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Publisher: Elsevier   (Total: 3159 journals)

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Showing 1 - 200 of 3159 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 9)
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 32, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 22, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 90, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 34, SJR: 1.771, CiteScore: 3)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 7)
Acta Astronautica     Hybrid Journal   (Followers: 408, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 2)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.18, CiteScore: 1)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.128, CiteScore: 0)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 246, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 10, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 28, SJR: 1.331, CiteScore: 2)
Acta Sociológica     Open Access   (Followers: 1)
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.052, CiteScore: 2)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3, SJR: 0.374, CiteScore: 1)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.344, CiteScore: 1)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.19, CiteScore: 0)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 6)
Acute Pain     Full-text available via subscription   (Followers: 15, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 16, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 9, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 143, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, SJR: 0.694, CiteScore: 3)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 12, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 22, SJR: 2.089, CiteScore: 5)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 0.572, CiteScore: 2)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.61, CiteScore: 7)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.686, CiteScore: 2)
Advances in Cancer Research     Full-text available via subscription   (Followers: 30, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 7, SJR: 1.453, CiteScore: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 1.992, CiteScore: 5)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 3)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 27, SJR: 0.156, CiteScore: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.713, CiteScore: 1)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 10, SJR: 1.316, CiteScore: 2)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 1.977, CiteScore: 8)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.205, CiteScore: 1)
Advances in Dermatology     Full-text available via subscription   (Followers: 15)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 9)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 24)
Advances in Ecological Research     Full-text available via subscription   (Followers: 43, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 27, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 44, SJR: 5.39, CiteScore: 8)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 9)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 54, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 16, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 8, SJR: 12.74, CiteScore: 13)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 1.193, CiteScore: 3)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 11, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.193, CiteScore: 0)
Advances in Immunology     Full-text available via subscription   (Followers: 36, SJR: 4.433, CiteScore: 6)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 1.163, CiteScore: 2)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 2, SJR: 1.938, CiteScore: 3)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6, SJR: 0.176, CiteScore: 0)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 3)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.682, CiteScore: 2)
Advances in Lipobiology     Full-text available via subscription   (Followers: 1)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 14, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.027, CiteScore: 2)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.694, CiteScore: 2)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.158, CiteScore: 3)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 21)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 1)
Advances in Organ Biology     Full-text available via subscription   (Followers: 1)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 16, SJR: 1.875, CiteScore: 4)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.174, CiteScore: 0)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 1.579, CiteScore: 4)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 10)
Advances in Pharmacology     Full-text available via subscription   (Followers: 16, SJR: 1.536, CiteScore: 3)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.574, CiteScore: 1)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.109, CiteScore: 1)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 8)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 0.791, CiteScore: 2)
Advances in Psychology     Full-text available via subscription   (Followers: 63)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (SJR: 0.263, CiteScore: 1)
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.101, CiteScore: 0)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 5)
Advances in Space Research     Full-text available via subscription   (Followers: 396, SJR: 0.569, CiteScore: 2)
Advances in Structural Biology     Full-text available via subscription   (Followers: 5)
Advances in Surgery     Full-text available via subscription   (Followers: 10, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 31, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 18)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 46, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 336, SJR: 0.796, CiteScore: 3)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.42, CiteScore: 2)
African J. of Emergency Medicine     Open Access   (Followers: 6, SJR: 0.296, CiteScore: 0)
Ageing Research Reviews     Hybrid Journal   (Followers: 11, SJR: 3.671, CiteScore: 9)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 445, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 16, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 32, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 43, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 1)
Agriculture and Natural Resources     Open Access   (Followers: 2)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 57, SJR: 1.747, CiteScore: 4)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.589, CiteScore: 3)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.26, CiteScore: 0)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.19, CiteScore: 0)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 9)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 10, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 50, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 50, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 54, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 44, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 28, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 34, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 45)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3, SJR: 1.967, CiteScore: 2)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 202, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 63, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 27, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 28, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 37, SJR: 1.141, CiteScore: 2)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.767, CiteScore: 1)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 6)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 62, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 16, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.277, CiteScore: 0)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription  
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5, SJR: 4.849, CiteScore: 10)
Analytica Chimica Acta     Hybrid Journal   (Followers: 40, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 173, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 10, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 23, SJR: 0.683, CiteScore: 2)
Angiología     Full-text available via subscription   (SJR: 0.121, CiteScore: 0)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1, SJR: 0.111, CiteScore: 0)
Animal Behaviour     Hybrid Journal   (Followers: 190, SJR: 1.58, CiteScore: 3)

