Defects In Region Research Articles

The defect detection of 3D-printed ceramic curved surface parts with low contrast based on deep learning

Some defects were produced during 3D printing ceramic parts and it is difficult to detect these defects, especially for the ceramic curved surface parts, because of low contrast between defects and ceramic background, blurred edges and low efficiency. In this word, a defect detection method with low contrast based on deep learning is studied. Firstly, the difficulties and adverse effects that occur in the detection of ceramic curved surface parts are analyzed qualitatively. Then, a blurry inpainting network model is proposed to effectively reduce the degree of blurring on the curved surface. A multi-scale detail contrast enhancement algorithm is also established to solve the problems low contrast among defective and the background regions, which can highlight the characteristic information of the defect regions. On this basis, two types of defects in the curved surface parts are detected by using our constructed ECANet-Mobilenet SSD network model. The results show that the prediction accuracy for crack and bulge defects recognition can reach 94.35%, and 96.72%, respectively, and meanwhile, their average detection time of a single image is 0.78s. Therefore, this study on the defect detection of 3D-printed ceramic curved surface parts can contribute to the intelligent and 3D printing development of advanced ceramic industry.

Dual-IRT-GAN: A defect-aware deep adversarial network to perform super-resolution tasks in infrared thermographic inspection

InfraRed Thermography (IRT) is a valuable diagnostic tool for detecting defects in fiber-reinforced polymers in a non-destructive manner through the measurement of surface temperature distribution. Yet, thermal cameras typically have a low native spatial resolution resulting in a blurry and low-quality thermal image sequence.This study proposes a defect-aware Generative Adversarial Network (GAN) framework, termed Dual-IRT-GAN, in order to simultaneously perform Super-Resolution (SR) and defect detection tasks in infrared thermography. Furthermore, the visibility of defective regions in generated high-resolution images are enhanced by leveraging defect-aware attention maps from segmented defect images.Following a series of augmentation techniques and a second-order degradation process, the proposed Dual-IRT-GAN model is trained on an extensive numerically generated thermographic dataset of composite materials with various defect types, sizes and depts. The high inference performance of the virtually trained Dual-IRT-GAN is demonstrated on several experimental thermographic datasets which were obtained from composite coupon specimens with various defect types, sizes, and depths, as well as from aircraft stiffened composite panels having real (production) defects.

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

Pipelines are typically used to transport oil, natural gas, water, etc. It is one of the most effective methods for transferring fluids over long distances. However, long-term usage of these pipes without maintenance results in the formation of residues, which will pave the way for pipeline accidents and soil contamination. To ensure the safety and protection of resources, these sustainable pipelines need to be inspected to avoid losses. This work aims to investigate various internal defect leaks in the non-uniform thickness of sustainable water pipes that are joined with a pipe expander. The magnetic flux leakage technique was implemented to evaluate these defects by means of a flexible GMR sensor array. An inspection robot containing two units was fabricated with the aid of 3D printing. The power unit provides the necessary thrust to actuate the entire robot whereas the sensing unit is responsible for analyzing the leaks. The robot’s movement is predicted by the MPU6050 and ultrasonic distance sensors that are plotted as motion plots. The sensing unit consists of permanent magnets and a giant magnetoresistance (GMR) array to interrogate the flux leakage in the defect region. The flux leakage from the defects was stored with the help of an Arduino microcontroller, which controls the overall process. In addition, the spring suspension is provided to regulate the motion of the robot. The flux leakage from the defect region was plotted as waveform graphs. Thus, the results are effectively presented and compared. The calculated signal-to-noise ratio (SNR) of the magnetic flux leakages (MFLs) for 4.5 mm-thick pipe defects was 12 to 20.8 dB, and for 6.52 mm-thick pipe defects, it was 9.5 to 19 dB. In sum, the MFL technique provides a reliable method for the sustainable development of water supply to wide areas.

