{"id":28455,"date":"2026-11-04T15:56:24","date_gmt":"2026-11-04T14:56:24","guid":{"rendered":"https:\/\/www.ipresas.com\/?p=28455"},"modified":"2026-11-04T16:18:19","modified_gmt":"2026-11-04T15:18:19","slug":"ipresas-ancold-2026-risk-analysis-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.ipresas.com\/en\/ipresas-ancold-2026-risk-analysis-artificial-intelligence\/","title":{"rendered":"iPresas Shares Its Experience in Risk Analysis and Artificial Intelligence at ANCOLD 2026, Australia"},"content":{"rendered":"\t\t
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Javier Aparici Borr\u00e1s, representing iPresas, participated in the international ANCOLD 2026 conference held in Hobart, Australia, where he delivered two presentations focused on the application of risk analysis and artificial intelligence to dam safety.<\/strong><\/p>

On October 27 and 28, 2026<\/strong>, iPresas attended the annual conference of the Australian National Committee on Large Dams (ANCOLD)<\/em>, an international event that brings together industry professionals and specialists to share knowledge, experiences, and advances in dam safety and management.<\/p>

During the event, Javier Aparici Borr\u00e1s<\/strong> delivered two presentations highlighting international experiences developed by iPresas and technological advances aimed at improving failure mode identification, risk assessment, and decision-making in the management of hydraulic infrastructure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Risk Analysis to Improve Dam Safety<\/h2>\t\t\t\t<\/div>\n\t\t
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On October 27, Javier delivered the presentation \u201cHow Can Risk-Based Approaches Be Used to Improve Dam Safety? Worldwide Examples and Lessons Learned\u201d<\/strong>, focusing on how risk-based approaches contribute to improving dam safety and establishing investment priorities based on technical criteria.<\/p>

The presentation covered experiences from Mozambique, Colombia, Spain, and the tailings dam sector<\/strong>, demonstrating how risk analysis methodologies can be adapted to different contexts, ranging from situations with limited information to the management of large dam portfolios.<\/p>

Key topics included Potential Failure Mode Analysis (PFMA), Semi-Quantitative Risk Analysis (SQRA), and Quantitative Risk Analysis (QRA), as well as their application in evaluating risk reduction alternatives and prioritizing safety measures.<\/p>

The presentation also highlighted Spain’s experience in applying these methodologies to a large portfolio of state-owned dams, emphasizing their integration with management tools such as GARI<\/strong>, which facilitate strategic planning of safety investments and risk-informed decision-making.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Artificial Intelligence Applied to Failure Mode Identification<\/h2>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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On October 28, Javier delivered the presentation \u201cAI-Assisted Failure Mode Identification and Risk Assessment\u201d<\/strong>, exploring the potential of artificial intelligence as a supporting tool in risk assessment processes.<\/p>

The presentation addressed one of the main challenges in dam safety: the comprehensive and systematic identification of potential failure modes<\/strong>, a fundamental step in conducting rigorous risk assessments.<\/p>

Drawing on iPresas’ accumulated experience in analyzing more than 450 dams, 8,000 failure modes, and 30,000 risk drivers<\/strong>, the presentation demonstrated how technical knowledge and structured information can be leveraged to develop artificial intelligence tools capable of supporting failure mode identification, probability and consequence classification, and the recommendation of mitigation measures.<\/p>

The presentation also emphasized the importance of combining these new technological capabilities with the knowledge and experience of specialists, recognizing artificial intelligence as a complementary tool that can improve analytical processes without replacing professional judgment.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\"\"\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Committed to Innovation and Dam Safety<\/h3>\t\t\t\t<\/div>\n\t\t\t\t
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iPresas’ participation in ANCOLD 2026<\/strong> provided an opportunity to share experiences with international professionals, exchange knowledge, and contribute to the development of methodologies and tools that support more efficient and risk-informed dam safety management.<\/p>

At iPresas, we continue to work on the application of advanced risk analysis methodologies, digital tools, and artificial intelligence<\/strong>, aiming to provide solutions that enhance safety, optimize decision-making, and contribute to more sustainable and resilient infrastructure management.<\/p>

We would like to thank ANCOLD for organizing this event and for the opportunity to share our experience with the international dam safety community.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Javier Aparici Borr\u00e1s, representing iPresas, participated in the international ANCOLD 2026 conference held in Hobart, Australia, where he delivered two presentations focused on the application of risk analysis and artificial intelligence to dam safety. On October 27 and 28, 2026, iPresas attended the annual conference of the Australian National Committee on Large Dams (ANCOLD), an […]<\/p>\n","protected":false},"author":3,"featured_media":28443,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-28455","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sin-categorizar"],"yoast_head":"\niPresas at ANCOLD 2026 | Risk Analysis and Artificial Intelligence<\/title>\n<meta name=\"description\" content=\"iPresas participates in ANCOLD 2026 in Australia with two presentations on risk analysis and artificial intelligence applied to dam safety.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ipresas.com\/en\/ipresas-ancold-2026-risk-analysis-artificial-intelligence\/\" 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