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Journal Cover
Advances in Engineering Software
Journal Prestige (SJR): 1.159
Citation Impact (citeScore): 4
Number of Followers: 27  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0965-9978
Published by Elsevier Homepage  [3159 journals]
  • Multi-objective topology optimization of a vehicle door using multiple
           material tailor-welded blank (TWB) technology
    • Abstract: Publication date: Available online 26 July 2018Source: Advances in Engineering SoftwareAuthor(s): Guangyong Sun, Dongdong Tan, Xiaojiang Lv, Xiaolei Yan, Qing Li, Xiaodong Huang As one of effective technologies, tailor welded blank (TWB) has been extensively applied to improve structural performance and efficiency of material usage for lightweight automobile. The vehicle door is an important part of structure that presents many design requirements including stiffness, natural frequency, etc. However, finding an optimal layout of the multi-material TWB welding lines of a vehicle door remains fairly challenging through conventional design methods. This study proposed a multi-objective topology optimization method for this purpose. The compromise programming approach (CAP) coupled with the mean frequency method (MFM) is introduced to handle the multi-objective optimization involving stiffness and natural frequency criteria for multiple load cases. The multi-objective problems are then solved by the extended bi-directional evolutionary structural optimization (BESO) method. The design examples demonstrate that the proposed approach is suitable for the multi-objective and multi-material topology optimization (MMTO) of TWB indoor panel. The study also provides the design guidance for lightweight and multi-material structures with the TWB technology.
       
  • Vector field radial basis function approximation
    • Abstract: Publication date: Available online 21 July 2018Source: Advances in Engineering SoftwareAuthor(s): Michal Smolik, Vaclav Skala, Zuzana Majdisova Vector field simplification aims to reduce the complexity of the flow by removing features according to their relevance and importance. Our goal is to preserve only the important critical points in the vector field and thus simplify the vector field for the visualization purposes. We use Radial Basis Functions (RBF) approximation with Lagrange multipliers for vector field approximation. The proposed method was experimentally verified on synthetic and real weather forecast data sets. The results proved the quality of the proposed approximation method compared to other existing approaches. A significant contribution of the proposed method is an analytical form of the vector field which can be used in further processing.
       
  • Ship inner shell optimization based on the improved particle swarm
           optimization algorithm
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Guan Guan, Qu Yang, Wenwen Gu, Wenying Jiang, Yan Lin To improve the changeability of ship inner shell (SIS), so that both performance and design efficiency of transport ship can be improved, a new method for SIS optimization is proposed in this study. The method is based on the parametric expression model of SIS, which is a fully-associative model driven by dimensions. Based on the parameters of SIS, the computing system of hold capacity is developed to calculate the floating status and stability automatically. Furthermore, a parametric SIS optimization model is created, including optimization objective, constraints, optimization model solving etc., in which the maximized hold capacity and minimized ballast capacity are optimization objectives, the requirements and rules for SIS design are used as the constraints. The particle swarm optimization (PSO) algorithm is improved to solve this optimization model. The proposed method is applied to a 50,000 DWT product oil tanker, and it is proved to be feasible, highly efficient, and engineering practical.
       
  • Numerical simulation of missile warhead operation
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): G. Martynenko, M. Chernobryvko, K. Avramov, V. Martynenko, A. Tonkonozhenko, V. Kozharin, D. Klymenko Numerical simulation of a missile warhead dynamic fracture is considered. The design of the warhead basic units is treated. The approach for simulations of the warhead fracture in software ANSYS is proposed. This approach is split on three stages. (I). The analysis of the static stress-strain state of the warhead, which is arisen owing to its assembling. (II). Calculations of the dynamic stress state of the structure. (III). Analysis of dynamic fracture of the most loaded units. The parameters of the warhead are chosen in order to a fracture takes place in the structure specified area.
       
  • Performance based discrete topology optimization of steel braced frames by
           a new metaheuristic
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Saeed Gholizadeh, Mehrdad Ebadijalal Seismic topology optimization of structures is a challenging field of structural engineering. So far, a little number of studies has been conducted on this regard and all of them have presented conceptual designs which are of limited practical applicability. The main aim of the present study is to find the practical optimal placement of X- and diagonal bracing systems in steel braced frames subject to seismic loading. To achieve this purpose, a discrete topology optimization formulation is proposed in the framework of seismic performance-based design. A new metaheuristic algorithm, center of mass optimization (CMO), is proposed to deal with the performance-based discrete topology optimization (PBDTO) problem based on the physical concept of center of mass for mass distribution in space. Two challenging benchmark structural optimization problems are presented in order to demonstrate the computational merit of the proposed CMO algorithm compared to a number of algorithms in literature. Furthermore, PBDTO process is implemented for four multi-story steel braced frames by CMO. Performance of the proposed CMO-based discrete topology optimization framework in finding practical topology of bracing members for SBFs is demonstrated on PBDTO examples.
       
