Search results for: additive parameter

Authors: Sofiane Bououden, Ilyes Boulkaibet

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In this paper, a robust model predictive controller (RMPC) for uncertain nonlinear system under actuator saturation is designed to control a DC-DC buck converter in PV pumping application, where this system is subject to actuator saturation and parameter uncertainties. The considered nonlinear system contains a linear constant part perturbed by an additive state-dependent nonlinear term. Based on the saturating actuator property, an appropriate linear feedback control law is constructed and used to minimize an infinite horizon cost function within the framework of linear matrix inequalities. The proposed approach has successfully provided a solution to the optimization problem that can stabilize the nonlinear plants. Furthermore, sufficient conditions for the existence of the proposed controller guarantee the robust stability of the system in the presence of polytypic uncertainties. In addition, the simulation results have demonstrated the efficiency of the proposed control scheme.

Keywords: PV pumping system, DC-DC buck converter, robust model predictive controller, nonlinear system, actuator saturation, linear matrix inequality

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Authors: Wadea Ameen, Abdulrahman Al-Ahmari, Osama Abdulhameed

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Electron beam melting (EBM) is one of the modern additive manufacturing (AM) technologies. In EBM, the electron beam melts metal powder into a fully solid part layer by layer. Since EBM is a new technology, most designers are unaware of the capabilities and the limitations of EBM technology. Also, many engineers are facing many challenges to utilize the technology because of a lack of design rules for the technology. The aim of this study is to identify the capabilities and the limitations of EBM technology in fabrication of small features and overhang structures and develop a design rules that need to be considered by designers and engineers. In order to achieve this objective, a series of experiments are conducted. Several features having varying sizes were designed, fabricated, and evaluated to determine their manufacturability limits. In general, the results showed the capabilities and limitations of the EBM technology in fabrication of the small size features and the overhang structures. In the end, the results of these investigation experiments are used to develop design rules. Also, the results showed the importance of developing design rules for AM technologies in increasing the utilization of these technologies.

Keywords: additive manufacturing, design for additive manufacturing, electron beam melting, self-supporting overhang

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Authors: Freddy Patricio Moncayo-Matute, Pablo Gerardo Peña-Tapia, Vázquez-Silva Efrén, Paúl Bolívar Torres-Jara, Diana Patricia Moya-Loaiza, Gabriela Abad-Farfán

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This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure.

Keywords: surgical planning, additive manufacturing, rapid prototyping, fused deposition modeling, custom anatomical model

Procedia PDF Downloads 66

Authors: Sadman Durlov, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Md Najmus Salehin, Nora Shayesteh Ameri

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In the field of additive manufacturing, tungsten stands out for its exceptional resistance to high temperatures, making it an ideal candidate for use in extreme conditions. However, its inherent brittleness and vulnerability to thermal cracking pose significant challenges to its manufacturability. This study explores the microstructural evolution of tungsten processed through layer-wise rolling in laser powder bed fusion additive manufacturing, utilizing a comprehensive approach that combines advanced simulation techniques with empirical research. We aim to uncover the complex processes of plastic deformation and microstructural transformations, with a particular focus on the dynamics of grain size, boundary evolution, and phase distribution. Our methodology employs a combination of simulation and experimental data, allowing for a detailed comparison that elucidates the key mechanisms influencing microstructural alterations during the rolling process. This approach facilitates a deeper understanding of the material's behavior under additive manufacturing conditions, specifically in terms of deformation and recrystallization. The insights derived from this research not only deepen our theoretical knowledge but also provide actionable strategies for refining manufacturing parameters to improve the tungsten components' mechanical properties and functional performance. By integrating simulation with practical experimentation, this study significantly enhances the field of materials science, offering a robust framework for the development of durable materials suited for challenging operational environments. Our findings pave the way for optimizing additive manufacturing techniques and expanding the use of tungsten across various demanding sectors.

