Elevated Temperature Baseplate Effect on Microstructure, Mechanical Properties, and Thermal Stress Evaluation by Numerical Simulation for Austenite Stainless Steel 316L Fabricated by Directed Energy Deposition.

In the present study, the effect of material deposition at the elevated temperature baseplate on the microstructure and mechanical properties was investigated and correlated to the unique thermal history by using numerical simulation. Numerical results agreed well with the experimental results of microstructure and mechanical properties. Numerical results revealed a significant decrease in temperature gradient and a 40% decrease in thermal stress due to material deposition on the elevated temperature baseplate. The reduced thermal stress and temperature gradient resulted in coarser grain features, which in turn led to a decrease in hardness and tensile strength, especially for the bottom region near the baseplate. Meanwhile, no significant effect could be found for ductility. In addition, an elevated temperature baseplate promoted less heterogeneity in hardness and tensile properties along the building direction. The current work demonstrates a collective and direct understanding of the baseplate preheating effect on thermal stress, microstructure and mechanical properties and their correlations, which is believed beneficial for the better utilization of baseplate preheating positive effects.

Heat Source Modeling and Residual Stress Analysis for Metal Directed Energy Deposition Additive Manufacturing.

The advancement in additive manufacturing encourages the development of simplified tools for deep and swift research of the technology. Several approaches were developed to reduce the complexity of multi-track modeling for additive manufacturing. In the present work, a simple heat source model called concentrated heat source was evaluated for single- and multi-track deposition for directed energy deposition. The concentrated heat source model was compared with the widely accepted Goldak heat source model. The concentrated heat source does not require melt pool dimension measurement for thermal model simulation. Thus, it reduces the considerable time for preprocessing. The shape of the melt pool and temperature contour around the heat source was analyzed for single-track deposition. A good agreement was noticed for the concentrated heat source model melt pool, with an experimentally determined melt pool, using an optical microscope. Two heat source models were applied to multi-track 3D solid structure thermo-mechanical simulation. The results of the two models, for thermal history and residual stress, were compared with experimentally determined data. A good agreement was found for both models. The concentrated heat source model reported less than the half the computational time required for the Goldak model. The validated model, for 3D solid structure thermo-mechanical simulation, was used to analyze thermal stress evolution during the deposition process. The material deposition on the base plate at room temperature results in lower peak temperatures in the layers near the base plate. Consequently, the higher thermal stress in the layers near the base plate was found, compared to the upper layers during the deposition process.

Prediction of Behaviour of Thin-Walled DED-Processed Structure: Experimental-Numerical Approach.

Additive manufacturing (AM) becomes a more and more standard process in different fields of industry. There is still only limited knowledge of the relationship between measured material data and the overall behaviour of directed energy deposition (DED)-processed complex structures. The understanding of the structural performance, including flow curves and local damage properties of additively manufactured parts by DED, becomes increasingly important. DED can be used for creating functional surfaces, component repairing using multiple powder feeders, and creating a heterogeneous structure with defined chemical composition. For thin parts that are used with the as-deposited surface, this evaluation is even highly crucial. The main goal of the study was to predict the behaviour of thin-walled structures manufactured by the DED process under static loading by finite element analysis (FEA). Moreover, in this study, the mechanical performance of partly machined and fully machined miniaturized samples produced from the structure was compared. The structure studied in this research resembles a honeycomb shape made of austenitic stainless steel AISI 316L, which is characterized by high strength and ductility. The uncoupled damage models based on a hybrid experimental-numerical approach were used. The microstructure and hardness were examined to comprehend the structural behaviour.

Base Plate Preheating Effect on Microstructure of 316L Stainless Steel Single Track Deposition by Directed Energy Deposition.

The microstructural morphology in additive manufacturing (AM) has a significant influence on the building structure. High-energy concentric heat source scanning leads to rapid heating and cooling during material deposition. This results in a unique microstructure. The size and morphology of the microstructure have a strong directionality, which depends on laser power, scanning rate, melt pool fluid dynamics, and material thermal properties, etc. The grain structure significantly affects its resistance to solidification cracking and mechanical properties. Microstructure control is challenging for AM considering multiple process parameters. A preheating base plate has a significant influence on residual stress, defect-free AM structure, and it also minimizes thermal mismatch during the deposition. In the present work, a simple single track deposition experiment was designed to analyze base plate preheating on microstructure. The microstructural evolution at different preheating temperatures was studied in detail, keeping process parameters constant. The base plate was heated uniformly from an external heating source and set the stable desired temperature on the surface of the base plate before deposition. A single track was deposited on the base plate at room temperature and preheating temperatures of 200 °C, 300 °C, 400 °C, and 500 °C. Subsequently, the resulting microstructural morphologies were analyzed and compared. The microstructure was evaluated using electron backscattered diffraction (EBSD) imaging in the transverse and longitudinal sections. An increase in grain size area fraction was observed as the preheating temperature increased. Base plate preheating did not show influence on grain boundary misorientation. An increase in the deposition depth was noticed for higher base plate preheating temperatures. The results were convincing that grain morphology and columnar grain orientation can be tailored by base plate preheating.