  • Parameter optimization design of vehicle E-HHPS system based on an
           improved MOPSO algorithm
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Wanzhong Zhao, Zhongkai Luan, Chunyan Wang To improve the handling stability as well as reduce the steering energy consumption of heavy commercial vehicle, a novel electric-hydraulic hybrid power steering (E-HHPS) system with multiple steering modes is presented, which enables the vehicle to acquire the steering handiness at low speed and better steering road feeling at high speed by switching the actuator unit according to the current working condition. In this paper, to achieve the design goals of E-HHPS system, which are to reduce steering energy consumption and improve steering stability, three evaluation indexes of E-HHPS system are established, which convert the E-HHPS system parameter optimization problem into a multi-objective optimization model. Because it is difficult to approximate the Pareto front of the transformed optimization model by basic algorithms, a multi-objective particle swarm optimization algorithm based on adaptive decomposition (MOPSO/AD) is proposed. Test functions are used to verify the performance of the algorithm and test results show that the MOPSO/AD algorithm has better comprehensive performance and stability compared with the basic MOPSO algorithm and MOEA/D algorithm. The MOPSO/AD algorithm is applied to solve the E-HHPS system optimization model and simulation results show that the proposed MOPSO/AD algorithm has better convergence in solving the E-HHPS parameter optimization problem compared with MOPSO, which enables the optimized E-HHPS system has good handling stability and low steering energy consumption.
       
  • Hull form design optimization of twin-skeg fishing vessel for minimum
           resistance based on surrogate model
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Yan Lin, Jingyi He, Kai Li Twin-skeg ship has better hydrodynamic performances than regular ship, however, it is still difficult to obtain an accurate relationship between skeg design and overall hydrodynamic performances. Resistance optimization is the major concern of developing twin-skeg ship. This paper proposes a combined approach for hull form design optimization of twin-skeg ship by using computational fluid dynamics (CFD) calculation and surrogate model. Main design parameters of skeg geometry and arrangement could be determined from the design domain by using the proposed method. Parametric modeling technology is adopted for performing design evaluations in an automatic manner with different design parameter combinations. A twin-skeg fishing vessel is selected as research object. In the proposed method, the sample set for constructing surrogate models is generated by using Optimal Latin Hypercube Sampling (OLHS) method, the corresponding responses are calculated through CFD simulations, and then the surrogate models are constructed by using Kriging modeling method, which represent the mathematical relationship between input design variables (skeg shape design variables) and output objective functions (resistance values under four different working conditions). The functional analysis of variance (ANOVA) is performed to investigate how much influence the design variables have on the objective functions. Finally, a multi-objective evolutionary algorithm (NSGA-II) is used to obtain the optimal solution, which shows 5.4% average decrease in the total resistance than the original design. The CFD calculation results of the optimal solution show that the proposed method can achieve minimum resistance design with high accuracy and low time cost.
       
  • Topology optimization of hyperelastic structure based on a directly
           coupled finite element and element-free Galerkin method
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Yaqing Zhang, Wenjie Ge, Yonghong Zhang, Zhenfei Zhao, Jinwang Zhang Meshless methods can solve large classes of problems where grid-based methods are awkward to handle, such as the discretizing of complicated structures, the remeshing in large displacement problems and so on. In this study, a meshless-based topology optimization is proposed for large displacement problems of nonlinear hyperelastic structure. In order to circumvent nonlinear numerical instabilities, the linear and nonlinear analyses are set in the low- and high-stiffness region, respectively. Thus, an interpolation scheme is adopted for hybridizing the linearity and nonlinearity in the structure analysis. A directly coupled finite element and meshless method is introduced to reduce the computational cost of meshless methods and an auto-coupling strategy is proposed for the adaptive arrangement of finite element and meshless regions. Several numerical examples are given to demonstrate the effectiveness of the proposed method.
       
  • Optimizing presetting attributes by softcomputing techniques to improve
           tapered roller bearings working conditions
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Roberto Fernandez Martinez, Ruben Lostado Lorza, Ana A. Santos Delgado, Nelson O. Piedra Pullaguari Double-row Tapered Roller Bearings are mechanical devices that have been designed to support a combination of loads that are fixed on an optimal presetting to ensure correct working conditions. The emergence of high contact stresses, fatigue spalling and pitting on the bearing railway makes it important to have a tool that enables knowing in advance whether certain presetting loads will lead to excellent working conditions or the opposite. This work proposes a methodology to classify the working condition on the basis of the values of presenting loads on four classes. To achieve this goal, a three-dimensional Finite Element (FE) model was generated. Later, a design of experiments was designed to provide the greatest amount of information by reducing the computational cost of the simulations based on FE models. Then, one of the four classes of working conditions was assigned to each of the experiments. Later, a statistical analysis and machine learning techniques were used to create classification models. Feature transformation and reduction, algorithm parameter tuning and validation methods were used to achieve robust classification models. The best results were obtained based on flexible discriminant analysis. As it provided acceptable accuracy, both the methodology and final model were validated.
       
  • A dynamic ductile failure analysis of shell structures using a nonlocal
           XFEM method with experimental validation
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): C.T. Wu, N. Ma, Y. Guo, W. Hu, K. Takada, H. Okada, K. Saito This paper presents a finite element continuous-discontinuous approach for the dynamic ductile failure analysis of shell structures. The continuum damage model based on continuous displacements is used in the continuous stage to describe the diffuse micro-cracking in ductile failure of high-strength steel before a macro-crack is formed. In the context of a fully integrated shear deformable shell formulation, a nonlocal modeling procedure based on a projection of mid-plane reference surface is introduced to regularize the element-wise strain fields induced by the continuum damage model. In the discontinuous stage, an incorporation of velocity discontinuities in shell finite elements is pursued by XFEM method when the damage variable exceeds a critical value and the transition from a continuous to a discontinuous model is permitted. A phantom-node approach is employed in the XFEM method to simplify the numerical treatment of velocity discontinuities in the shell finite element formulation. Several numerical benchmarks are examined using the explicit dynamics analysis and the results are compared with the experimental data to demonstrate the effectiveness and accuracy of the proposed method.
       
