Energy efficiency parametric design tool in the framework of holistic ship design optimization

Recent International Maritime Organization (IMO) decisions with respect to measures to reduce the emissions from maritime greenhouse gases (GHGs) suggest that the collaboration of all major stakeholders of shipbuilding and ship operations is required to address this complex techno-economical and highly political problem efficiently. This calls eventually for the development of proper design, operational knowledge, and assessment tools for the energy-efficient design and operation of ships, as suggested by the Second IMO GHG Study (2009). This type of coordination of the efforts of many maritime stakeholders, with often conflicting professional interests but ultimately commonly aiming at optimal ship design and operation solutions, has been addressed within a methodology developed in the EU-funded Logistics-Based (LOGBASED) Design Project (2004–2007). Based on the knowledge base developed within this project, a new parametric design software tool (PDT) has been developed by the National Technical University of Athens, Ship Design Laboratory (NTUA-SDL), for implementing an energy efficiency design and management procedure. The PDT is an integral part of an earlier developed holistic ship design optimization approach by NTUA-SDL that addresses the multi-objective ship design optimization problem. It provides Pareto-optimum solutions and a complete mapping of the design space in a comprehensive way for the final assessment and decision by all the involved stakeholders. The application of the tool to the design of a large oil tanker and alternatively to container ships is elaborated in the presented paper

Preface of the “Symposium on numerical optimization and applications”

[Excerpt] Numerical Optimization and Applications Symposium emphasizes modeling, theory and study of numerical algorithms for optimization. Optimization is an important tool in decision science and in the analysis of physical systems. Furthermore the Optimization plays central role in a tremendous variety of application in the natural sciences, in the sectors of economy, finance, and industry operational research and in the engineering. Because of the wide and growing use of optimization, it is important to develop an understanding of optimization algorithms. Knowledge of the capabilities and limitations of these algorithms leads to a better understanding of their impact on various applications, and points the way to future research on improving and extending optimization algorithms and software. [...](undefined

Biofilm dynamics characterization using a novel DO-MEA sensor: mass transport and biokinetics

Biodegradation process modeling is an essential tool for the optimization of biotechnologies related to gaseous pollutant treatment. In these technologies, the predominant role of biofilm, particularly under conditions of no mass transfer limitations, results in a need to determine what processes are occurring within the same. By measuring the interior of the biofilms, an increased knowledge of mass transport and biodegradation processes may be attained. This information is useful in order to develop more reliable models that take biofilm heterogeneity into account. In this study, a new methodology, based on a novel dissolved oxygen (DO) and mass transport microelectronic array (MEA) sensor, is presented in order to characterize a biofilm. Utilizing the MEA sensor, designed to obtain DO and diffusivity profiles with a single measurement, it was possible to obtain distributions of oxygen diffusivity and biokinetic parameters along a biofilm grown in a flat plate bioreactor (FPB). The results obtained for oxygen diffusivity, estimated from oxygenation profiles and direct measurements, revealed that changes in its distribution were reduced when increasing the liquid flow rate. It was also possible to observe the effect of biofilm heterogeneity through biokinetic parameters, estimated using the DO profiles. Biokinetic parameters, including maximum specific growth rate, the Monod half-saturation coefficient of oxygen, and the maintenance coefficient for oxygen which showed a marked variation across the biofilm, suggest that a tool that considers the heterogeneity of biofilms is essential for the optimization of biotechnologies.Peer ReviewedPostprint (published version

Optimization Model that Minimizes the Penalty Caused by Delayed Delivery of Construction Projects

Purpose: This work aims to minimize the penalty generated by delays in delivering construction projects operated by a single machine.   Theoretical framework: The fundamental issues to develop this work are optimization and its application to delays in construction projects operated in their initial stage by a single machine.   Design/Methodology/Approach: We presented a construction case study, developed an optimization model, implemented a computational optimization tool and obtained the optimal sequence to perform the tasks.     Findings: The numerical results demonstrated the model’s usefulness in minimizing the penalty generated by delays in the delivery of projects.   Research, practical & social implications: The benefit of this study is to help managers or decision-makers schedule their construction projects with limited resources and deadlines per activity to minimize penalty costs of delay.   Originality/Value: Considering that the construction sector generates the largest labor force in Peru, the study has an important social value by providing a tool to improve operations and incentivize construction companies to continue operating. In addition, it provides a substantial basis for future work by applying optimization in a specific area of civil engineering. To our knowledge, no researcher or company in Peru has yet addressed this study