Imaging of sub-surface defect in CFRP laminate using A0-mode Lamb wave: Analytical, numerical and experimental studies

Lamb wave propagation in the anisotropic material is characterized by the prominent directivity of wave energy transfer governed by the fiber direction. Due to this anisotropic behavior, it is difficult to define the location of defects by using the arriving time of reflected signals. In this article, A0-mode Lamb wave-based damage detection technique has been illustrated which can detect the overlapping region of incident and scattered wave in the vicinity of the finite defect region in CFRP composite plate-like structure. A 5-cycle Hanning windowed tone burst of 30 kHz has been allowed to propagate through a 2 mm thickness [0/90]4S CFRP plate with subsurface cylindrical defect. In the near field region of the defect, the incoming and reflected wave overlaps and the dynamic shear strains of the out-of-plane displacement evaluated consequently. A covariance matrix is developed consisting of the shear strains. The proposed technique can detect the overlapping regions by measuring the determinant of covariance matrix, thus the image of the defect can be reconstructed. In this article, the analytical model of the proposed wavelet-based technique for the subsurface cylindrical defect is discussed and their physical meanings are investigated through numerical and experimental studies in a cross-ply laminate.

Dual-passivation strategy on CsPbI2Br perovskite solar cells for reduced voltage deficit and enhanced stability

The notorious defects in the grain boundaries (GBs) and surfaces trigger serious nonradiative recombination and interfacial charge losses, concomitantly exacerbating the deterioration of photovoltaic performance and phase stability of CsPbI2Br perovskite solar cells. In this work, a comprehensive dual-passivation strategy enabled by formamidine salts (FADP) is developed to annihilate defects both inside the GBs and over the surface. It is shown that formamidinothiourea (FATU) additive could effectively modulate crystallization and afford to passivate both shallow-/deep-level defects at GBs, thereby endowing CsPbI2Br films with reduced lattice micro-strains and enlarged grains over 2 µm. Meanwhile, formamidinium bromine (FABr) post-treatment can efficiently heal the defective surface and realize cationic exchange with below CsPbI2Br films, forming a gradient band alignment at the CsPbI2Br/HTL interface. Profiting from ameliorated crystallization, inhibited GBs/surface charge recombination and facilitated hole transport ability, the novel FADP strategy substantially lifts the Voc from 1.22 V to 1.34 V, yielding a champion PCE of 16.74% with greatly reduced hysteresis. Coincidently, the unencapsulated FADP devices maintained 86.2% of initial PCE after aging at 25% RH for 40 days and 83.8% after 480 h aging under continuous illumination, which is pertinent to the inhibited defective region as well as Br-rich surface.

Antimicrobial Peptide Mechanism Studied by Scattering-Guided Molecular Dynamics Simulation.

In an effort to combat rising antimicrobial resistance, our labs have rationally designed cationic, helical, amphipathic antimicrobial peptides (AMPs) as alternatives to traditional antibiotics since AMPs incur bacterial resistance in weeks, rather than days. One highly positively charged AMP, WLBU2 (+13e), (RRWV RRVR RWVR RVVR VVRR WVRR), has been shown to be effective in killing both Gram-negative (G(-)) and Gram-positive (G(+)) bacteria by directly perturbing the bacterial membrane nonspecifically. Previously, we used two equilibrium experimental methods: synchrotron X-ray diffuse scattering (XDS) providing lipid membrane thickness and neutron reflectometry (NR) providing WLBU2 depth of penetration into three lipid model membranes (LMMs). The purpose of the present study is to use the results from the scattering experiments to guide molecular dynamics (MD) simulations to investigate the detailed biophysics of the interactions of WLBU2 with LMMs of Gram-negative outer and inner membranes, and Gram-positive cell membranes, to elucidate the mechanisms of bacterial killing. Instead of coarse-graining, backmapping, or simulating without bias for several microseconds, all-atom (AA) simulations were guided by the experimental results and then equilibrated for ∼0.5 μs. Multiple replicas of the inserted peptide were run to probe stability and reach a combined time of at least 1.2 μs for G(-) and also 2.0 μs for G(+). The simulations with experimental comparisons help rule out certain structures and orientations and propose the most likely set of structures, orientations, and effects on the membrane. The simulations revealed that water, phosphates, and ions enter the hydrocarbon core when WLBU2 is positioned there. For an inserted peptide, the three types of amino acids, arginine, tryptophan, and valine (R, W, V), are arranged with the 13 Rs extending from the hydrocarbon core to the phosphate group, Ws are located at the interface, and Vs are more centrally located. For a surface state, R, W, and V are positioned relative to the bilayer interface as expected from their hydrophobicities, with Rs closest to the phosphate group, Ws close to the interface, and Vs in between. G(-) and G(+) LMMs are thinned ∼1 Å by the addition of WLBU2. Our results suggest a dual anchoring mechanism for WLBU2 both in the headgroup and in the hydrocarbon region that promotes a defect region where water and ions can flow across the slightly thinned bacterial cell membrane.

