Add new publications: HADAD and LNG/LPG design analysis

Author: Daniel Precioso, PhD

_publications/2025-01-01-hadad.md _publications/2025-03-01-hadad.md_publications/2025-01-01-hadad.md renamed to _publications/2025-03-01-hadad.md

@@ -4,14 +4,14 @@ title: "HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather
 collection: publications
 permalink: /publications/2025/hadad/
 excerpt: "HADAD conducts a global exploration using an A* search on a hexagonal grid with higher-order neighbors, then refines the solution using a discrete Newton-Jacobi variational method."
-date: 2025-01-01
+date: 2025-03-01
 venue: "Ocean Engineering"
 paperurl: "https://doi.org/10.1016/j.oceaneng.2024.120050"
 featured_image: "https://weathernavigation.com/images/2025-01-01-hadad.jpg"
 
 ---
 
-### Overview
+### Abstract
 
 We present HADAD (Hexagonal A-Star with Differential Algorithm Designed for weather routing), a novel optimization algorithm for weather routing. HADAD conducts a global exploration using an A* search on a hexagonal grid with higher-order neighbors, enhancing directional flexibility and overcoming limitations of traditional graph searches that constrain vessel movements. It then refines the solution using a discrete Newton-Jacobi variational method, ensuring convergence to a locally optimal, smooth route in continuous space.
 

_publications/2025-10-15-lng-lpg-design.md

@@ -0,0 +1,40 @@
+---
+
+title: "New analysis in the preliminary design for LNG and LPG ships"
+collection: publications
+permalink: /publications/2025/lng-lpg-design/
+excerpt: "This paper presents statistical and machine learning analyses over a large dataset of LNG and LPG ships to improve the accuracy of early-stage vessel design."
+date: 2025-10-15
+venue: "Marine Structures"
+paperurl: "https://doi.org/10.1016/j.marstruc.2025.103863"
+featured_image: "https://danielprecioso.com/images/2025-10-15-marine-structures.jpg"
+
+---
+
+### Abstract
+
+In recent years, the production of LNG and LPG ships has increased, driven by the increasing demand for natural and petroleum gases. To meet this demand, ship designs must be optimized at all stages, requiring designers to have advanced, efficient and accurate design tools. This study presents new statistical and regression analyses of data extracted from the Hyundai Heavy Industries Shipbuilding Group catalogue which includes information on LNG and LPG ships built between 1979 and 2023. The database includes 145 LNG carriers and 322 LPG carriers, representing approximately 20% of the global gas carrier fleet. Simple and multiple regression analyses were used to estimate dependent variables and their correlation to other ship parameters. In addition, Machine Learning algorithms were trained and compared against these traditional methods. This study provides updated tools to support the preliminary design of LNG and LPG ships, enhancing the understanding and accuracy of early-stage design decisions.
+
+[**Download the full paper here**]({{ page.paperurl }})
+
+---
+
+### Authors & Affiliations
+
+- **Mariano Marcos-Pérez**  
+  _Universidad de Cádiz_
+
+- **Javier Jiménez de la Jara**  
+  _Universidad de Cádiz_
+
+- **Daniel Precioso**  
+  _IE University_
+
+- **Aurelio Muñoz**  
+  _Universidad de Cádiz_
+
+- **M. Victoria Redondo-Neble**  
+  _Universidad de Cádiz_
+
+- **David Gómez-Ullate**  
+  _IE University_