DNV GL is an international accredited registrar and classification society headquartered in Høvik, Norway. The company currently has about 14,500 employees and 350 offices operating in more than 100 countries, and provides services for several industries including maritime, renewable energy, oil & gas, electrification, food & beverage and healthcare. It was created in 2013 as a result of a merger between two leading organizations in the field — Det Norske Veritas (Norway) and Germanischer Lloyd (Germany). DNV GL is the world's largest classification society, providing services for 13,175 vessels and mobile offshore units (MOUs) amounting to 265.4 million gt, which represents a global market share of 21%. It is also the largest technical consultancy and supervisory to the global renewable energy (particularly wind, wave, tidal and solar) and oil and gas industry — 65% of the world's offshore pipelines are designed and installed to DNV GL's technical standards. Prior to the merger, both DNV and GL have independently acquired several companies in different sectors, such as Hélimax Energy (Canada), Garrad Hassan (UK), Windtest (Germany) and KEMA (Netherlands), which now contribute to DNV GL's expertise across several industries. In addition to providing services such as technical assessment, certification, risk management and software development, DNV GL also invests heavily in research. Remi Eriksen took over as Group President and CEO of DNV GL on August 1, 2015, succeeding Henrik O. Madsen.
Abstract Modern simulation and analysis tools rely on assumptions and numerical schemes that inevitably affect their outputs, leading to uncertainties and biases that must be quantified and bounded, especially when they influence critical aspects such as system stability. This paper presents recent results from an aeroelastic benchmark on a reference 15-MW wind turbine, conducted by multiple partners within the framework of the International Energy Agency (IEA) Wind TCP Task 47 TURBINIA, focusing on stability characteristics and aeroelastic responses. The agreement among the results is reasonably good, although some quantities exhibit a significant spread. This is particularly evident in the damping factors of the turbine modes and in the periodic loads observed under sheared conditions.
Concern for the collapse behaviour of ships and offshore structures and their structural components under ultimate conditions. Uncertainties in strength assessment shall be highlighted. Attention shall be given to the influence of load combinations, fabrication-induced imperfections, life-cycle effects, damage, and user approach. Consideration shall be given to the practical application of methods.
As modern ships grow larger, monitoring structural integrity becomes increasingly critical, particularly high-frequency hull-girder vibrations that accelerate structural fatigue. Since hull monitoring systems are expensive and difficult to maintain, this research explores using machine learning models based on ship motion sensors for prediction of the vertical bending moment (VBM), analysing in-service data of a 2800 TEU container ship. The tested models include LightGBM, Random Forest, XGBoost, Extra Trees, with LightGBM emerging as the best-performing and fastest framework, reinforcing its status as a state-of-the-art choice for tabular data regression tasks. Two spectral methodologies are developed: a frequency energy densities approach and a statistical-feature approach. Both consistently demonstrated that the optimal input for predicting VBM is a combination of heave, roll, and pitch motions, limited to cutoff frequency of 0.3 Hz for global wave-frequency loads, and bow acceleration, extended to 2.0 Hz to capture high-frequency hull vibrations. The report provides ship operators with a practical, cost-effective alternative to conventional strain measurement systems, predicting key VBM parameters such as the standard deviation and zero-crossing frequency, enabling fatigue analysis, critical for ensuring the structural integrity and operational safety of modern vessels.
Concern for crack initiation and growth under cyclic loading and unstable crack propagation and tearing in the ship and offshore structures. Due attention shall be paid to the suitability and uncertainty of physical models and testing. Consideration is to be given to the practical application, statistical description, and fracture control methods in design, fabrication, and service.
