A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems

In the reduced order modeling (ROM) framework, the solution of a parametric partial differential equation is approximated by combining the high-fidelity solutions of the problem at hand for several properly chosen configurations. Examples of the ROM application, in the naval field, can be found in [31, 24]. Mandatory ingredient for the ROM methods is the relation between the high-fidelity solutions and the parameters. Dealing with geometrical parameters, especially in the industrial context, this relation may be unknown and not trivial (simulations over hand morphed geometries) or very complex (high number of parameters or many nested morphing techniques). To overcome these scenarios, we propose in this contribution an efficient and complete data-driven framework involving ROM techniques for shape design and optimization, extending the pipeline presented in [7]. By applying the singular value decomposition (SVD) to the points coordinates defining the hull geometry --- assuming the topology is inaltered by the deformation ---, we are able to compute the optimal space which the deformed geometries belong to, hence using the modal coefficients as the new parameters we can reconstruct the parametric formulation of the domain. Finally the output of interest is approximated using the proper orthogonal decomposition with interpolation technique. To conclude, we apply this framework to a naval shape design problem where the bulbous bow is morphed to reduce the total resistance of the ship advancing in calm water

Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing

In the field of parametric partial differential equations, shape optimization represents a challenging problem due to the required computational resources. In this contribution, a data-driven framework involving multiple reduction techniques is proposed to reduce such computational burden. Proper orthogonal decomposition (POD) and active subspace genetic algorithm (ASGA) are applied for a dimensional reduction of the original (high fidelity) model and for an efficient genetic optimization based on active subspace property. The parameterization of the shape is applied directly to the computational mesh, propagating the generic deformation map applied to the surface (of the object to optimize) to the mesh nodes using a radial basis function (RBF) interpolation. Thus, topology and quality of the original mesh are preserved, enabling application of POD-based reduced order modeling techniques, and avoiding the necessity of additional meshing steps. Model order reduction is performed coupling POD and Gaussian process regression (GPR) in a data-driven fashion. The framework is validated on a benchmark ship

PyGeM: Python Geometrical Morphing

PyGeM is an open source Python package which allows to easily parametrize and deform 3D object described by CAD files or 3D meshes. It implements several morphing techniques such as free form deformation, radial basis function interpolation, and inverse distance weighting. Due to its versatility in dealing with different file formats it is particularly suited for researchers and practitioners both in academia and in industry interested in computational engineering simulations and optimization studies

An efficient shape parametrisation by free-form deformation enhanced by active subspace for hull hydrodynamic ship design problems in open source environment

In this contribution, we present the results of the application of a parameter space reduction methodology based on active subspaces to the hull hydrodynamic design problem. Several parametric deformations of an initial hull shape are considered to assess the influence of the shape parameters considered on the hull total drag. The hull resistance is typically computed by means of numerical simulations of the hydrodynamic flow past the ship. Given the high number of parameters involved - which might result in a high number of time consuming hydrodynamic simulations - assessing whether the parameters space can be reduced would lead to considerable computational cost reduction. Thus, the main idea of this work is to employ the active subspaces to identify possible lower dimensional structures in the parameter space, or to verify the parameter distribution in the position of the control points. To this end, a fully automated procedure has been implemented to produce several small shape perturbations of an original hull CAD geometry which are then used to carry out high-fidelity flow simulations and collect data for the active subspaces analysis. To achieve full automation of the open source pipeline described, both the free form deformation methodology employed for the hull perturbations and the solver based on unsteady potential flow theory, with fully nonlinear free surface treatment, are directly interfaced with CAD data structures and operate using IGES vendor-neutral file formats as input files. The computational cost of the fluid dynamic simulations is further reduced through the application of dynamic mode decomposition to reconstruct the steady state total drag value given only few initial snapshots of the simulation. The active subspaces analysis is here applied to the geometry of the DTMB-5415 naval combatant hull, which is which is a common benchmark in ship hydrodynamics simulations

E-commerce and e-procurement: an outsourcing perspective

The make or buy dilemma has been largely analyzed in the field of Information Systems. The main reason for this type of literature thriving so much is that the Information Systems function was one of the first enterprise areas to be externalized. If traditionally only few activities, distant from the core business of the enterprises, have been externalized with the sole objective of gaining efficiency, in the late Nineties externalization of real company functions has started to be considered again, in some instances concerning activities that have always been considered core business. The role played by the management of organizational interdependencies was stressed and the fact that outsourcing was perceived according to solutions of organizational engineering was highlighted, steering enterprises towards new organizational design criteria. In fact, make or buy decisions require more and more that organizational variables be structured by processes and not by functions, precisely to ease the management of organizational interdependencies and make externalization decisions more transparent and objectively measurable. The research question of this paper aims at understanding how much can a particular form of electronic commerce, such as e-procurement, be categorized as a special form of outsourcing, intending this phenomenon as a hybrid organizational form, halfway between hierarchy and market. In order to categorize the outsourcing phenomenon from a theoretical standpoint, the Transaction Cost Theory (TCT) has been used, while the research method consists of a case study. In this paper the attention will be focused on a particular process only, i.e., procurement, in relation to the activities involved in the externalization process. The paper will analyze an outsourcing case applied to the entire macro-process of procurement. The conclusions will highlight the evolving trends in this research field, which appears to be affected by substantial changes and to be increasingly more volatile and influenced by multiple factors that are not always easily recognizable and measurable. The purpose of this paper in fact is to give a contribution to the formalization of an application subject, namely, externalization of procurement, largely diffused in practice although scarcely developed from a theoretical standpoint