Preface of the symposium: numerical optimization and applications

Numerical Optimization and Applications Symposium emphasizes modeling, theory and study of numerical algorithms for optimization. Optimization is an important tool in decision science and in the analysis of physical systems. Furthermore the Optimization plays central role in a tremendous variety of application in the natural sciences, in the sectors of economy, finance, and industry operational research and in the engineering. Because of the wide and growing use of optimization, it is important to develop an understanding of optimization algorithms. Knowledge of the capabilities and limitations of these algorithms leads to a better understanding of their impact on various applications, and points the way to future research on improving and extending optimization algorithms and software. Our goal in this session is to illustrate some modern optimization techniques in our days, by presenting efficient methods to solve different type of optimization problems including some real world problems.info:eu-repo/semantics/publishedVersio

A traveling salesman approach for predicting protein functions

BACKGROUND: Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. RESULTS: Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm [1] on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. CONCLUSION: Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems

Pinch Analysis as a Knowledge Management Tool for Optimization in Supply Chain

Supply chain managers are trying to maximize the profitable operation of their manufacturing and distribution supply chain, but due to global competition in process industries and complexities of the supply chain processes together with large computational times, it has made optimization of supply chain management (SCM) quite difficult. Recently, Knowledge management (KM) is a new important information technology-based business paradigm for achieving competitive advantage, and it is no surprise that it has received so much attention from researchers. This paper therefore deploys Pinch Analysis, a practicable tool that entails less complex mathematics compared to many other optimization tools, to manage critical knowledge generated in supply chains. In this study, demand and supply explicit knowledge from the organization was represented as composites for the pinch analysis. The developed system gave supply chain managers new insights into SCM and thus aiding quick decision-making and on the overall helped to achieve the much needed competitive advantage

Pinch Analysis as a Knowledge Management Tool for Optimization in Supply Chain

Supply chain managers are trying to maximize the profitable operation of their manufacturing and distribution supply chain, but due to global competition in process industries and complexities of the supply chain processes together with large computational times, it has made optimization of supply chain management (SCM) quite difficult. Recently, Knowledge management (KM) is a new important information technology-based business paradigm for achieving competitive advantage, and it is no surprise that it has received so much attention from researchers. This paper therefore deploys Pinch Analysis, a practicable tool that entails less complex mathematics compared to many other optimization tools, to manage critical knowledge generated in supply chains. In this study, demand and supply explicit knowledge from the organization was represented as composites for the pinch analysis. The developed system gave supply chain managers new insights into SCM and thus aiding quick decision-making and on the overall helped to achieve the much needed competitive advantage

Evolutionary Structural Optimization as Tool in Finding Strut-and-tie-models for Designing Reinforced Concrete Deep Beam

AbstractStrut-and-Tie models are well-known worldwide as valuable tool in designing D-Regions of Reinforced Concrete members. It has been adopted in many Concrete Structural Codes in many countries. Recently strut-and-tie-models have been included in Indonesia Concrete Structural Code (SNI-03-2847-2012). In this paper, it will be shown how a Strut-and-Tie Model can be developed for various structural concrete deep beams using Evolutionary Structural Optimization. As a tool for this study the author used Bi-Directional Evolutionary Structural Optimization (BESO2D) computer programs, developed by X. Huang and Y.M. Xie [1]. Three tested concrete beams with small, medium, and large opening [2] will be taken as the case study. It will be shown the optimal topology of a plane stress of continuum structures produced from BESO2D can be taken as the basic strut-and-tie-model. For design process the best strut-and-tie-model can be delivered from the optimal topology structure only with the deep knowledge of the basic load transfer from loading to support poin