Keywords: additive manufacturing, layer wise rolling, refractory materials, in-situ microstructure modifications

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Nadama Kumar, P. Parthiban, T. Niranjan

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In the present paper, we propose an incorporated approach for 3PL supplier choice that suits the distinctive strategic needs of the outsourcing organization in southern part of India. Four fundamental criteria have been used in particular Performance, IT, Service and Intangible. These are additionally subdivided into fifteen sub-criteria. The proposed strategy coordinates Structural Equation Modeling (SEM) and Non-additive Fuzzy Integral strategies. The presentation of fluffiness manages the unclearness of human judgments. The SEM approach has been used to approve the determination criteria for the proposed show though the Non-additive Fuzzy Integral approach uses the SEM display contribution to assess a supplier choice score. The case organization has a exclusive vertically integrated assembly that comprises of several companies focusing on a slight array of the value chain. To confirm manufacturing and logistics proficiency, it significantly relies on 3PL suppliers to attain supply chain superiority. However, 3PL supplier selection is an intricate decision-making procedure relating multiple selection criteria. The goal of this work is to recognize the crucial 3PL selection criteria by using the non-additive fuzzy integral approach. Unlike the outmoded multi criterion decision-making (MCDM) methods which frequently undertake independence among criteria and additive importance weights, the nonadditive fuzzy integral is an effective method to resolve the dependency among criteria, vague information, and vital fuzziness of human judgment. In this work, we validate an empirical case that engages the nonadditive fuzzy integral to assess the importance weight of selection criteria and indicate the most suitable 3PL supplier.

Keywords: 3PL, non-additive fuzzy integral approach, SEM, fuzzy

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Authors: Adriana Hernandez-Martinez, Edgar D. Ramon-Raygoza

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Currently, there has been a great interest, during the last years, on graphene due to its lubricant properties on friction and antiwear processes. Likewise, fluorographene has also been gaining renown due to its excellent chemical and physical properties which have been mostly applied in the electronics industry. Nevertheless, its tribological properties haven’t been analyzed thoroughly. In this paper, fluorographene was examined as an extreme pressure additive and the nano lubricant made with a cutting fluid and fluorographene in the range of 0.01-0.5% wt, which proved to withstand 53.78% more pounds than the conventional product and 7.12% more than the nano lubricant with graphene in a range between 0.01-0.5% wt. Said extreme pressure test was carried out with a Pin and Vee Block Tribometer following an ASTM D3233A test. The fluorographene used has a low C/F ratio, which reflects a greater presence of atomic fluorine and its low oxygen percentage, supports the substitution of oxygen-containing groups by fluorine. XPS Spectra shows high atomic fluorine content of 56.12%, and SEM analysis details the formation of long and clear crystalline structures, in the fluorographene used.

Keywords: extreme pressure additive, fluorographene, nanofluids, nanolubricant

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Authors: Mary Chriselda A

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This paper deals with the fact that the Hubble's parameter is not constant and tends to vary stochastically with time. This premise has been proven by converting it to a stochastic differential equation using the Ornstein-Uhlenbeck process. The formulated stochastic differential equation is further solved analytically using the Euler and the Kolmogorov Forward equations, thereby obtaining the probability density function using the Fourier transformation, thereby proving that the Hubble's parameter varies stochastically. This is further corroborated by simulating the observations using Python and R-software for validation of the premise postulated. We can further draw conclusion that the randomness in forces affecting the white noise can eventually affect the Hubble’s Parameter leading to scale invariance and thereby causing stochastic fluctuations in the density and the rate of expansion of the Universe.

