Research

19 pages, 6090 KiB

Open AccessArticle

Finite Element Modeling and Experimental Validation of AA 5052-H34 Machining: A Comprehensive Study on Chip Morphology and Temperature Analysis

by Abbas Farhan Jawad Al-Khafaji, Behnam Davoodi and Seyed Ali Niknam

Appl. Mech. 2024, 5(1), 102-120; https://doi.org/10.3390/applmech5010007 - 25 Feb 2024

Viewed by 531

Abstract

An understanding of the dynamic behavior of materials plays a crucial role in machining improvement. According to the literature on this issue, one of the alloys whose dynamic behavior has been investigated less is AA 5052-H34, despite its numerous industrial applications. Using finite [...] Read more.

An understanding of the dynamic behavior of materials plays a crucial role in machining improvement. According to the literature on this issue, one of the alloys whose dynamic behavior has been investigated less is AA 5052-H34, despite its numerous industrial applications. Using finite element (FE) modeling greatly reduces machining research costs. This research delved into the dynamic behavior modeling of AA 5052-H34 during dry-turning FE simulation. The dynamic behavior of AA 5052-H34 was achieved using the Johnson–Cook (J-C) constitutive equation, which was calculated using the uniaxial tensile and Split-Hopkinson pressure bar (SHPB) tests. To confirm the accuracy of the material model, these SHPB tests were then simulated in Abaqus. The J-C constitutive equation, paired with a J-C damage criterion, was employed in a chip formation and cutting temperature simulation. It was found that the feed rate significantly influences the dynamic behavior of AA 5052-H34. The thickness and morphology of the chip were investigated. The experimental and numerical chip thicknesses showed a direct relationship with the feed rate. The simulation temperature was also analyzed, and, as expected, it showed an upward trend with increasing cutting speed and feed rate. Then, the accuracy of the proposed FE simulation was confirmed by the agreement of the experimental and simulation results. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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21 pages, 8060 KiB

Open AccessArticle

Modeling De-Coring Tools with Coupled Multibody Simulation and Finite Element Analysis

by Melvin Mariadass, Roman Binder, Florian Ettemeyer, Wolfram Volk and Daniel Günther

Appl. Mech. 2023, 4(4), 1206-1226; https://doi.org/10.3390/applmech4040062 - 06 Dec 2023

Viewed by 914

Abstract

De-coring is an essential process in the casting process chain, determining the quality and cost of production. In this study, a coupled multibody system (MBS) and finite element modeling (FEM) technique is presented to study the mechanical loads during the de-coring process. The [...] Read more.

De-coring is an essential process in the casting process chain, determining the quality and cost of production. In this study, a coupled multibody system (MBS) and finite element modeling (FEM) technique is presented to study the mechanical loads during the de-coring process. The removal of cast-in sand cores from the inner regions of the cast part by de-coring or knocking out is a complex process with dynamic loads. Currently, the process relies upon empirical knowledge and tests. Inorganic sand cores pose additional challenges in the success of the de-coring process. Increasing complexity in geometry and stringent environmental regulations compel a predictive process in the earlier stages of design. Predicting the process’ success is challenged by the dynamic non-linearities of the system. The dynamic characteristics and the interaction between hammer and casting were studied here for the first time using an industrial-based test rig, and a novel modeling approach was formulated. The results of the developed model are in good compliance with the experiments. The methodology presented in this study can be used to include a varying number of hammers and loads. The proposed approach presents the possibility to discretize the process and qualitatively assess the process parameters for optimization. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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16 pages, 4570 KiB

Open AccessArticle

A Novel Method of Jacobian Contours to Evaluate the Influence Line in Statically Determinate Structures

by Anis Sulejmani, Odhisea Koça, Klodian Dhoska, Mohammad Gheibi and Reza Moezzi

Appl. Mech. 2023, 4(4), 1172-1187; https://doi.org/10.3390/applmech4040060 - 30 Nov 2023

Cited by 2 | Viewed by 837

Abstract

Influence lines are indispensable tools for visualizing and analyzing the dynamic variations in force factors induced by external loads within structural systems. Among these methods, the energetic approach stands as a widely employed technique, rooted in the fundamental principle of work done by [...] Read more.