  • Multi-surrogate-based Differential Evolution with multi-start exploration
           (MDEME) for computationally expensive optimization
    • Abstract: Publication date: September 2018Source: Advances in Engineering Software, Volume 123Author(s): Huachao Dong, Chengshan Li, Baowei Song, Peng Wang In this paper, we present a new global optimization algorithm MDEME for black-box problems with computationally expensive objectives. Considering that Differential Evolution (DE) is an efficient global optimization algorithm but has difficulty in expensive optimization problems, we combine DE with three surrogate models Kriging, Radial Basis Function (RBF), and Quadratic Polynomial Response (QRS) to realize surrogate-based optimization. Although the three surrogates have different approximate effects that may generate diverse updating points, the surrogate-based DE may still get stuck in local optimal regions. In order to enhance its exploration capability, a multi-start optimization algorithm with a new selecting strategy is proposed. The multi-start optimization algorithm can capture and select several promising points from Kriging and RBF that always generate multiple local optimal solutions per optimization cycle. In the whole optimization process, DE and the proposed multi-start optimization are alternately carried out on the three surrogate models that are dynamically updated. Once no more satisfactory points can be obtained from Kriging and RBF, the multi-start optimization will explore the sparsely sampled area using the estimated mean square error of Kriging. After the comparison with 5 global optimization algorithms on 17 representative cases, MDEME shows its high efficiency, strong stability and good parallelism capability in dealing with expensive optimization problems. Finally, MDEME is used for the shape optimization of a blended-wing-body underwater glider, and the design performance gets significantly improved.
       
  • In-plane torsional stiffness in a macro-panel element for practical finite
           element modelling
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): T.Q. Li, T. Ward, W.J. Lewis Finite element (FE) analysis produces results, which, in most cases, gain in accuracy, as the size of the FE mesh is reduced. However, this is not necessarily the case when beam and shell element connections induce in-plane torsional effects in the shell. In such situations, shell elements either do not allow for an in-plane torsional stiffness, or, when present, the in-plane torsional stiffness is incorrectly affected by the sizes of the elements. To overcome this problem, we propose a macro- panel element that has fewer degrees of freedom, includes a new model for in-plane torsional stiffness, and produces results with sufficient accuracy to meet engineering requirements. The panel element is based on the principle of sub-structuring, i.e., the panel is meshed internally by smaller shell elements. As shown in the paper, the proposed panel element can be quite large, yet, it can give accurate analysis results. This work helps to overcome a common dilemma in practical use of finite element analysis, where finite element theory requires element sizes to be sufficiently small, but practical considerations suggest the use of large-size elements that simplify the modelling process and reduce excesses in generated results. A model built using macro-panel elements is equivalent to the model built using smaller shell elements, with the normal and shear stresses in the former being the same as the stresses in the finely meshed shell element model, We identify a number of performance benefits that become available as a consequence of modelling the shell elements at a higher level of abstraction.
       
  • Optimal design of prestressed concrete hollow core slabs taking into
           account its fire resistance
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): V. Albero, H. Saura, A. Hospitaler, J.M. Montalvà, Manuel L. Romero Prestressed hollow core slabs are a concrete element widely used as construction floor product, which manufacturing process has greatly been improved in recent years. Several research studies focused on hollow core slab performance, mainly related to its fire behavior, have provided new limit states to be assessed throughout its life cycle. Therefore, the hollow core slab design needs to be reviewed to allow for these improvements, a process which may involve changes to its geometry. In order to deal with this review, modern computational optimization techniques offer an alternative approach to traditional structural product design procedure, mainly based on the engineer's prior experience.This paper proposes a hollow core slab model (including variables and constraints) to develop heuristic search algorithms, such as simulated annealing, in order to find the most economical slab design including the fire resistant constraint and taking into account all available manufacturing technologies. The optimal designs obtained by this process save up to 20% in cross-section area compared with common circular void designs from market, which is taken as a comparison pattern. The results show that traditional designs are deficient when the fire resistant constraint is considered, so that precast manufacturers and machinery designers should use optimization techniques to modify their hollow core slab geometry.
       
  • Discontinuous Galerkin method in numerical simulation of two-dimensional
           thermoelasticity problem with single stabilization parameter
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Jan Jaśkowiec, Piotr Pluciński The aim of the paper is the development of discontinuous Galerkin with finite difference rules (DGFD) to a two-dimensional stationary and non-stationary thermoelasticity problem. Displacement and temperature fields are approximated on the same mesh frame but with various approximation orders, which are set independently for each of the fields. Because the DGFD method does not use nodes, special attention needs to be paid to applying boundary conditions. Various types of thermal and mechanical boundary conditions are considered. In the presented approach only one stabilization parameter for the coupled problem needs to be evaluated in the DGFD method. The same parameter used in thermal and in mechanical part. The considered domain is discretized by a polygonal mesh in which the polygonal elements may have arbitrary shapes, such as e.g. a fish shape, as well as typical rectangular shapes. The orthogonality of Chebyshev basis functions may be utilized for rectangular elements. Very high-order approximate solution can be obtained in such case. In the coupled problem, the same element may be high-order for displacement field while low-order to approximate temperature. The argument contained in the paper is illustrated with few examples.
       