Keywords: Chapman Kolmogorov forward differential equations, fourier transformation, hubble's parameter, ornstein-uhlenbeck process , stochastic differential equations

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Authors: Liubov Magerramova, Mikhail Petrov, Vladimir Isakov, Liana Shcherbinina, Suren Gukasyan, Daniil Povalyukhin, Olga Klimova-Korsmik, Darya Volosevich

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Aircraft engines are developing along the path of increasing resource, strength, reliability, and safety. The building of gas turbine engine body parts is a complex design and technological task. Particularly complex in the design and manufacturing are the casings of the input stages of helicopter gearboxes and central drives of aircraft engines. Traditional technologies, such as precision casting or isothermal forging, are characterized by significant limitations in parts production. For parts like housing, additive technologies guarantee spatial freedom and limitless or flexible design. This article presents the results of computational and experimental studies. These investigations justify the applicability of additive technologies (AT) to reduce the weight of aircraft housing gearbox parts by up to 32%. This is possible due to geometrical optimization compared to the classical, less flexible manufacturing methods and as-casted aircraft parts with over-insured values of safety factors. Using an example of the body of the input stage of an aircraft gearbox, visualization of the layer-by-layer manufacturing of a part based on thermal deformation was demonstrated.

Keywords: additive technologies, gas turbine engines, topological optimization, synthesis process

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Authors: M. Volpini, D. Alves, A. Horta, M. Borges, P. Reis

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The gait pattern in people that present motor limitations foment the demand for auxiliary locomotion devices. These artifacts for movement assistance vary according to its shape, size and functional features, following the clinical applications desired. Among the ortheses of lower limbs, the ankle-foot orthesis aims to improve the ability to walk in people with different neuromuscular limitations, although they do not always answer patients' expectations for their aesthetic and functional characteristics. The purpose of this study is to explore the possibility of using new design in additive manufacturer to reproduce the shape and functional features of a ankle-foot orthesis in an efficient and modern way. Therefore, this work presents a study about the performance of the mechanical forces through the analysis of finite elements in an ankle-foot orthesis. It will be demonstrated a study of distribution of the stress on the orthopedic device in orthostatism and during the movement in the course of patient's walk.

Keywords: additive manufacture, new designs, orthoses, finite elements

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Authors: Yi Zheng

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Improving formability and mechanical properties have always been one of the challenges in the field of additive manufacturing (AM) of nickel-based superalloys. In this work, the effect of a coaxially coupled alternating magnetic field (AMF) on surface morphology and mechanical properties of plasma arc-based additive manufactured Inconel 718 deposit were investigated. Results show that the Lorentz force induced by AMF strongly alters the flow behavior of the plasma jet and the molten pool, suppressing the tendency of the liquid metal in the molten pool to flow down on the two sides face of the deposit, which in turn remarkably improved the surface accuracy of the thin-walled deposit. Furthermore, the electromagnetic stirring induced by AMF can effectively enhance the convection between the dendrites, which could not only contribute to the formation of finer dendrites but also alleviate the enrichment of the elements (i.e., Nb and Mo) at the solid-liquid interface and inhibits the precipitation of Laves phase. The smallest primary dendritic arm spacing (~13 μm) and lowest Laves phases area fraction (3.12%) were witnessed in the bottom region of the AMF-assisted deposit. The mechanical test confirmed that the deposit's micro-hardness and tensile properties were moderately improved compared with the counterpart without AMF.

Keywords: additive manufacturing, inconel 718, alternating magnetic field, laves phase

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Authors: Bunty Tomar, Shiva S.

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Fabrication of steel and copper-based functionally graded material (FGM) through cold metal transfer-based wire arc additive manufacturing is a novel exploration. Components combining Cu and steel show significant usage in many industrial applications as they combine high corrosion resistance, ductility, thermal conductivity, and wear resistance to excellent mechanical properties. Joining steel and copper is challenging due to the mismatch in their thermo-mechanical properties. In this experiment, a functionally graded material (FGM) structure of pure copper (Cu) and 316L stainless steel (SS) was successfully developed using cold metal transfer-based wire arc additive manufacturing (CMT-WAAM). The interface of the fabricated samples was characterized under optical microscopy, field emission scanning electron microscopy, and X-ray diffraction techniques. Detailed EBSD and TEM analysis was performed to analyze the grain orientation, strain distribution, grain boundary misorientations, and formation of metastable and intermetallic phases. Mechanical characteristics of deposits was also analyzed using tensile and wear testing. This works paves the way to use CMT-WAAM to fabricate steel/copper FGMs.