Influence lines are indispensable tools for visualizing and analyzing the dynamic variations in force factors induced by external loads within structural systems. Among these methods, the energetic approach stands as a widely employed technique, rooted in the fundamental principle of work done by changing forces. It enables engineers to transform intricate structural analysis problems into manageable ones by exploring the first derivatives of the radius vector, which represent infinitesimal velocity or displacement. This methodology seamlessly interweaves concepts such as carrier motion, relative motion, and the construction of mechanisms, bringing fresh perspectives to the analysis of influence lines. In this article, we explore the nuances of these novel methods within the domain of mechanism theory. Through comprehensive elaboration and analysis, we elucidate the underlying principles and practical applications of Jacobian contours. Crucially, we introduce a straightforward, rapid, and programmable approach, promising to revolutionize influence line determination in structural engineering. This method bridges the gap between theory and practice, offering the potential to elevate the accuracy, efficiency, and adaptability of influence line analysis. As such, it represents a significant advancement in the field of structural and applied mechanics, with broad-reaching implications for engineering practice. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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13 pages, 16658 KiB

Open AccessArticle

Experimental Investigation of Unidirectional Glass-Fiber-Reinforced Plastics under High Strain Rates

by Sören Bieler, Sebastian Haller, Robert Brandt and Kerstin Weinberg

Appl. Mech. 2023, 4(4), 1127-1139; https://doi.org/10.3390/applmech4040058 - 26 Oct 2023

Cited by 1 | Viewed by 1019

Abstract

When a vehicle leaves the road, crash barriers stop it and prevent significant damage to the vehicle, its environment, and the occupants. Typically, such protection systems are made of simple steel, but fiber-reinforced composites can efficiently absorb and dissipate the impact energy at [...] Read more.

When a vehicle leaves the road, crash barriers stop it and prevent significant damage to the vehicle, its environment, and the occupants. Typically, such protection systems are made of simple steel, but fiber-reinforced composites can efficiently absorb and dissipate the impact energy at high-risk locations. In order to design such protective systems, material parameters under dynamic loading are necessary. Here, split Hopkinson pressure bar tests with unidirectional glass-fiber-reinforced epoxy of 58% glass fiber content are performed. The elastic response at strain rates between 300/s and 700/s in the loading direction parallel and perpendicular to the fiber is determined. From the measured data, a model of the time dependence of the elastic modulus is derived to enable the design engineer to lay out protective systems made of such GFRPs. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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12 pages, 1596 KiB

Open AccessArticle

Generation of Realistic Cut-In Maneuvers to Support Safety Assessment of Advanced Driver Assistance Systems

by Zafer Kayatas, Dieter Bestle, Pascal Bestle and Robin Reick

Appl. Mech. 2023, 4(4), 1066-1077; https://doi.org/10.3390/applmech4040054 - 28 Sep 2023

Viewed by 1337

Abstract

Advanced Driver Assistance Systems (ADASs) attract constantly growing attention from academics and industry as more and more vehicles are equipped with such technology. Level-3 ADASs, like the DRIVE PILOT from Mercedes-Benz AG, are expected to appear more and more on the market in [...] Read more.