  • Genetic programming for soil-fiber composite assessment
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): HV Kurugodu, S Bordoloi, Y Hong, Ankit Garg, Akhil Garg, S Sreedeep, AH Gandomi Unconfined compressive strength (UCS) of soil is one of the basic index parameters for representing the compressive bearing strength of soil. Fiber reinforced soil is one of the most popular and practical ground improvement approaches used in geotechnical infrastructures. Analytical models for estimating UCS of soil-fiber composites have been developed in the literature. However, these models rarely incorporate the combined effects of dynamic field parameters such as fiber content, soil moisture, and density. These effects can be studied by the development of a holistic model based on a dimensionless strength improvement factor (SIF), which is defined as the ratio of UCS of reinforced soil to the unreinforced UCS. The current model estimating SIF indicates the improvement expected in UCS of soil-PP fiber composite based on the three design conditions such as fiber content, soil density, and moisture content. For this purpose, a series of 108 laboratory tests were first conducted to measure UCS of both fiber-reinforced soil and unreinforced soil under different fiber contents, soil density, and soil moisture content. Clayey silt soil and commercially used polypropylene (PP) fibers were selected in this study as soil and fiber material respectively. Genetic programming (GP) approach was then used to formulate models based on the measured data. The hidden non-linear relationships between SIF and the three inputs were determined by sensitivity and parametric analysis of the GP model. It was found that the moisture content in the soil has the highest influence on the strength factor that accounts for the change in strength. Coupled effects of soil parameters (soil moisture, soil density) and fiber content have been studied using parametric analysis which includes different possible field conditions (parameters). The results have been discussed along with the reinforcement mechanism of PP fiber for different soil conditions. It is believed that the robust GP model developed will be useful to determine optimum input values for designing safe bearing foundation soils which are reinforced with PP fibers.
       
  • Phase field modeling of quasi-static and dynamic crack propagation: COMSOL
           implementation and case studies
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Shuwei Zhou, Timon Rabczuk, Xiaoying Zhuang The phase-field model (PFM) represents the crack geometry in a diffusive way without introducing sharp discontinuities. This feature enables PFM to effectively model crack propagation compared with numerical methods based on discrete crack model, especially for complex crack patterns. Due to the involvement of “phased field”, phase-field method can be essentially treated a multifield problem even for pure mechanical problem. Therefore, it is supposed that the implementation of PFM based on a software developer that especially supports the solution of multifield problems should be more effective, simpler and more efficient than PFM implemented on a general finite element software. In this work, the authors aim to devise a simple and efficient implementation of phase-field model for the modelling of quasi-static and dynamic fracture in the general purpose commercial software developer, COMSOL Multiphysics. Notably only the tensile stress induced crack is accounted for crack evolution by using the decomposition of elastic strain energy. The width of the diffusive crack is controlled by a length-scale parameter. Equations that govern body motion and phase-field evolution are written into different modules in COMSOL, which are then coupled to a whole system to be solved. A staggered scheme is adopted to solve the coupled system and each module is solved sequentially during one time step. A number of 2D and 3D examples are tested to investigate the performance of the present implementation. Our simulations show good agreement with previous works, indicating the feasibility and validity of the COMSOL implementation of PFM.
       
  • Uncertainty analysis of an actuator for a shape memory alloy micro-pump
           with uncertain parameters
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Ahmed Guerine, Tarek Merzouki, Abdelkhalak El Hami, Tarak Ben Zineb In this paper, we propose a method for taking into account uncertainties of a micro-pump system using Shape Memory Alloy (SMA), based on the perturbation method. The proposed method is used to determine the thermo-mechanical response of a system. Comparisons with the mean value reference solution, illustrate the efficiency of the proposed method. The results are discussed in order to investigate the influence of the most influential parameters of the thermomechanical SMA model. The simulation results are obtained by the proposed method for static analysis with uncertainties.The perturbation method results are compared with the mean value reference solution. The results are discussed in order to investigate the influence of the Young's modulus E, the two transformations strain magnitude ɛtracT and ɛtracTFA, the martensite start Ms and austenite finish Af temperatures and the stress reorientation Fε on the static response of a micro-pump system.
       
