BrainMap

Mr. LAURENTIU ASIMOPOLOS

Senior Researcher, PhD & M.Sc Geophysicist, M.Sc Mathematician

Senior Researcher - INSTITUTUL GEOLOGIC AL ROMANIEI

Other affiliations

Senior Researcher - INSTITUTUL DE GEODINAMICA (Romania)

ENG. Head of Team (Geoelectrical Methods) - PROSPECTIUNI S.A. (Romania)

Researcher | Scientific reviewer

Dr. Asimopolos Laurentiu graduated from the University of Bucharest, Faculty of Geology and Geography, Department of Geophysics in 1984, Faculty of Mathematics and Informatics, Department of Mathematics in 1996 and received his PhD in Geology in 2003. He is a researcher scientific within Magnetism and electromagnetism in the Surlari National Geomagnetic Observatory. His main scientific expertise is in Data Analysis, Data Processing, Interpretation and Modeling of the Earth's Electromagnetic Field, Numerical Analysis Methods and Software in Geophysics. In addition, he contributed to the complex analysis of geophysical signals by statistical-spectral-wavelet methods and by machine learning and deep learning algorithms. The last two completed projects that I led were: Creation of 3D geological/geophysical models for the characterization of some areas of economic and scientific interest in Romania, with Contract no. 49N/2019 and Capacities and institutional services for research, monitori

Web of Science ResearcherID: not public

Curriculum Vitae (21/03/2023)

Expertise & keywords

Artificial Intelligence and Combined Survey Techniques for Stone Quarries Optimization Call name: P 3 - SP 3.2 - Proiecte ERA.NET - COFUND
COFUND-ERAMIN-3-AI-COSTSQO-2 2022 - 2024

Role in this project:

Coordinating institution: INSTITUTUL GEOLOGIC AL ROMANIEI

Project partners: INSTITUTUL GEOLOGIC AL ROMANIEI (RO); BAY E Bilişim Danışmanlık Eğitim Bilgisayar Sanayi ve Ticaret Limited Şirketi (TR); Faculty of Information Studies in Novo mesto Complex systems and Data Science Lab (SI); UNIBO - University of Bologna DICAM - DEPARTMENT OF CIVIL, CHEMICAL, ENVIRONMENTAL AND MATERIALS ENGINEERING (IT)

Affiliation:

Project website: https://www.ai-costsqo.igr.ro/

Abstract:

ABSTRACT

Stone blocks, such as marble, granite, and sandstone, are natural materials with excellent properties. Their market is currently worth 30 billion EUR, and is increasing day by day, since they are in high demand in a variety of industries. However, their exploitation in quarries is conditioned by two unfavourable factors. First, these ores have naturally occurred fractures and discontinuities, such faults, joints, and fissures, which preclude the excavation of larger blocks with bigger commercial value. Second, stone quarrying is a very intensive waste-producing process, since not all excavated material is of commercial use. With booming markets, risks to the environment are only bound to become more serious. Here, we propose the project to ameliorate the above situation. We will combine geophysical and photogrammetric survey methods to populate a database with all-encompassing inventory of major European quarrying sites. These in-situ, non-invasive measurements will include the Unmanned Aerial Vehicles equipped with Light Detection and Ranging sensors, Ground Penetrating Radar, Borehole Digital Imaging, and Integrated data Processing of the Point Cloud. They will be used to detect the discontinuity surfaces in the natural stone and formulate a polygonal model. Next, the polygonal model will be examined via an innovative Artificial Intelligence approach. The identification of the discontinuity sets will be improved by the actual “visual” manually operated procedure. With help of Deep Learning algorithms this will lead to a higher degree of automation. The derived Discrete Fracture Network will be considered as input for the polyhedron extraction methodology and computational optimization. These innovative algorithms consist of the combined use of several parameters like maximum cuboids volume, the surface of slabs, the orientation of the cutting grid in quarries, and commercially relevant parameters. In turn, this will enable the framework for automated design and optimization of mining plans, tailored to specific mine and stone properties, maximizing the size of the extracted stone blocks. This will increase the efficiency of raw materials supply while creating environment friendly and sustainable modus of exploitation. In addition, this should reduce the waste production, while consuming less energy and water. The developed model will be validated for each quarry site and will be applied to the existing quarries. The most important impact of this undertaking will be recovering up to 25% of waste. Completion of this project amounts to a considerable technological improvement in mining of natural resources and reduction of environmental risks, thereby boosting the competitiveness of Europe.

PUBLISHABLE ABSTRACT

AI-COSTSQO partners come together to create an eco-efficient and sustainable stone exploitation by using non-invasive survey, optimize production, reducing waste, energy and water usage. Thus, the degree of negative social effects of mining activities, which have increased in recent years, will also be reduced. The interest area of the project will cover both currently operating mines and non-operating deposits. With the project work, an effort will be made to evaluate the current situation, to predict the financial profitability of virgin deposits and the amount of waste to be produced. The project, which has an interdisciplinary character, consists of academic people who are experts in their fields. These people have a lot of projects and academic studies related to the subject, and they are completely locking at the target. The operability of the stone deposit as a rock mass is mostly assessed by the presence of discontinuities. Our project will be primarily the basis on the modelling of the existence of these using Analytical, Mathematical, Statistical, Machine Learning and Big Data solutions. In addition, realistic survey methods will be used as mainly data. The innovative model will be created combining several approaches, like calculating the maximum cuboid volumes that fit into natural polyhedrons and the orientation of the cutting grid, considering discontinuities and planning to cut directions and spatial position of general planning of quarry using block dimension distributions. In this concept, six work packages have been designed and distributed to the partners according to their specialisation. Although there is no exact data for natural stone quarries recovery rates, it is well known these rates may be decreased to about 10% in many quarries. We believe that the project outcomes, combined innovative survey methods and new optimization algorithms, will significantly improve the recovery rates and decrease waste production in stone quarries.