Advanced Driver Assistance Systems (ADASs) attract constantly growing attention from academics and industry as more and more vehicles are equipped with such technology. Level-3 ADASs, like the DRIVE PILOT from Mercedes-Benz AG, are expected to appear more and more on the market in the next few years. However, automated driving raises new challenges for the system validation required for series approval. The replacement of a human driver as control instance expands the range of variants to be validated and verified. The scenario-based validation approach meets these challenges by simulating only specific safety-critical driving scenarios using software-in-the-loop simulation. According to the current state of the art, various safety-relevant driving scenarios are parameterized as idealized maneuvers which, however, requires a great modeling effort, and at the same time, such simplifications may bias the safety assessment. Therefore, a novel approach using artificial intelligence methods is taken here to generate more realistic driving scenarios. Namely, a generative model based on a variational autoencoder is trained with real-world data and then used to generate trajectories for a specific driving maneuver. Through a comprehensive analysis of the synthetic trajectories, it becomes clear that the generative model can learn and replicate relevant properties of real driving data as well as their probabilistics much better than the mathematical models used so far. Furthermore, it is proven that both the statistical properties and the time characteristics are almost equal to those of the input data. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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28 pages, 12635 KiB

Open AccessArticle

A Comparative Analysis of the Response-Tracking Techniques in Aerospace Dynamic Systems Using Modal Participation Factors

by Michelle Guzman Nieto, Sandeep Suresh Babu, Mostafa S. A. ElSayed and Abdel-Hamid Ismail Mourad

Appl. Mech. 2023, 4(4), 1038-1065; https://doi.org/10.3390/applmech4040053 - 26 Sep 2023

Viewed by 1231

Abstract

Mechanical structural systems are subject to multiple dynamic disturbances during service. While several possible scenarios can be examined to determine their design loading conditions, only a relatively small set of such scenarios is considered critical. Therefore, only such particular deterministic set of critical [...] Read more.

Mechanical structural systems are subject to multiple dynamic disturbances during service. While several possible scenarios can be examined to determine their design loading conditions, only a relatively small set of such scenarios is considered critical. Therefore, only such particular deterministic set of critical load cases is commonly employed for the structural design and optimization. Nevertheless, during the design and optimization stages, the mass and stiffness distributions of such assemblies vary, and, in consequence, their dynamic response also varies. Thus, it is important to consider the variations in the dynamic loading conditions during the design-and-optimization cycles. This paper studies the modal participation factors at length and proposes an alternative to the current point-wise treatment of the dynamic equations of motion of flexible bodies during design optimization. First, the most relevant-to-structural-dynamics definitions available in the literature are reviewed in depth. Second, the analysis of those definitions that have the potential to be adopted as point-wise constraint equations during structural optimization is extended. Finally, a proof of concept is presented to demonstrate the usability of each definition, followed by a case study in which the potential advantages of the proposed extended analysis are shown. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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16 pages, 5831 KiB

Open AccessArticle

Analysis of Acid Diffusion Effects on Physical Properties of Polymer Composites: A Combined Study of Mechanical and Electrical Characterization

by Sebastian Tamayo-Vegas, Khalid Lafdi, Mostapha Tarfaoui, Khalil K. Lafdi and Mohamed Daly

Appl. Mech. 2023, 4(3), 974-989; https://doi.org/10.3390/applmech4030050 - 31 Aug 2023

Viewed by 1048

Abstract

In this study, we examined the impact of carbon nanotube (CNT) concentration on the mechanical properties of epoxy/CNT composites under acid exposure. Samples with varying CNT concentrations (0% to 5%) were fabricated and characterized using dynamic mechanical analysis (DMA) and nanoindentation. Beyond the [...] Read more.

In this study, we examined the impact of carbon nanotube (CNT) concentration on the mechanical properties of epoxy/CNT composites under acid exposure. Samples with varying CNT concentrations (0% to 5%) were fabricated and characterized using dynamic mechanical analysis (DMA) and nanoindentation. Beyond the percolation threshold, the composites experienced decreased bulk mechanical properties due to CNT agglomeration. Acid exposure for one week and one month revealed a gradient of properties from the sample’s skin to its core. Overall, the composites exhibited modified physical properties, with degradation influenced by the CNT concentration. Higher concentrations acted as barriers but also created pathways for acid diffusion through pores surrounding CNT agglomerates. The agreement between nanoindentation and vector network analyzer (VNA) measurements further supported our findings. This convergence of mechanical and electromagnetic characterization techniques holds promise for wireless structural health monitoring (SHM) applications. Our study enhances the understanding of epoxy/CNT composites for SHM applications. The relationship between CNT concentration, acid exposure, and mechanical properties guides material selection and the development of real-time damage-detection techniques. Integrating multiple measurement techniques, as demonstrated by the agreement between nanoindentation and VNA data, provides a comprehensive understanding of structural behavior, improving SHM practices. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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26 pages, 3742 KiB