Analysis of a No-Insulation HTS Pancake Coil Including Multiple Resistive Joints

One of the technical issues in the application of High Temperature Superconducting (HTS) tapes to magnet technology is the need to wind long tape sections with uniform electric properties along the length. It has been reported that a No-Insulation (NI) coil can properly work even in the presence of defective super-conductive regions, with a minimal drop of performance as com-pared to its “defect-free” counterpart. This could open up the possibility of manufacturing coils by jointing together several tape segments of limited length, lowering the conductor cost. In this work, a single pancake NI HTS coil is wound using several tape segments cut from the same lot, jointed together. The electrical resistance of each joint is set independently, realizing either high or low resistance joints. Thus, the coil is designed to include multiple defective sections at specific locations. The coil is refrigerated by conduction-cooling, and tested at different temperatures and charging rates. The coil instrumentation allows measuring the voltage over the whole winding, as well as the magnetic field in the central bore. The measurements are used to study the defect-irrelevant behavior of the coil. A simple equivalent lumped parameter circuit is applied to derive the coil effective parameters and analyze its electromagnetic behaviour.

Ordered domains in sheared dense suspensions: The link to viscosity and the disruptive effect of friction

Monodisperse suspensions of Brownian colloidal spheres crystallize at high densities, and ordering under shear has been observed at densities below the crystallization threshold. We perform large-scale simulations of a model suspension containing over 105 particles to quantitatively study the ordering under shear and to investigate its link to the rheological properties of the suspension. We find that at high rates, for Pe>1, the shear flow induces an ordering transition that significantly decreases the measured viscosity. This ordering is analyzed in terms of the development of layering and planar order, and we determine that particles are packed into hexagonal crystal layers (with numerous defects) that slide past each other. By computing local ψ6 and ψ4 order parameters, we determine that the defects correspond to chains of particles in a squarelike lattice. We compute the individual particle contributions to the stress tensor and discover that the largest contributors to the shear stress are primarily located in these lower density, defect regions. The defect structure enables the formation of compressed chains of particles to resist the shear, but these chains are transient and short-lived. The inclusion of a contact friction force allows the stress-bearing structures to grow into a system-spanning network, thereby disrupting the order and drastically increasing the suspension viscosity.

Potential Use of 3D CORAGRAF-Loaded PDGF-BB in PLGA Microsphere Seeded Mesenchymal Stromal Cells in Enhancing the Repair of Calvaria Critical-Size Bone Defect in Rat Model.

Our previous study evidenced that the 3D CORAGRAF loaded with PLGA microsphere constitutes PDGF-BB can support cell attachment and proliferation and can induce an osteogenic commitment of mesenchymal stromal cells in the in vitro condition. However, how this construct can perform in pathophysiological conditions in terms of repairing critical bone defects is yet to be understood. A study was therefore conducted to investigate the regeneration potential of calvaria critical-size defects using CORAGRAF + PLGA with PDGF-BB + mesenchymal stromal cells (MSCs) in a rat model. A 5 mm critical bone defect was created on calvaria of 40 male Sprague-Dawley rats. CORAGRAF incorporated either with or without PDGF-BB and seeded with rat bone-marrow-derived MSCs was implanted at the defect region. The bone regeneration potential of implanted constructs was assessed using micro-CT imaging and histological staining in weeks 4 and 8. The micro-CT images indicated a significant closure of defects in the cranial bone of the rats treated with 3D CORAGRAF + PLGA with PDGF-BB + MSCs on week 4 and 8 post-implantation. This finding, further supported with the histology outcome where the rat cranial defect treated with CORAGRAF + PLGA with PDGF-BB + MSCs indicated neo-bony ingrowth with organized and mature bone-like morphology as compared with other groups. The previous in vitro results substantiated with our pre-clinical findings demonstrate that the combination of CORAGRAF + PLGA with PDGF-BB + MSCs could be an ideal construct to support bone regeneration in critical bone defects. Hence, this construct can be further investigated for its safety and efficacy in large animal models, or it can be skipped to human trial prior for commercialization.

