali lebih luas dibanding rupture di atas tangki (skenario 1) untuk ukuran lubang diameter 1 cm. Area risiko heavy gas (skenario 4) 2 kali lebih luas dibanding dengan hasil prediksi model gaussian (skenario 3).Simpulan: Penyusunan manajemen evakuasi berdasarkan hasil proyeksi zona bahaya dan upaya pelatihan tanggap darurat yang lebih luas akan meningkatkan tingkat kesiapsiagaan masyarakat dan manajemen bencana. ABSTRACT Title: Analysis of Technological Disaster Preparedness from Fertilizer Factory on Hazard Zone Projection AspectBackground: Technological failure in the fertilizer industry is unavoidable mainly because of the state of the fertilizer factory with old technology and hazardous chemicals as production raw materials, so strategic technological disaster management is needed. This study aims to describe public knowledge regarding the dangers of ammonia gas dispersion and the preparation of hazard zone projections as an important input in disaster management of the technology.Method: Survey research with cross-sectional design. The research sample was 548 people who had met the inclusion and exclusion criteria of the study. Secondary data from the Meteorology, Climatology and Geophysics Agency of the Sultan Mahmud Badaruddin II Meteorological Station for meteorological data for the January – December period is used for hazard zone projections.Result: Research results are presented in frequency distribution and hazard zone projections are presented in images that have been mapped with Google Earth. Consequence analysis of the 4 worst case scenarios when an ammonia tank ruptures, explains that the risk area for rupture under the tank (scenario 2) is 3 times larger than that of rupture above the tank (scenario 1) for a hole size of 1 cm diameter. The risk area for heavy gas (scenario 4) is 2 times wider than the predicted result of the gaussian model (scenario 3).Conclusion: Preparation of evacuation management based on the results of hazard zone projections and wider emergency response training efforts will increase the level of community preparedness and disaster management

show abstract

Consequence assessment of anhydrous ammonia release using CFD‐probit analysis

Cited by 13 publications

References 29 publications

Risk assessment of liquid ammonia tanks based on Bayesian network and Probit model

Risk assessment of liquid ammonia tanks based on Bayesian network and Probit model

Quantitative risk assessment for ammonia ship‐to‐ship bunkering based on Bayesian network

Analisis Kesiapsiagaan Bencana Teknologi dari Pabrik X pada Aspek Proyeksi Zona Bahaya

Contact Info

Product

Resources

About