Open AccessArticle

Analytical and Numerical Investigation of Fatigue Life in Rectangular Plates with Opposite Semicircular Edge Single Notches

by Kristaq Hazizi, Mohammad Ghaleeh and Shafqat Rasool

Appl. Mech. 2023, 4(3), 948-973; https://doi.org/10.3390/applmech4030049 - 31 Aug 2023

Viewed by 1370

Abstract

This study undertakes an investigation into the fatigue life of carbon steel specimens with opposite semicircular edge notches using a combined approach based on experimental and numerical analysis. The study emphasises the determination of stress concentration factors (SCFs) for these notches based on [...] Read more.

This study undertakes an investigation into the fatigue life of carbon steel specimens with opposite semicircular edge notches using a combined approach based on experimental and numerical analysis. The study emphasises the determination of stress concentration factors (SCFs) for these notches based on S-N curves of carbon steel, employing a comprehensive method to evaluate their impacts on fatigue performance. Both experimental and numerical methods are applied to understand the influence of notches on fatigue characteristics, yielding insights into potential failure modes and opportunities for design enhancement. The research deepens our comprehension of fatigue mechanics in carbon steel structures, offering valuable perspectives regarding structural engineering and design refinement. The outcomes highlight the significance of integrating experimental testing and numerical simulations to carry out an exhaustive investigation of fatigue behaviour in notched specimens. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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31 pages, 8231 KiB

Open AccessArticle

Explainable Artificial Intelligence (XAI) and Supervised Machine Learning-based Algorithms for Prediction of Surface Roughness of Additively Manufactured Polylactic Acid (PLA) Specimens

by Akshansh Mishra, Vijaykumar S. Jatti, Eyob Messele Sefene and Shivangi Paliwal

Appl. Mech. 2023, 4(2), 668-698; https://doi.org/10.3390/applmech4020034 - 12 May 2023

Cited by 4 | Viewed by 2406

Abstract

Structural integrity is a crucial aspect of engineering components, particularly in the field of additive manufacturing (AM). Surface roughness is a vital parameter that significantly influences the structural integrity of additively manufactured parts. This research work focuses on the prediction of the surface [...] Read more.

Structural integrity is a crucial aspect of engineering components, particularly in the field of additive manufacturing (AM). Surface roughness is a vital parameter that significantly influences the structural integrity of additively manufactured parts. This research work focuses on the prediction of the surface roughness of additive-manufactured polylactic acid (PLA) specimens using eight different supervised machine learning regression-based algorithms. For the first time, explainable AI techniques are employed to enhance the interpretability of the machine learning models. The nine algorithms used in this study are Support Vector Regression, Random Forest, XGBoost, AdaBoost, CatBoost, Decision Tree, the Extra Tree Regressor, the Explainable Boosting Model (EBM), and the Gradient Boosting Regressor. This study analyzes the performance of these algorithms to predict the surface roughness of PLA specimens, while also investigating the impacts of individual input parameters through explainable AI methods. The experimental results indicate that the XGBoost algorithm outperforms the other algorithms with the highest coefficient of determination value of 0.9634. This value demonstrates that the XGBoost algorithm provides the most accurate predictions for surface roughness compared with other algorithms. This study also provides a comparative analysis of the performance of all the algorithms used in this study, along with insights derived from explainable AI techniques. Full article

(This article belongs to the Special Issue Early Career Scientists’ (ECS) Contributions to Applied Mechanics)

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