  • An enhanced explicit technique for the solution of non-Fourier heat
           transfer problems
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Delfim Soares In this work, an enhanced explicit technique is proposed to analyze hyperbolic heat conduction models. As usual, the explicit approach allows the solution of the problem to be carried out without dealing with any system of equations, featuring a very efficient methodology. In addition, the proposed technique enables algorithmic dissipation, allowing the influence of spurious high modes to be properly eliminated, without introducing significant period elongation and amplitude decay errors into the analysis. As an explicit approach, the technique is conditionally stable; however, it exhibits high stability limits (its critical time-step is around 1.8 times that of the Central Difference Method), emphasizing its effectiveness. The technique is very accurate, truly self-starting and extremely direct to implement. At the end of the manuscript, numerical results are presented, illustrating the good performance of the discussed technique.
       
  • Suspension mechanical performance and vehicle ride comfort applying a
           novel jounce bumper based on negative Poisson's ratio structure
    • Abstract: Publication date: August 2018Source: Advances in Engineering Software, Volume 122Author(s): Yuanlong Wang, Wanzhong Zhao, Guan Zhou, Qiang Gao, Chunyan Wang Comparing with traditional honeycomb structures, Negative Poisson's Ratio (NPR) structures had better mechanical performances in some certain respects, especially the shear modulus and fracture toughness. However, few publications focused on the cylinder-shape NPR structure, which influence the diversity and possibility of NPR structure applications. In this paper, a cylindrical NPR structure was introduced and applied as a suspension jounce bumper in order to solve the issue that the ideal uniaxial compression load-displacement curve sometimes cannot be realized by traditional Polyurethane (PU) jounce bumper. The load-displacement curve of NPR jounce bumper was proved to be smoother and more ideal than that of traditional jounce bumper. Nevertheless, the influences of NPR jounce bumper on the suspension mechanical performance and vehicle ride comfort were not comprehended yet. In this study, the traditional and NPR jounce bumpers were both assembled into virtual prototypes of Macpherson, double wishbone and multi-link suspensions to conduct single wheel travel virtual tests. The results indicated that NPR jounce bumper can achieve more ideal wheel force vs. jounce height curve without adjusting free travel, which is beneficial to spare precise suspension space. Furthermore, a jounce bumper evaluation method using pulse ride comfort was proposed in this paper. The virtual ride comfort tests of travelling through bump and pothole were conducted using established vehicle virtual prototype. The maximum vertical accelerations and weighted root mean square (RMS) of acceleration of vehicle centroid at most speeds were reduced applying NPR jounce bumper. Thus, the NPR jounce bumper can apparently improve vehicle ride comfort.
       
  • Evaluation of the Intel Xeon Phi offload runtimes for domain decomposition
           solvers
    • Abstract: Publication date: Available online 8 July 2018Source: Advances in Engineering SoftwareAuthor(s): Lukas Maly, Jan Zapletal, Michal Merta, Lubomir Riha, Vit Vondrak In the paper we provide a comparison of several runtimes which can be used for offloading computationally intensive kernels to the Intel Xeon Phi coprocessors. The presented benchmark application is a stripped-down version of an iterative solver used within the Schur complement finite or boundary element tearing and interconnecting (FETI, BETI) domain decomposition methods where the sparse solve with local stiffness matrices is replaced by the multiplication with dense matrices in order to exploit coalesced memory access patterns. We present offload approaches based on the Intel Language Extension for Offload (LEO), Hetero Streams Library (hStreams), and Heterogeneous Active Messages (HAM), and compare their performance and ease of use.
       
  • Path-following interior point method: Theory and applications for the
           Stokes flow with a stick-slip boundary condition
    • Abstract: Publication date: Available online 8 July 2018Source: Advances in Engineering SoftwareAuthor(s): Tomáš Brzobohatý, Marta Jarošová, Radek Kučera, Václav Šátek A path-following interior point method is proposed for minimization of quadratic functions subject to box and equality constraints. The problems with the singular Hessian that is symmetric, positive definite on the null space of the equality constraint matrix are considered. The inner linear systems are solved by the projected conjugate gradient method preconditioned by oblique projectors. Numerical experiments include large-scale problems arising from the TFETI domain decomposition method applied for solving the Stokes flow with the stick-slip boundary condition.
       
  • Modelling fracture in heterogeneous materials on HPC systems using a
           hybrid MPI/Fortran coarray multi-scale CAFE framework
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): A. Shterenlikht, L. Margetts, L. Cebamanos A 3D multi-scale cellular automata finite element (CAFE) framework for modelling fracture in heterogeneous materials is described. The framework is implemented in a hybrid MPI/Fortran coarray code for efficient parallel execution on HPC platforms. Two open source BSD licensed libraries developed by the authors in modern Fortran were used: CGPACK, implementing cellular automata (CA) using Fortran coarrays, and ParaFEM, implementing finite elements (FE) using MPI. The framework implements a two-way concurrent hierarchical information exchange between the structural level (FE) and the microstructure (CA). MPI to coarrays interface and data structures are described. The CAFE framework is used to predict transgranular cleavage propagation in a polycrystalline iron round bar under tension. Novel results enabled by this CAFE framework include simulation of progressive cleavage propagation through individual grains and across grain boundaries, and emergence of a macro-crack from merging of cracks on preferentially oriented cleavage planes in individual crystals. Nearly ideal strong scaling up to at least tens of thousands of cores was demonstrated by CGPACK and by ParaFEM in isolation in prior work on Cray XE6. Cray XC30 and XC40 platforms and CrayPAT profiling were used in this work. Initially the strong scaling limit of hybrid CGPACK/ParaFEM CAFE model was 2000 cores. After replacing all-to-all communication patterns with the nearest neighbour algorithms the strong scaling limit on Cray XC30 was increased to 7000 cores. TAU profiling on non-Cray systems identified deficiencies in Intel Fortran 16 optimisation of remote coarray operations. Finally, coarray synchronisation challenges and opportunities for thread parallelisation in CA are discussed.
       