Keywords: wire arc additive manufacturing (waam), cold metal transfer (cmt), metals and alloys, mechanical properties, characterization

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Authors: Liang Zhao, Chong-quan Zhong

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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

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Authors: Umadevi B., Dinesh P. A., Indira. R., Vinay C. V.

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A mathematical model is developed to study the simultaneous effects of particle drag and slip parameter on the velocity as well as rate of flow in an annular cross sectional region bounded by two eccentric cylinders. In physiological flows this phenomena can be observed in an eccentric catheterized artery with inner cylinder wall is impermeable and outer cylinder wall is permeable. Blood is a heterogeneous fluid having liquid phase consisting of plasma in which a solid phase of suspended cells and proteins. Arterial wall gets damaged due to aging and lipid molecules get deposited between damaged tissue cells. Blood flow increases towards the damaged tissues in the artery. In this investigation blood is modeled as two phase fluid as one is a fluid phase and the other is particulate phase. The velocity of the fluid phase and rate of flow are obtained by transforming eccentric annulus to concentric annulus with the conformal mapping. The formulated governing equations are analytically solved for the velocity and rate of flow. The numerical investigations are carried out by varying eccentricity parameter, slip parameter and drag parameter. Enhancement of slip parameter signifies loss of fluid then the velocity and rate of flow will be decreased. As particulate drag parameter increases then the velocity as well as rate flow decreases. Eccentricity facilitates transport of more fluid then the velocity and rate of flow increases.

Keywords: catheter, slip parameter, drag parameter, eccentricity

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Authors: Adrian Travieso Disotuar, J. Antonio Travieso Rodriguez, Ramon Jerez Mesa, Montserrat Vilaseca

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The effect of the non-vibration-assisted and vibration-assisted ball burnishing on both the surface and mechanical properties of C300 obtained by Selective Laser Melting additive manufacturing technology is studied in this paper. Different vibration amplitudes preloads, and burnishing strategies were tested. A topographical analysis was performed to determine the surface roughness of the different conditions. Besides, micro tensile tests were carried out in situ on Scanning Electron Microscopy to elucidate the post-treatment effects on damaging mechanisms. Experiments show that vibration-assisted ball burnishing significantly enhances mechanical properties compared to the non-vibration-assisted method. Moreover, it was found that the surface roughness was significantly improved with respect to the reference surface.

Keywords: additive manufacturing, ball burnishing, mechanical properties, metals, surface roughness

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Authors: D. Chen, H. Daoud, C. Kreiner, U. Glatzel

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Additive Manufacturing (AM) provides promising opportunities to optimize and to produce tooling by integrating near-contour tempering channels for more efficient cooling. To enhance the properties of the produced tooling using additive manufacturing, prototypes should be produced in short periods. Thereby, this requires a small amount of tailored powders, which either has a high production cost or is commercially unavailable. Hence, in this study, an arc spray atomization approach to produce a tailored metal powder at a lower cost and even in small quantities, in comparison to the conventional powder production methods, was proposed. This approach involves converting commercially available metal wire into powder by modifying the wire arc spraying process. The influences of spray medium and gas pressure on the powder properties were investigated. As a result, particles with smooth surface and lower porosity were obtained, when nonoxidizing gases are used for thermal spraying. The particle size decreased with increasing of the gas pressure, and the particles sizes are in the range from 10 to 70 µm, which is desirable for selective laser melting (SLM). A comparison of microstructure and mechanical behavior of SLM generated parts using arc sprayed powders (alloy: X5CrNiCuNb 16-4) and commercial powder (alloy: X5CrNiCuNb 16-4) was also conducted.

