A FEM Based Potential Theory Approach for Optimal Ice Routing

2016 ◽  
Author(s):  
Henry Piehl ◽  
Aleksandar-Saša Milaković ◽  
Sören Ehlers
Keyword(s):  
Fuel Consumption ◽  
Computational Method ◽  
Detection Methods ◽  
Ice Thickness ◽  
Test Problems ◽  
Theory Approach ◽  
Optimal Route ◽  
Cost Information ◽  
Development Approach ◽  
Problem Solve

Shipping in ice covered regions has gained high attention within recent years. Analogous to weather routing, the occurrence of ice in a seaway affects the selection of the optimal route with respect to the travel time or fuel consumption. The shorter, direct path between two points — which may lead through an ice covered area — may require a reduction of speed and an increase in fuel consumption. A longer, indirect route, could be more efficient by avoiding the ice covered region. Certain regions may have to be avoided completely, if the ice thickness exceeds the ice-capability of the ship. The objective of this study is to develop a computational method that combines coastline maps, route cost information (e.g. ice thickness), transport task and ship properties to find the optimal route between port of departure A and port of destination B. The development approach for this tool is to formulate the transport task in form of a potential problem, solve this equation with a finite element method and apply edge detection methods and line integration to determine the optimal route. The functionality of the method is first evaluated with simple test problems and then applied to realistic transport scenarios.

A Finite Element Method-Based Potential Theory Approach for Optimal Ice Routing

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Henry Piehl ◽  
Aleksandar-Saša Milaković ◽  
Sören Ehlers
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Fuel Consumption ◽  
Computational Method ◽  
Ice Thickness ◽  
Test Problems ◽  
Theory Approach ◽  
Optimal Route ◽  
Cost Information ◽  
Element Method

Shipping in ice-covered regions has gained high attention within recent years. Analogous to weather routing, the occurrence of ice in a seaway affects the selection of the optimal route with respect to the travel time or fuel consumption. The shorter, direct path between two points—which may lead through an ice-covered area—may require a reduction of speed and an increase in fuel consumption. A longer, indirect route, could be more efficient by avoiding the ice-covered region. Certain regions may have to be avoided completely, if the ice thickness exceeds the ice-capability of the ship. The objective of this study is to develop a computational method that combines coastline maps, route cost information (e.g., ice thickness), transport task, and ship properties to find the optimal route between port of departure, A, and port of destination, B. The development approach for this tool is to formulate the transport task in the form of a potential problem, solve this equation with a finite element method (FEM), and apply line integration and optimization to determine the best route. The functionality of the method is first evaluated with simple test problems and then applied to realistic transport scenarios.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

Numerical Simulation of Ice Action to a Lighthouse

2009 ◽  
Author(s):  
Arne Gu¨rtner ◽  
Morten Bjerka˚s ◽  
Walter Ku¨hnlein ◽  
Peter Jochmann ◽  
Ibrahim Konuk
Keyword(s):  
Outer Boundary ◽  
Element Model ◽  
Computational Method ◽  
Ice Thickness ◽  
Cohesive Elements ◽  
Element Mesh ◽  
To The Lighthouse ◽  
Ice Loads ◽  
Qualitative Observation ◽  
Cohesive Element Model

Ice actions to the Norstro¨msgrund lighthouse are simulated by means of the computational cohesive element model. The numerical model is developed in the framework of finite elements. Fracture of the ice sheet is accounted for by the cohesive elements placed at internal finite element mesh boundaries in order to track traction versus separation. One single ice event on the Norstro¨msgrund lighthouse is selected for which the ice loads as well as outer boundary conditions are recorded. This event serves as a basis for comparison to the computational method presented in this paper. The simulation results indicate that the proposed numerical method captures many of the qualitative observation as well as quantitatively derives comparable global ice loads to the lighthouse to those of the selected ice event. Future analysis should include additional validation to variations in ice thickness and drift speed.

scholarly journals ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data

2019 ◽  
Author(s):  
Egor Dolzhenko ◽  
Mark F. Bennett ◽  
Phillip A. Richmond ◽  
Brett Trost ◽  
Sai Chen ◽  
...  
Keyword(s):  
Tandem Repeats ◽  
Simulated Data ◽  
Computational Method ◽  
Detection Methods ◽  
Sequencing Data ◽  
Short Read ◽  
Short Read Sequencing ◽  
Monogenic Disorders ◽  
Genome Wide ◽  
Repeat Expansions

AbstractExpansions of short tandem repeats are responsible for over 40 monogenic disorders, and undoubtedly many more pathogenic repeat expansions (REs) remain to be discovered. Existing methods for detecting REs in short-read sequencing data require predefined repeat catalogs. However recent discoveries have emphasized the need for detection methods that do not require candidate repeats to be specified in advance. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide detection of REs. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference REs not discoverable via existing methods.ExpansionHunter Denovo is freely available at https://github.com/Illumina/ExpansionHunterDenovo

scholarly journals High resolution discovery of chromatin interactions

2018 ◽  
Author(s):  
Yuchun Guo ◽  
Konstantin Krismer ◽  
Michael Closser ◽  
Hynek Wichterle ◽  
David K. Gifford
Keyword(s):  
De Novo ◽  
Interaction Analysis ◽  
Computational Method ◽  
Detection Methods ◽  
Chromatin Interaction ◽  
Dynamic Interactions ◽  
Interaction Detection ◽  
Chromatin Interactions ◽  
Linkage Information ◽  
Functional Consequences

ABSTRACTChromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a method for the genome-wide de novo discovery of chromatin interactions. Existing computational methods typically fail to detect weak or dynamic interactions because they use a peak-calling step that ignores paired-end linkage information. We have developed a novel computational method called Chromatin Interaction Discovery (CID) to overcome this limitation with an unbiased clustering approach for interaction discovery. CID outperforms existing chromatin interaction detection methods with improved sensitivity, replicate consistency, and concordance with other chromatin interaction datasets. In addition, CID also outperforms other methods in discovering chromatin interactions from HiChIP data. We expect that the CID method will be valuable in characterizing 3D chromatin interactions and in understanding the functional consequences of disease-associated distal genetic variations.

scholarly journals EVALUATION OF THE EFFICIENCY OF THE LOGISTICS COMPANY'S TRANSPORT PARK

2021 ◽  
pp. 150-156
Author(s):  
M. Golovanenko ◽  
Keyword(s):  
Fuel Consumption ◽  
Optimal Transport ◽  
Load Capacity ◽  
Optimal Route ◽  
Logistics Network ◽  
Logistics Company ◽  
Route Length ◽  
Consumption Rates ◽  
Minimum Capacity ◽  
Lower Capacity

The article is devoted to the conceptual issues of evaluation of the efficiency of the logistics company's transport park. The information base of the study is data of the real logistics network of one of the leading logistics companies in Dnipro, which has 42 branches. Based on the capabilities of the Google OR-Tools optimization package, a system of optimal transport routes for different fleet options has been built. According to the results of calculations, the transition from vehicles with higher capacity to lower capacity increases the number of passages and the length of the optimal route. Replacing the fleet of the largest load capacity (20 tons) with the smallest (1 ton) leads to considerable increasing of the optimal route’ length. Less capable vehicles are characterized by lower fuel consumption. But the results of calculating the total cost of implementing optimal routes proves that the transition from more capable to less capable vehicles is not effective. Indirect estimation of the efficiency of the combined fleet was built by gradually replacing of the minimum capacity vehicles in the fleet with the maximum capacity vehicles. For each such variant of the fleet, the optimal route was built, its length was recorded and fuel consumption was estimated. Estimation of fuel consumption was carried out by multiplying the length of mileage of large and small-capacity vehicles by the corresponding fuel consumption rates. Prospects for further research are to verify the results using alternative optimization tools. The results of the analysis indicate the effectiveness of building a transport fleet of logistics company based on heavy-duty vehicles. This approach reduces the number of pendulum routes and minimizes fuel consumption through the use of ring routes.

scholarly journals Nonlinear model of a dynamic system for forecasting of fuel consumption of a ship using a neural network

2020 ◽  
Author(s):  
В.И. Филатов
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Optimal Route ◽  
Training Set ◽  
Marquardt Algorithm ◽  
Levenberg Marquardt ◽  
Nonlinear Forecasting ◽  
Statistical Sample ◽  
Operational Data ◽  
Bunker Fuel

В современных условиях коммерческого судоходства, большое внимания уделяется вопросам оптимизации расхода топлива на судах. Наиболее критическим моментом, определяющим эффективность рейса, является количество бункерного топлива, использованного на морском переходе судном. В данной статье предложен подход к прогнозированию расхода топлива на предстоящем переходе судна с помощью использования нейронной сети, обученной с помощью алгоритма Левенберга-Марквардта, а также рассмотрено преимущество данного метода в сравнении с методами других исследователей. Статистическая выборка для машинного обучения составлена на основе эксплуатационных данных с танкера класса Афрамакс . Элементом новизны в данной работе является формирование данных для обучающего множества, а также возможность нелинейного прогнозирования посуточного приращения скорости. Данный метод имеет высокую точность и может применятся как фрахтователем, так и судоводителем для того, чтобы оценить экономическую эффективность предстающего рейса или выбрать оптимальный маршрут по параметру расхода топлива. Ещё одной задачей прогнозирования параметров судна на переходе с помощью нейронной сети является расчёт ожидаемых приращений скорости судна, что таблица расходов бункерного топлива может быть применена только при условиях не более 4-5 баллом во шкале Бофорта. In modern conditions of commercial shipping, much attention is paid to the optimization of fuel consumption on the sea. The most critical moment determining the voyages efficiency is the amount of bunker fuel used by the ship at the sea passage. This article proposes an approach to forecasting fuel consumption at the upcoming passage of a vessel using a neural network taught-in by the Levenberg-Marquardt algorithm, and also considers the advantage of this method in comparison with methods of other researchers. The statistical sample for machine learning is based on operational data from an Aframax class tanker. The novelty element in this work is the formation of data for the training set, as well as the possibility of nonlinear forecasting of the daily increment of speed. This method is highly accurate and can be used by both the charterer and the navigator in order to evaluate the economic efficiency of the upcoming voyage or to choose the optimal route according to the fuel consumption parameter. Another task of predicting the parameters of a vessel at a passage using a neural network is to calculate the expected increments of the vessels speed, with that the table of bunker fuel consumption can be applied only under conditions of no more than 4-5 points on the Beaufort scale.