Mitigating Depolarizing Noise on Quantum Computers with Noise-Estimation Circuits.

A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit and then correcting the output of the target circuit using the estimated rate. The method is experimentally validated on a simulation of the Heisenberg model. We find that our approach in combination with readout-error correction, randomized compiling, and zero-noise extrapolation produces close to exact results even for circuits containing hundreds of CNOT gates. We also show analytically that zero-noise extrapolation is improved when it is applied to the output of our method.

Chemistry on Quantum Computers with Virtual Quantum Subspace Expansion.

Simulating chemical systems on quantum computers has been limited to a few electrons in a minimal basis. We demonstrate experimentally that the virtual quantum subspace expansion (Takeshita, T.; Phys. Rev. X 2020, 10, 011004, 10.1103/PhysRevX.10.011004) can achieve full basis accuracy for hydrogen and lithium dimers, comparable to simulations requiring 20 or more qubits. We developed an approach to minimize the impact of experimental noise on the stability of the generalized eigenvalue problem, a crucial component of the quantum algorithm. In addition, we were able to obtain an accurate potential energy curve for the nitrogen dimer in a quantum simulation on a classical computer.

Numerical Simulation Development and Computational Optimization for Directed Energy Deposition Additive Manufacturing Process.

The rapid growth of Additive Manufacturing (AM) in the past decade has demonstrated a significant potential in cost-effective production with a superior quality product. A numerical simulation is a steep way to learn and improve the product quality, life cycle, and production cost. To cope with the growing AM field, researchers are exploring different techniques, methods, models to simulate the AM process efficiently. The goal is to develop a thermo-mechanical weld model for the Directed Energy Deposition (DED) process for 316L stainless steel at an efficient computational cost targeting to model large AM parts in residual stress calculation. To adapt the weld model to the DED simulation, single and multi-track thermal simulations were carried out. Numerical results were validated by the DED experiment. A good agreement was found between predicted temperature trends for numerical simulation and experimental results. A large number of weld tracks in the 3D solid AM parts make the finite element process simulation challenging in terms of computational time and large amounts of data management. The method of activating elements layer by layer and introducing heat in a cyclic manner called a thermal cycle heat input was applied. Thermal cycle heat input reduces the computational time considerably. The numerical results were compared to the experimental data for thermal and residual stress analyses. A lumping of layers strategy was implemented to reduce further computational time. The different number of lumping layers was analyzed to define the limit of lumping to retain accuracy in the residual stress calculation. The lumped layers residual stress calculation was validated by the contour cut method in the deposited sample. Thermal behavior and residual stress prediction for the different numbers of a lumped layer were examined and reported computational time reduction.

Plasma fatty acid composition in patients with pancreatic cancer: correlations to clinical parameters.

Pancreatic cancer (PC) ranks as the fourth cause of cancer-related deaths in the Czech Republic. Evidence exists that deregulation of fatty acid (FA) metabolism is connected with some malignancies; therefore, we decided to analyze FA profile in plasma lipid classes in patients with PC with relation to tumor staging, nutritional status, and survival. The study included 84 patients (47 males, 37 females) with PC and 68 controls (36 males, 32 females). FA patterns were analyzed in plasma lipid classes by gas-chromatography. We observed increased proportion of total monounsaturated FA (MUFA) in PC group in all plasma lipid classes. These changes were connected with increased Δ9-desaturase (SCD1) and Δ5-desaturase indices. Correlations of dihomo-γ-linolenic acid (DHGLA) with these variables were opposite. Longer survival of patients was connected with higher content of EPA, DHA, and with lower SCD1 index, respectively. Plasma phospholipid proportions of α-linolenic acid, DHGLA, EPA, and n-3 polyunsaturated fatty acids displayed negative trend with tumor staging. Plasma lipid FA pattern in PC patients resulted from decreased dietary fat intake and increased de novo synthesis of FA with transformation into MUFA. Changes in FA profile implicated some pathophysiological mechanisms responsible for disturbed FA metabolism in PC and importance of appropriate nutritional support.