  • Cloud agnostic Big Data platform focusing on scalability and
           cost-efficiency
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): Róbert Lovas, Enikő Nagy, József Kovács Nowadays a significant part of the cloud applications processes a large amount of data to provide the desired analytics, simulation and other results. Cloud computing is becoming a widely used IT model to address the needs of many scientific and commercial Big Data applications. In this paper, we present a Hadoop platform deployment method for various cloud infrastructures with the Occopus cloud orchestrator tool. Our automated solution provides an easy-to-use, portable and scalable way to deploy the popular Hadoop platform with the main goal to avoid vendor locking issues, i.e. there is no dependency on any cloud provider prepared and offered virtual machine image or “black-box” Platform-as-a-Service mechanism. The paper presents promising performance measurements results and cost analysis.
       
  • Transformations of Arm-Z modular manipulator with Particle Swarm
           Optimization
    • Abstract: Publication date: Available online 27 June 2018Source: Advances in Engineering SoftwareAuthor(s): Machi Zawidzki, Jacek Szklarski A novel concept of hyper-redundant, snake-like manipulator is presented. It is based on the reconfigurable modular construction system–Arm-Z (AZ). AZ is comprised of linearly joined congruent modules with possibility of relative twist. AZ is an Extremely Modular System, i.e. it is composed of a single basic unit and allows for creating free-form shapes. Required level of usefulness and efficiency are among the most challenging design aspects of such reconfigurable systems. Here AZ is considered in the context of kinematics of robotic arms. In general, due to its highly non-linear nature, it is very difficult to find transitions between given states (configurations), especially under realistic environmental and structural constraints. As a way to control the manipulator, an implementation of Particle Swarm Optimization (PSO) for finding transitions between AZ states in realistic scenarios is proposed. Four practical examples are presented which are variations of two distinct problems: bending of a hexagonal AZ in a narrow slot (strong environmental constraints), and reaching a given point in 3D space by the tip of dodecagonal AZ (acting as a robotic arm). The problem of AZ transformation has been defined as a multi-objective optimization. The methodology is general with no restrictions to the objective function. Since the problem is strongly non-linear, in order to cover large space of potential solutions, the algorithm runs for a relatively large number of random initial swarms. This task was distributed on a computer cluster. Although the nature of AZ reconfiguration is discrete, the optimization algorithm is continuous.
       
  • Parallel implementation of hyper-dimensional dynamical particle system on
           CUDA
    • Abstract: Publication date: Available online 7 April 2018Source: Advances in Engineering SoftwareAuthor(s): Jan Mašek, Miroslav Vořechovský The presented paper deals with possible approaches to parallel implementation of solution of a hyper-dimensional dynamical particle system. The proposed implementation approaches are generally applicable for similar particle systems of interest in various research and engineering fields. The original motivation for the present work was a simulation of particles that represent a space-filling design to be optimized for further use in design of experiments. Due to the underlying purpose of this particle system, the dimension of the particle system of interest is considered to be entirely arbitrary. Such a hyper-dimensional space is further folded into a periodically repeated domain.The theoretical background of the proposed particle system is provided along with the derivation of equations of motion of the dynamical system. As the complexity of the system is not limited by the number of particles nor the number of dimensions, the possibilities of utilizing the GPGPU platform are more restricted in comparison with today’s fast parallel implementations of common particle systems.Two distinct approaches to parallel implementation are presented, one aiming at a generalized usage of the fast on-chip resources, the other entirely relying on the GPU’s on-board global memory. Despite unambiguous mutual differences in their performance, both parallel implementations deliver major speedup compared to the single-thread CPU solution as well as a better scaling of execution time when increasing both the number of particles and dimensions.
       
  • Modelling of nitrogen leaching from watersheds with large drained peat
           areas
    • Abstract: Publication date: Available online 23 March 2018Source: Advances in Engineering SoftwareAuthor(s): Anatoli Vassiljev, Katrin Kaur, Ivar Annus The SOIL and MACRO models with different versions of SOILN initially developed for small field-scales were used to simulate the water flow and nitrate N concentrations in two watersheds in Estonia that contain large areas of peat soils. Monitoring data show that nitrogen concentrations tend to increase in some rivers even where the human activity is very low. This may be connected to soil self-degradation processes taking place in drained peat soils where it is difficult to use most of the hydrological models. Results show that SOIL, MACRO and SOILN may be successfully applied at the watershed scale to model the water quantity and quality on watersheds with high content of peat soils. The analysis revealed that the nitrate nitrogen level trends depend considerably on the meteorological conditions.
       