Scaffold microarchitecture regulates angiogenesis and the regeneration of large bone defects

Emerging 3D printing technologies can provide exquisite control over the external shape and internal architecture of scaffolds and tissue engineering (TE) constructs, enabling systematic studies to explore how geometric design features influence the regenerative process. Here we used fused deposition modelling (FDM) and melt electrowriting (MEW) to investigate how scaffold microarchitecture influences the healing of large bone defects. FDM was used to fabricate scaffolds with relatively large fibre diameters and low porosities, while MEW was used to fabricate scaffolds with smaller fibre diameters and higher porosities, with both scaffolds being designed to have comparable surface areas. Scaffold microarchitecture significantly influenced the healing response following implantation into critically sized femoral defects in rats, with the FDM scaffolds supporting the formation of larger bone spicules through its pores, while the MEW scaffolds supported the formation of a more round bone front during healing. After 12 weeks in vivo, both MEW and FDM scaffolds supported significantly higher levels of defect vascularisation compared to empty controls, while the MEW scaffolds supported higher levels of new bone formation. Somewhat surprisingly, this superior healing in the MEW group did not correlate with higher levels of angiogenesis, with the FDM scaffold supporting greater total vessel formation and the formation of larger vessels, while the MEW scaffold promoted the formation of a dense microvasculature with minimal evidence of larger vessels infiltrating the defect region. To conclude, the small fibre diameter, high porosity and high specific surface area of the MEW scaffold proved beneficial for osteogenesis and bone regeneration, demonstrating that changes in scaffold architecture enabled by this additive manufacturing technique can dramatically modulate angiogenesis and tissue regeneration without the need for complex exogenous growth factors. These results provide a valuable insight into the importance of 3D printed scaffold architecture when developing new bone TE strategies.

An Approach to Software Defect Prediction Combining Semantic Features and Code Changes

Software defect prediction (SDP), which predicts defective code regions, can help developers reasonably allocate limited resources for locating bugs and prioritizing their testing efforts. Previous work on defect prediction has used machine learning and artificial software metrics. However, traditional defect prediction features extracted from artificial software metrics often fail to capture the syntactic and semantic information of defective modules. This work on defect prediction mostly focuses on abstract syntax tree (AST). Moreover, because current research on AST technology is relatively mature, it is difficult to further improve the accuracy of defect prediction when only using AST to characterize codes. In this paper, in order to capture more semantic features, we extract semantic information both from the sequences of AST tokens and code change tokens. In addition, to leverage the traditional features extracted from statistical metrics, we also combine the semantic features with traditional defect prediction features to perform SDP, and use the gated fusion mechanism to determine the combination ratio of the two kinds of features. In our empirical studies, 10 open-source Java projects from the PROMISE repository are chosen as our empirical subjects. Experimental results show that our proposed approach can perform better than several state-of-the-art baseline SDP methods.

Graph-component approach to defect identification in large atomistic simulations

The graph-theoretical concept of connected components is employed to extract the evolution of defect configurations in a polycrystalline aluminum structure containing ∼8.3 million atoms. This graph-component approach is applied to reveal details of defect formation, transport, and transformation in the polycrystalline Al under large shear deformation. Building upon standard nearest neighbor analysis, graph theory and associated tools are used to reduce the multi-million-atom system into discrete component subgraphs that represent distinct structural defects. This method allows the automated identification, characterization, and tracking of defective regions within large volumes of data representing atomic-scale processes. Such analysis elucidates relationships between external stimuli, such as strain, and defect distributions, which have a large influence on material properties. The Graph Analytics for Large Atomistic Simulations (GALAS) codebase that implements this analysis, together with user guidance, is openly available at https://github.com/pnnl/galas.

In Situ Assessment of Porcine Osteochondral Repair Tissue in the Visible-Near Infrared Spectral Region.