Keywords: additive manufacturing, arc spraying, powder production, selective laser melting

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Authors: M. Şimşek

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Additive manufacturing (AM) or generally known as three dimensional (3D) printing provides great opportunities for both civilian and military applications by which 3D has become the biggest nominee of breakthrough of 21th century. When properly used, it has a wide spectrum of applications that make production easier and more profitable. Considering the advantages of AM, every firm has an intention of catching up with this new trend. As well as reducing costs and thus increasing benefits, 3D printing provides opportunities for national armies by reducing maintenance and repair time and increasing operational readiness.

Keywords: additive manufacturing, operational cost, operational readiness, supply chain, three dimensional printing

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Authors: Joon-Hoon Park

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In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: G. Nitesh

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The shear strength of soils is a crucial parameter instability analysis. Therefore, it is important to determine reliable values for the accuracy of stability analysis. Direct shear tests are mostly performed to determine the shear strength of cohesionless soils. The major limitation of the direct shear test is that the failure takes place through the pre-defined failure plane but the failure is not along pre-defined plane and is along the weakest plane in actual shearing mechanism that goes on in the field. This leads to overestimating the strength parameter; hence, a new apparatus called simple shear is developed and used in this study to determine the shear strength parameter that simulates the field conditions.

Keywords: direct shear, simple shear, angle of shear resistance, cohesionless soils

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Authors: Ala’a H. Al-Muhtaseb, Farrukh Jamil, Lamya Al-Haj, Mohab Al-Hinai

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Bio-glycerol is considered as high boiling polar triol and immiscible with fossil fuel fractions due to which it is transformed into its respective ketals and acetals which help to improve the quality of diesel emitting less amount of aldehydes and carbon monoxide. Solketal visual appearance is transparent and it is odorless organic liquid used as fuel additive for diesel to improve its cold flow properties. Condensation of bio-glycerol with bio-acetone in presence of beta zeolite has been done for synthesizing solketal. It was observed that glycerol conversion and selectivity of solketal was largely effected by temperature, as it increases from 40 ºC to 60 ºC the conversion of glycerol rises from 80.04 % to 94.26 % and selectivity of solketal from 80.0 % to 94.21 % but further increase in temperature to 100 ºC glycerol conversion reduced to 93.06 % and solketal selectivity to 92.08 %. At the optimum conditions, the bio-glycerol conversion and solketal yield were about 94.26% and 94.21wt% respectively. This process offers an attractive route for converting bio-glycerol, the main by-product of biodiesel to solketal with bio-acetone; a value-added green product with potential industrial applications as a valuable green fuel additive or combustion promoter for gasoline/diesel engines.

Keywords: bio-acetone, bio-glycerol, acetylation, solketal

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Authors: Gürkan Şakar, Akgün Alsaran, Emrah E. Özbaldan

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In this study, lateral buckling analysis of composite beams with particle additive was carried out experimentally and numerically. The effects of particle type, particle addition ratio on buckling loads of composite beams were determined. The numerical studies were performed with ANSYS package. In the analyses, clamped-free boundary condition was assumed. The load carrying capabilities of composite beams were influenced by different particle types and particle addition ratios.

Keywords: lateral buckling, nanoparticle, composite beam, numeric analysis

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Authors: Abdullah Bilal Ozturk, Nil Acarali, Hediye Irem Ozgunduz, Hava Gizem Kandilci, Hanifi Sarac

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In this study, zeolite, shellac and different boron chemicals were used as additive to dye and effects were comprehensively investigated. Considering previous studies additive materials that had not used before were determined for produce dye with physical properties. Literature research about the materials provides determining easily sufficient amount of additive materials. Accessible of additives or yearly production amounts are become important issue at selection of materials. Zeolite and boron chemicals are suitable selection in that easy access and has large amount of production in our country. Previous research about boron chemicals shows they have flame retardant effect on textile materials besides numerous usage areas. Also, from previous research, shellac was used widely for protection and insulation of metallic materials. Zeolite added to dye to increase adhesive effect of dye. In this study, corrosion tests were applied to find out if there are positive effects of zeolite, shellac, and boron chemicals to dye’s physical properties.