SRtP 2.0 \u2014 The Evolution of the Safe Return to Port Concept

In 2010 IMO (International Maritime Organisation) introduced new rules in SOLAS with the aim of intrinsically increase the safety of passenger ships. This requirement is achieved by providing safe areas for passengers and essential services for allowing ship to Safely Return to Port (SRtP). The entry into force of these rules has changed the way to design passenger ships. In this respect big effort in the research has been done by industry to address design issues related to the impact on failure analysis of the complex interactions among systems. Today the research activity is working to bring operational matters in the design stage. This change of research focus was necessary because human factor and the way to operate the ship itself after a casualty on board may have a big impact in the design of the ship/systems. Also the management of the passengers after a casualty is becoming a major topic for safety. This paper presents the state of the art of Italian knowledge in the field of system engineering applied to passenger ship address to safety improvement and design reliability. An overview of present tools and methodologies will be offered together with future focuses in the research activity

BI as a service: an attempt to understand the leading adoption factors

The research question of this study attempts to identify which are the leading factors for the adoption of a sourcing Software as a Service model for Business Intelligence applications. The objective is to build a model containing enabling factors for the adoption of BI solutions. We seek to expand on the Benlian et al. model which is based on a theoretical framework including axioms from Transaction Cost Theory, Resource Based View, Theory of Planned Behavior. In order to better understand the phenomenon under investigation, we will use also the Organizational Culture Theory. It is a theoretical research in progress

Italian Version of the Risk Assessment and Prediction Tool: Properties and Usefulness of a Decision-Making Tool for Subjects' Discharge after Total Hip and Knee Arthroplasty

Background: Growing attention is being given to standardized outcome measures to improve interventions for total hip arthroplasty (THA) and total knee arthroplasty (TKA). We culturally adapt and validate the Italian version of the Risk Assessment and Prediction Tool (RAPT-I) to allow its predictive use after THA and TKA. Methods: The RAPT-I was adapted by forward-backward translation, a final review by an expert committee and a test of the pre-final version to establish its correspondence with the original version. The psychometric testing included test-retest reliability (intraclass correlation coefficient, ICC). The RAPT score was used to predict the subjects-destination (<6: rehabilitation unit; 6-9: additional intervention before discharging home; or >9: discharge directly at home) by comparing the actual discharge destination with the predicted destination. The predictive effects of RAPT items on the discharge destination were further described by a logistic regression model (repeated leave-one-out bootstrap procedure). Results: The questionnaire was administered to 78 subjects with THA and 70 subjects with TKA and proven to be acceptable. The questionnaire showed excellent test–retest reliability (ICC = 0.839; with 95% confidence interval (CI) of 0.725–0.934 for THA; ICC = 0.973, with 95% CI of 0.930–0.997 for TKA). The RAPT-I overall predictive validity was 87.2%, and the discharge destination was directly related to living condition (odds ratio (OR) = 2.530), mobility (OR = 2.626) and age (OR = 1.332) and inversely related to gait aids (OR = 0.623) and gender (OR = 0.474). Conclusions: The RAPT-I was successfully adapted into Italian and proven to exhibit satisfactory properties, including predictive validity in determining discharge destination

Advances in geometrical parametrization and reduced order models and methods for computational fluid dynamics problems in applied sciences and engineering: overview and perspectives

Several problems in applied sciences and engineering require reduction techniques in order to allow computational tools to be employed in the daily practice, especially in iterative procedures such as optimization or sensitivity analysis. Reduced order methods need to face increasingly complex problems in computational mechanics, especially into a multiphysics setting. Several issues should be faced: stability of the approximation, efficient treatment of nonlinearities, uniqueness or possible bifurcations of the state solutions, proper coupling between fields, as well as offline-online computing, computational savings and certification of errors as measure of accuracy. Moreover, efficient geometrical parametrization techniques should be devised to efficiently face shape optimization problems, as well as shape reconstruction and shape assimilation problems. A related aspect deals with the management of parametrized interfaces in multiphysics problems, such as fluid-structure interaction problems, and also a domain decomposition based approach for complex parametrized networks. We present some illustrative industrial and biomedical problems as examples of recent advances on methodological developments. \ua9 The author