Standard assessment of cartilage repair progression by visual arthroscopy can be subjective and may result in suboptimal evaluation. Visible–near infrared (Vis-NIR) fiber optic spectroscopy of joint tissues, including articular cartilage and subchondral bone, provides an objective approach for quantitative assessment of tissue composition. Here, we applied this technique in the 350–2,500 nm spectral region to identify spectral markers of osteochondral tissue during repair with the overarching goal of developing a new approach to monitor repair of cartilage defects in vivo. Full thickness chondral defects were created in Yucatan minipigs using a 5-mm biopsy punch, and microfracture (MFx) was performed as a standard technique to facilitate repair. Tissues were evaluated at 1 month (in adult pigs) and 3 months (in juvenile pigs) post-surgery by spectroscopy and histology. After euthanasia, Vis-NIR spectra were collected in situ from the defect region. Additional spectroscopy experiments were carried out in vitro to aid in spectral interpretation. Osteochondral tissues were dissected from the joint and evaluated using the conventional International Cartilage Repair Society (ICRS) II histological scoring system, which showed lower scores for the 1-month than the 3-month repair tissues. In the visible spectral region, hemoglobin absorbances at 540 and 570 nm were significantly higher in spectra from 1-month repair tissue than 3-month repair tissue, indicating a reduction of blood in the more mature repair tissue. In the NIR region, we observed qualitative differences between the two groups in spectra taken from the defect, but differences did not reach significance. Furthermore, spectral data also indicated that the hydrated environment of the joint tissue may interfere with evaluation of tissue water absorbances in the NIR region. Together, these data provide support for further investigation of the visible spectral region for assessment of longitudinal repair of cartilage defects, which would enable assessment during routine arthroscopy, particularly in a hydrated environment.

Use of Eggshells as Bone Grafts around Commercially Pure Titanium Implant Screws Coated with Nano Calcium Sulfate.

Background Implant insertion in regions with poor bone quantity, such as the posterior maxilla, is potentially associated with an increased rate of implant failure. Calcium sulfate can be used as the coating material for commercially pure titanium (CpTi) and as the bone graft material around implants when bound to eggshell powder to enhance the bone quality and quantity of bone defect regions. This study performed a torque removal test to evaluate the effectiveness of eggshell powder as a bone substitute for filling bone defects around CpTi-coated implants coated with nanocrystalline calcium sulfate. Materials and Methods Eighty screw implant designs were used in the tibiae of 20 white New Zealand rabbits. A total of uncoated 20 screws constituted the control group, and the remaining 60 screws coated with nano calcium sulfate nanoparticles were used as the experimental groups as follows: 20 screws coated with nano calcium sulfate were used alone in the tibiae without gaps around them, 20 screws coated with nano calcium sulfate were used with the gaps made around them and filled with eggshell powder as the bone graft material, and 20 screws coated with nano calcium sulfate were used with the gaps made around them left unfilled. Results After 2 to 6 weeks of healing, a significant improvement in bone regeneration and an increase in torque removal values were observed when the bone defect around the CpTi implant coated with nano calcium sulfate was filled with eggshell powder as the bone substitute. Conclusions Nano calcium sulfate particles applied through the dip-coating method can successfully work as the coating material of CpTi implants. These particles work in synergy with eggshell powder to act as the bone graft around the implants.

Investigating the micro-turbulent corrosion mechanism of pipeline defects based on a combined experimental and simulation approach

The existence of pipeline defects in oil and gas gathering pipelines predisposed the pipeline to rupture under the synergistic effects of local micro–turbulence and electrochemical corrosion. Here, a combination of experimental and simulation methods was proposed to facilitate the investigation of CO2 corrosion and the mass transfer process in pipeline defects. The corrosion kinetic characteristics of the defect region were clarified by coupling wire beam microelectrode (WBE) and electrochemical impedance spectroscopy (EIS). Additionally, the effect of flow mass transfer on the corrosion of pipeline defects was investigated by using the existing mass transfer models and COMSOL Multiphysics simulations. The results showed that different locations of the pipeline defects exhibited different mass transfer behavior and corrosion variations. The mass transfer process at the bottom of the defect was lower than that in the upper and lower edge of the defect. Furthermore, the bottom of the defect behaved as an anode and corrodes more severely at low flow velocities. The enhanced mass transfer process led to more severe corrosion at the upper and lower edges of the defect at high flow velocities.

Experimental and numerical studies on collapse of subsea pipelines with interacting corrosion defects

The pipeline is prone to collapse under the combined external pressure and multiple corrosion defects. Experiments of the full-scale pipelines with longitudinally, circumferentially and diagonally dual defects are conducted, respectively. Finite element models are established to simulate the experimental process, and achieved good consistency. Then the influences of corrosion defect dimensions on the interaction are analyzed, and the corresponding critical spacing is determined. Moreover, the collapse modes of the pipeline under different defect forms are studied. The collapse mode of the pipeline with two external corrosion defects changes from U-shaped to ∞-shaped mode. However, the collapse modes for the pipeline with internal and external corrosion defects or two internal corrosion defects are irregular and the deformation is mainly concentrated on the region of corrosion defects. In addition, the critical pressure of the pipeline is sensitive to the defect distribution type (distributed axially, circumferentially, or diagonally along the pipeline, etc.). Finally, a formula for estimating the collapse pressure of the pipeline with dual corrosion defects is proposed. The comparison between the proposed formula and finite element results proves that this formula can be used for the collapse pressure of the pipeline with multiple corrosion defects in a slightly conservative manner.