Development and Evaluation of Optimal Routing System

2008 ◽  
Author(s):  
Gunil Park ◽  
Jaewoong Choi ◽  
Jinho Lee ◽  
Munsung Kim ◽  
Changseon Bang ◽  
...  
Keyword(s):  
Real Time ◽  
Fuel Consumption ◽  
Weather Forecasting ◽  
Weather Condition ◽  
Bending Moment ◽  
Optimal Route ◽  
Stress Monitoring ◽  
Wave Condition ◽  
Propulsion Performance ◽  
Seakeeping Performance

To improve the safety and efficiency of trans-ocean voyage, authors developed a new onboard weather routing system (so called SORAS). The system utilizes weather forecasting data to evaluate seakeeping performance and to generate optimized route plan with respect to fuel consumption and sailing time. The system can provide decision support for navigator in real time. For this feature, onboard wave measurement system and hull stress monitoring system are integrated to provide real time wave information and actual hull stress and bow acceleration. The optimal route depends on not only weather condition but also ship’s propulsion performance. We performed a simulation study to determine the accuracy limit of mathematical model for propulsion performance. To evaluate the system, we compared calculation results with actual voyage data. The estimation results of speed reduction and fuel consumption showed good coincidence with measurement results. The wave bending moment was estimated on the forecasted wave condition. The results were compared with measured wave bending moment. For optimal route, it was confirmed that the efficiency of optimal route is superior to the efficiency of the actual route which planned by captains or officers, and the improvement of efficiency would be significant.

scholarly journals An effective computational approach based on Gegenbauer wavelets for solving the time-fractional Kdv-Burgers-Kuramoto equation

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Aydin Secer ◽  
Neslihan Ozdemir
Keyword(s):  
Galerkin Method ◽  
Operational Matrix ◽  
Computational Method ◽  
Test Problems ◽  
Algebraic Equations ◽  
Dispersion Parameters ◽  
Wavelet Galerkin Method ◽  
Operational Matrix Of Integration ◽  
Nonlinear Physical Phenomena ◽  
The Galerkin Method

Abstract In this paper, our purpose is to present a wavelet Galerkin method for solving the time-fractional KdV-Burgers-Kuramoto (KBK) equation, which describes nonlinear physical phenomena and involves instability, dissipation, and dispersion parameters. The presented computational method in this paper is based on Gegenbauer wavelets. Gegenbauer wavelets have useful properties. Gegenbauer wavelets and the operational matrix of integration, together with the Galerkin method, were used to transform the time-fractional KBK equation into the corresponding nonlinear system of algebraic equations, which can be solved numerically with Newton’s method. Our aim is to show that the Gegenbauer wavelets-based method is efficient and powerful tool for solving the KBK equation with time-fractional derivative. In order to compare the obtained numerical results of the wavelet Galerkin method with exact solutions, two test problems were chosen. The obtained results prove the performance and efficiency of the presented method.

scholarly journals A Two-Step Approach for Airborne Delay Minimization Using Pretactical Conflict Resolution in Free-Route Airspace

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Ramazan Kursat Cecen ◽  
Cem Cetek
Keyword(s):  
Conflict Resolution ◽  
Fuel Consumption ◽  
Traffic Management ◽  
Test Problems ◽  
Mathematical Basis ◽  
Solution Approach ◽  
Delay Minimization ◽  
Entry Points ◽  
Feasible Solutions ◽  
Short Time

This study proposes a two-step solution approach for aircraft conflict resolution and fuel consumption due to resolution maneuver occurring in free-route airspace. This model aims to provide a mathematical basis for a decision-support system that is used during the pretactical conflict resolution in air traffic management. Mathematical model of the first step presents alternative entry points on both sides of existing sector entry points to minimize delays by directing aircraft to the most convenient entry points. The second step suggests a vector deflection maneuver to minimize extra fuel consumption caused by conflict resolution. GAMS/CPLEX solver is used to solve the first step of the model but the solution is not produced in a reasonable time. To obtain feasible solutions, genetic algorithm and tabu search algorithms are implemented in the first step. Small size test problems are generated to evaluate the metaheuristic algorithms, and results are compared with GAMS/CPLEX solver solutions. According to this comparison, both metaheuristics algorithms produce near optimal solutions in a reasonably short time. The proposed approach has made significant improvements for airborne delays and extra fuel consumption caused by aircraft conflicts resolution in large-scaled airspaces.

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