INSTITUTIONAL CAPABILITIES AND SERVICES FOR RESEARCH, SURVEILANCE AND FORECASTING OF RISKS FROM EXTRA-ATMOSPHERIC SPACE Call name: P 1 - SP 1.2 - Proiecte complexe realizate in consorții CDI
PN-III-P1-1.2-PCCDI-2017-0266 2018 - 2021

Role in this project:

Coordinating institution: AGENTIA SPATIALA ROMANA

Project partners: AGENTIA SPATIALA ROMANA (RO); INSTITUTUL NATIONAL DE CERCETARE - DEZVOLTARE IN INFORMATICA - ICI BUCURESTI (RO); INSTITUTUL ASTRONOMIC (RO); ACADEMIA ROMANA FILIALA CLUJ (RO); INSTITUTUL DE STIINTE SPATIALE-FILIALA INFLPR (RO); INSTITUTUL GEOLOGIC AL ROMANIEI (RO); INSTITUTUL NATIONAL DE CERCETARE-DEZVOLTARE PENTRU FIZICA PAMANTULUI - INCDFP RA (RO); INSTITUTUL DE GEODINAMICA (RO)

Affiliation: INSTITUTUL GEOLOGIC AL ROMANIEI (RO)

Project website: http://safespace.rosa.ro

Abstract:

The project aims to develop competences and research capabilities in the field of space situational awareness. Knowledge of Space Situational Awareness (SSA) refers to the ability to assess the risks associated with extra-atmospheric space, that can be subjected to the biological environment, material assets and critical infrastructure.

As a member of ESA, Romania has been participating in the "Space Situational Awareness" Program since 2012 and from 2013 onwards in the European Commission's work on the establishment of the Support Framework for Space Surveillance and Tracking.

In Romania there is experience and achievements in the field of SSA, however, research, monitoring and forecasting of the situation in the extra-atmospheric space must be sustained, developed and materialized internally through specific services and products. At present, information and predictions about possible hazards that may come from space are incomplete or restricted, being taken from sources of interest that predict impacts on very extensive geographic areas, and their customization in national territory is only made for certain extreme cases, and in the majority of situations, effects being already in progress.

The development of national research, monitoring and forecasting capacities in the area of spatial knowledge knowledge aims at qualitatively and quantitatively stimulating the space research potential in Romania and strengthening its connections with European initiatives and the international scientific community. The SAFESPACE project will have a relevant international visibility, contributing to ensuring the long-term availability of national space infrastructure interdependent with the European one, facilities and services essential to the safety and security of the economy, society and citizens in Romania and in Europe.

Real-Time Mineral X-Ray analysis for efficient and sustainable mining (H2020 project) Call name:
730270 — X-MINE — H2020-SC5-2016-2017/H2020-SC5-2016 -

Role in this project: Key expert

Coordinating institution: Teknologian tutkimuskeskus VTT Oy (VTT)

Project partners:

Affiliation:

Project website: http://www.xmine.eu

Abstract:

The X-MINE project supports better resource characterisation and estimation as well as more efficient ore extraction in existing mine operations, making the mining of smaller and complex deposits economically feasible and increasing potential European mineral resources (specifically in the context of critical raw materials) without generating adverse environmental impact.

The project will implement large-scale demonstrators of novel sensing technologies improving the efficiency and sustainability of mining operations based on X-Ray Fluorescence (XRF), X-Ray Transmission (XRT) technologies, 3D vision and their integration with mineral sorting equipment and mine planning software systems.

The project will deploy these technologies in 4 existing mining operations in Sweden, Greece, Bulgaria and Cyprus. The sites have been chosen to illustrate different sizes (from small-scale to large-scale) and different target minerals (zinc-lead-silver-gold, copper-gold, gold) including the presence of associated critical metals such as indium, gallium, germanium, platinum group metals and rare earth elements. The pilots will be evaluated in the context of scientific, technical, socio-economic, lifecycle, health and safety performances.

The sensing technologies developed in the project will improve exploration and extraction efficiency, resulting in less blasting required for mining. The technologies will also enable more efficient and automated mineral-selectivity at extraction stage, improving ore pre-concentration options and resulting in lower use of energy, water, chemicals and men hours (i.e. worker exposure) during downstream processing.

FILE DESCRIPTION	DOCUMENT
List of research grants as project coordinator or partner team leader
Significant R&D projects for enterprises, as project manager
R&D activities in enterprises
Peer-review activity for international programs/projects	Download (70.16 kb) 14/10/2019