Automatic Grading Assessments for Knee MRI Cartilage Defects via Self-ensembling Semi-supervised Learning with Dual-Consistency.

Knee cartilage defects caused by osteoarthritis are major musculoskeletal disorders, leading to joint necrosis or even disability if not intervened at early stage. Deep learning has demonstrated its effectiveness in computer-aided diagnosis, but it is time-consuming to prepare a large set of well-annotated data by experienced radiologists for model training. In this paper, we propose a semi-supervised framework to effectively use unlabeled data for better evaluation of knee cartilage defect grading. Our framework is developed based on the widely-used mean-teacher classification model, by designing a novel dual-consistency strategy to boost the consistency between the teacher and student models. The main contributions are three-fold: (1) We define an attention loss function to make the network focus on the cartilage regions, which can both achieve accurate attention masks and boost classification performance simultaneously; (2) Besides enforcing the consistency of classification results, we further design a novel attention consistency mechanism to ensure the focusing of the student and teacher networks on the same defect regions; (3) We introduce an aggregation approach to ensemble the slice-level classification outcomes for deriving the final subject-level diagnosis. Experimental results show that our proposed method can significantly improve both classification and localization performances of knee cartilage defects. Our code is available on https://github.com/King-HAW/DC-MT.

A CISG Method for Internal Defect Detection of Solar Cells in Different Production Processes

The internal defect detection of solar cells indifferent production processes currently adopts manual visual verification on the images captured by electroluminescence or photoluminescence system. To improve the efficiency and reliability of the inspection, this article proposes a generic and automatic component-of-interest superposition graph(CISG) method. First, the solar cell inspection region is located by shape-based matching. Second, based on the properties of Fourier transform and singular value decomposition, the frequency components of the testing image are modified adaptively, and then component graphs with different local saliency are generated. According to the normalized marginal gains of energy, these component graphs are combined into a saliency map. Finally, defective regions are extracted from the saliency map using the global threshold technique. By employing various compared approaches to conduct experiments on five datasets from different production processes, the great performance of our presented method is revealed, which also implies this method outperforms the current methods.

Structure-property-process parameter correlation in the Advanced MOCVD growth of 4+ μm REBCO thick films over 10+ m

REBCO (REBa2Cu3O7−δ ) coated conductor with Je > 1000 A/mm2 at operating condition is being utilized in fusion and high-field-magnet applications. We have demonstrated short REBCO samples with an engineering current density (Je ) ~ 4,600 A/mm2 (based on 0.1 mm thick tape) at 4.2 K, 20 T using Advanced Metal-Organic Chemical Vapor Deposition (A-MOCVD). In order to achieve such high performance uniformly over long tapes, defective regions in thick films need to be avoided. In this work, we investigated parameters that cause dropout or variation in the critical current along the length of long tapes made by A-MOCVD. By addressing the engineering challenges of growing 4+ μm thick REBCO films in a single pass, 10+ m long tapes with high critical current that varies < 5% along the length have been fabricated.

Effect of processing parameters on pore structures, grain features, and mechanical properties in Ti-6Al-4V by laser powder bed fusion

In this study, the process-structure-property linkages in laser powder bed fusion of Ti-6Al-4V were investigated experimentally and quantified via correlation analysis. Forty-two different combinations of laser power and scan speed were examined to probe lack-of-fusion, keyholing, and beading-up defect regions in addition to dense regions of the processing space. The resultant structures of the fabricated components were characterized through X-ray computed tomography for visualization and characterization of internal pores and optical metallography to examine prior-β grain features. Mechanical properties were assessed via uniaxial tension tests and Vickers microhardness measurements. Correlation analyses, used to quantify the statistical bivariate relations between feature pairs describing processing conditions, microstructural features, and mechanical properties, revealed the relationship between processing parameters and defect pore morphology, which in turn correlated with mechanical properties. Additionally, the work expands on process maps for avoiding porosity by defining correlations between processing conditions and resultant properties, providing a means for tailoring properties and structures via processing in laser powder bed fusion additive manufactured materials.