  • Parallel two-stage algorithms for solving the PageRank problem
    • Abstract: Publication date: Available online 13 March 2018Source: Advances in Engineering SoftwareAuthor(s): Héctor Migallón, Violeta Migallón, José Penadés In this work we present parallel algorithms based on the use of two-stage methods for solving the PageRank problem as a linear system. Different parallel versions of these methods are explored and their convergence properties are analyzed. The parallel implementation has been developed using a mixed MPI/OpenMP model to exploit parallelism beyond a single level. In order to investigate and analyze the proposed parallel algorithms, we have used several realistic large datasets. The numerical results show that the proposed algorithms can speed up the time to converge with respect to the parallel Power algorithm and behave better than other well-known techniques.
       
  • CUDA accelerated implementation of parallel dynamic relaxation
    • Abstract: Publication date: Available online 8 March 2018Source: Advances in Engineering SoftwareAuthor(s): P. Iványi The dynamic relaxation method has been widely used for the design and analysis of cable-membrane structures. The method iteratively determines a static solution and it has already been parallelized with the MPI environment to speed up the analysis process. This paper discusses a new parallelization approach, which is programmed with the NVIDIA CUDA API and executed on GPU systems. Since a GPU system has a large number of cores and a separate memory from the computer therefore the original dynamic relaxation method has to be reorganized. The paper also discusses the performance measurements of the dynamic relaxation method on GPU systems.
       
  • Comparative studies of metamodeling and AI-Based techniques in damage
           detection of structures
    • Abstract: Publication date: Available online 6 March 2018Source: Advances in Engineering SoftwareAuthor(s): Ramin Ghiasi, Mohammad Reza Ghasemi, Mohammad Noori Despite advances in computer capacity, the enormous computational cost of running complex engineering simulations makes it impractical to rely exclusively on simulation for the purpose of structural health monitoring. To cut down the cost, surrogate models, also known as metamodels, are constructed and then used in place of the actual simulation models. In this study, structural damage detection is performed using two approaches. In both cases ten popular metamodeling techniques including Back-Propagation Neural Networks (BPNN), Least Square Support Vector Machines (LS-SVMs), Adaptive Neural-Fuzzy Inference System (ANFIS), Radial Basis Function Neural network (RBFN), Large Margin Nearest Neighbors (LMNN), Extreme Learning Machine (ELM), Gaussian Process (GP), Multivariate Adaptive Regression Spline (MARS), Random Forests and Kriging are used and the comparative results are presented. In the first approach, by considering dynamic behavior of a structure as input variables, ten metamodels are constructed, trained and tested to detect the location and severity of damage in civil structures. The variation of running time, mean square error (MSE), number of training and testing data, and other indices for measuring the accuracy in the prediction are defined and calculated in order to inspect advantages as well as the shortcomings of each algorithm. The results indicate that Kriging and LS-SVM models have better performance in predicting the location/severity of damage compared with other methods. In the second approach, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the MSEBI of structural elements is evaluated using a properly trained surrogate model. The results indicate that after determining the damage location, the proposed solution method for damage severity detection leads to significant reduction of computational time compared to finite element method. Furthermore, engaging colliding bodies optimization algorithm (CBO) by efficient surrogate model of finite element (FE) model, maintains the acceptable accuracy of damage severity detection.
       
  • Static load estimation using artificial neural network: Application on a
           wing rib
    • Abstract: Publication date: Available online 7 February 2018Source: Advances in Engineering SoftwareAuthor(s): Samson B. Cooper, Dario DiMaio This paper presents a novel approach to predicting the static load on a large wing rib in the absence of load cells. A Finite Element model of the wing rib was designed and calibrated using measured data obtained from static experimental test. An Artificial Neural Network (ANN) model was developed to predict the static load applied on the wing rib, this was achieved by using random data and strain values obtained from the static test as input parameters. A number of two layer feed-forward networks were designed and trained in MATLAB using the back-propagation algorithm. The first set of Neural Networks (NN) were trained using random data as inputs, measured strain values were introduced as input into the already trained neural network to access the training algorithm and quantify the accuracy of the static load prediction produced by the trained NN. In addition, a procedure that combines ANN and FE modelling to create a hybrid inverse problem analysis and load monitoring tool is presented. The hybrid approach is based on using trained NN to estimate the applied load from a known FE structural response. Results obtained from this research proves that using an ANN to identify loads is feasible and a well-trained NN shows fast convergence and high degree of accuracy of 92% in the load identification process. Finally, additional trained network results showed that ANN as an inverse problem solver can be used to estimate the load applied on a structure once the load-response relationship has been identified.
       
  • A new nodal outflow function for head-dependent modelling of water
           distribution networks
    • Abstract: Publication date: Available online 19 January 2007Source: Advances in Engineering SoftwareAuthor(s): T.T. Tanyimboh, A.B. TemplemanThis article has been removed consistent with Elsevier Policy on Article Withdrawal. The Publisher apologises for any inconvenience this may cause.
       
 
 
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