1,721,100 research outputs found
METALS
No full textAims
Metals (ISSN 2075-4701) is an open access journal of related scientific research and technology development. It publishes reviews, regular research papers (articles) and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
Metals provides a forum for publishing papers which advance the in-depth understanding of the relationship between the structure, the properties or the functions of all kinds of metals
Journal of Marine Science and Engineering
No full textJournal of Marine Science and Engineering (JMSE; ISSN 2077-1312) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to marine science and engineering. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possibl
Predicting the Temperature-Dependent Tensile properties of Polyphenylsulfone using a Machine learning approach
No full textAfter 200 years of their birth, synthetic polymers are present in over 60 primary forms. Many are largely known and spread, others less common and investigated, such as Polyphenylsulfone (PPSU) which, on the contrary, offers multiple applications. Among them, in particular, many concerns the use of the PPSU at (cold or hot) temperature. But experiments with its temperature-dependent characterization are very few and limited to specific formulations. Machine learning algorithms can fill the gap providing accurate predictions. Specifically, an unsupervised classification was here used for clustering material data with the scope to recognize patterns between PPSU up to the selection of similarities respect to a polymer as reference. Then, a supervised regression was used to predict temperature-dependent tensile properties. A high level of accuracy was achieved, up to 99% in terms of coefficient of determination. This is probably the first time that data regarding the mechanical behavior of PPSU were derived from an approach based on artificial intelligence and machine learning
GEOMETRY OPTIMIZATION BY FEM SIMULATION OF THE AUTOMATIC CHANGING GEAR
No full textElectro-mechanic devices for the automatic changing of gear were tested by company using the same accelerated life testing procedures in different stages of the product development. All the tested prototypes satisfied the experimental conditions for accelerated life tests, while 50% of components coming from the first sample of serial production showed crack phenomena during the same testing procedure. This situation can be related to a large number of undefined factors: from the variability of material proprieties or in production process parameters to accidentally different conditions in testing. The complete list of all the possibilities of variance was extremely complex to be defined, recognized and verified by new sets of experimental tests. FEM calculation permitted a fast simulation of the component response under the complex experimental testing conditions, modifying the interpretation of some experimental results and correctly driving the designer toward quick improvements of product
Investigating the Material Properties of Nodular Cast Iron from a Data Mining Perspective
Full text linkCast iron is a very common and useful metal alloy, characterized by its high carbon content (>4%) in the allotropic state of graphite. The correct shape and distribution of graphite are essential for ensuring that the material has the right properties. The present investigation examines the metallurgical and mechanical characterization of a spheroidal (nodular) cast iron, an alloy that derives its name and its excellent properties from the presence of graphite as spheroidal nodules. Experimental data are detected and considered from a data mining perspective, with the scope to extract new and little-known information. Specifically, a machine learning toolkit (i.e., Orange Data Mining) is used as a means of permitting supervised learners/classifiers (such as neural networks, k-nearest neighbors, and many others) to understand related metallurgical and mechanical features. An accuracy rate of over 90% can be considered as representative of the method. Finally, interesting considerations emerged regarding the dimensional effect on the variation in the solidification rates, microstructure, and properties
LIGHTENING STRUCTURES BY METAL REPLACEMENT: FROM TRADITIONAL GYM EQUIPMENT TO AN ADVANCED FIBER-REINFORCED COMPOSITE EXOSKELETON
Full text linkA redesign procedure used for introducing new functional properties in innovative gym equipment is here reported. It is based on a metal replacement action where a tempered steel was firstly replaced by an aluminum alloy and then by high strength-to-weight fiber-reinforced polymers. The effect of fiber properties (as strength and volume ratio) and plies stacking sequences (as thicknesses and orientation) were investigated. Numerical analyses, done by Ansys ACP, allowed evaluating the stress-strain behavior in realistic boundaries and quasi-static loads, comparing materials and layouts in terms of stiffness. The single-layered shell method with additional integration points was preferred as a technique for discretizing composite laminates. Maximum Principal Stress and Maximum Distortion Energy (Tsai-Hill) were applied as anisotropic failure criteria. Changes in geometry were also considered given their relevant effects on parts and processes. Specifically, this paper is focused on a representative component of the main kinematic chain (the ‘forearm’) and details the different redesign phases for that part. The chosen solution consisted of 14 layers of unidirectional and bidirectional carbon fiber-reinforced pre-pregs, offering a 68 % weight reduction with respect to a solid aluminum component with equal stiffness. The part was manufactured by hand lay-up and cured in autoclave. This redesign practice was extended to the rest of the equipment allowing its transformation into an exoskeleton
Advances in Design by Metallic Materials: Synthesis, Characterization, Simulation and Applications
Full text linkMetals have exerted a significant influence throughout the history of mankind, so much so that the different periods of development have often been marked with the name of some material: bronze age and iron age [...
Investigating the crash-box-structure’s ability to absorb energy
No full textProtection under external loads often requires the use of energy absorbers. They are designed to absorb impact energy in a controlled way protecting the structures, as well as their possible occupants. This study examines the crushing performances of thin structures, made in sheet metal, as their shape and thickness vary. Three crash-box-structures were considered for their geometries (i.e. rectangular, rectangular with two inclined walls, and truncated pyramidal structures) with two variations in thicknesses (i.e. s = 1 and 2 mm). Their elastic-plastic behaviour under low-speed compression was analysed by experiments and simulations. The collision force reduction and energy absorption were compared. Based on outcomes a new absorber was developed and used for improving safety in the case of an innovative ultra-light solar racing vehicle
Enhanced Predictive Model for the Mechanical Response of Compression-Loaded Slender Structures
Full text linkThe study of the behavior of thin metal sheets subjected to external loads has always been a matter of great interest due to its numerous theoretical and practical implications. The present analysis aims to investigate how to improve the predictions offered by a numerical model based on the finite element method by considerations on the material properties. Specifically, different modeling alternatives are compared, assessing these choices both with the similar assumptions made by other researchers in the past and with measurements from our own experimentation. The case under consideration consists of a slender, aluminum crash-box structure (a bumper) with a truncated pyramid shape subjected to a concentrated load on the top (axial crushing) up to a 46% reduction in its height. The system is characterized by high deformations (>15%) and large displacements. This presents a complex situation with various nonlinear effects, where the chosen assumptions in material modeling can have significant implications for the results, both in terms of accuracy and computational time. Among the investigated aspects, of no less importance are those related to the appropriate modeling of the elasto-plastic-hardening behavior of the metallic material
Investigating the resistance of reinforced barriers to high velocity projectiles
No full textThe resistance of concrete barriers to high velocity projectile impact from firearms is a research topic that has been of interest for quite some time, with the first known study going back to the mid-18th century. Despite this long history, only a very limited number of the test results are available in the public domain due to their sensitive nature and strategic importance. This situation has made the development of precise models for predicting the effects of ballistic impact difficult, despite the recent availability of highly refined and powerful calculation tools. Many researchers are still convinced that a validated methodology does not currently exist for this type of problem due to the number of uncertainties. Within this context, the objective of the present work is to study projectile impact on barriers made of reinforced concrete with explicit Finite Element (FE) simulations. In particular, this paper presents a FE analysis that considers the full range of projectile class as defined in the ballistic standards. Results from simulation are also compared with experiments
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