Keywords: dye, corrosion, zeolite, shellac, boron

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Authors: Aung Kyaw Moe, Lukin Evgeny Stepanovich, Popova Nelya Alexandrovna

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In this paper, the effect of the additive content in the Al₂O₃-TiO₂-MnO system on the sintering of composite ceramics based on corundum was studied. The samples were pressed by uniaxial semi-dry pressing under 100 MPa and sintered at 1500 °С and 1550 °С. The properties of composite ceramics for porosity and flexural strength were studied. When the amount of additives increases, the properties of composite ceramic samples are better than samples without additives.

Keywords: ceramic, composite material, sintering, corundum

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Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

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This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

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Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

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Authors: Leonnel Mhuka

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Background: The field of photonics has witnessed substantial growth, with an increasing demand for miniaturized and high-performance optical components. Microstructured optical waveguides have gained significant attention due to their ability to confine and manipulate light at the subwavelength scale. Conventional fabrication methods, however, face limitations in achieving intricate and customizable waveguide structures. Two-photon polymerization (TPP) emerges as a promising additive manufacturing technique, enabling the fabrication of complex 3D microstructures with submicron resolution. Objectives: This experiment aimed to utilize two-photon polymerization to fabricate microstructured optical waveguides with precise control over geometry and dimensions. The objective was to demonstrate the feasibility of TPP as an additive manufacturing method for producing functional waveguide devices with enhanced performance. Methods: A femtosecond laser system operating at a wavelength of 800 nm was employed for two-photon polymerization. A custom-designed CAD model of the microstructured waveguide was converted into G-code, which guided the laser focus through a photosensitive polymer material. The waveguide structures were fabricated using a layer-by-layer approach, with each layer formed by localized polymerization induced by non-linear absorption of the laser light. Characterization of the fabricated waveguides included optical microscopy, scanning electron microscopy, and optical transmission measurements. The optical properties, such as mode confinement and propagation losses, were evaluated to assess the performance of the additive manufactured waveguides. Conclusion: The experiment successfully demonstrated the additive manufacturing of microstructured optical waveguides using two-photon polymerization. Optical microscopy and scanning electron microscopy revealed the intricate 3D structures with submicron resolution. The measured optical transmission indicated efficient light propagation through the fabricated waveguides. The waveguides exhibited well-defined mode confinement and relatively low propagation losses, showcasing the potential of TPP-based additive manufacturing for photonics applications. The experiment highlighted the advantages of TPP in achieving high-resolution, customized, and functional microstructured optical waveguides. Conclusion: his experiment substantiates the viability of two-photon polymerization as an innovative additive manufacturing technique for producing complex microstructured optical waveguides. The successful fabrication and characterization of these waveguides open doors to further advancements in the field of photonics, enabling the development of high-performance integrated optical devices for various applications

Keywords: Additive Manufacturing, Microstructured Optical Waveguides, Two-Photon Polymerization, Photonics Applications

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Authors: Mahdi Mottahedi, Peter Zahn, Armin Lechler, Alexander Verl

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Optimal topology of components leads to the maximum stiffness with the minimum material use. For the generation of these topologies, normally algorithms are employed, which tackle manufacturing limitations, at the cost of the optimal result. The global optimum result with penalty factor one, however, cannot be fabricated with conventional methods. In this article, an additive manufacturing method is introduced, in order to enable the production of global topology optimization results. For a benchmark, topology optimization with higher and lower penalty factors are performed. Different algorithms are employed in order to interpret the results of topology optimization with lower factors in many microstructure layers. These layers are then joined to form the final geometry. The algorithms’ benefits are then compared experimentally and numerically for the best interpretation. The findings demonstrate that by implementation of the selected algorithm, the stiffness of the components produced with this method is higher than what could have been produced by conventional techniques.

Keywords: topology optimization, additive manufacturing, 3D-printer, laminated object manufacturing

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Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

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Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

Abstract:

The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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