Additive manufacturing has changed how we think about design—but it hasn't changed the laws of mechanics.
Metal additive manufacturing offers unprecedented design freedom: lattice structures that were impossible to machine, topology-optimized geometries that minimize weight while maximizing strength, and radical part consolidation that eliminates hundreds of fasteners. These capabilities promise to reduce manufacturing time and cost while opening new frontiers in aerospace design.
Yet every aerospace part—whether traditionally machined or additively manufactured—still lives under the same unforgiving constraints. It must survive fatigue cycles, resist crack propagation, and meet regulatory requirements substantiated through rigorous test and analysis. The industry's challenge isn't just printing complex parts. It's proving they can endure a lifetime of service.
In aerospace, certification demands substantiation—a combination of testing and analysis that demonstrates compliance with structural requirements throughout the part's lifecycle. Additive manufacturing doesn't remove that requirement; it complicates it.
The structural engineer must now interpret not just geometry and load cases, but process-induced features that traditional manufacturing methods don't introduce: anisotropic material properties that vary with build direction (e.g., columnar grains affecting fatigue crack growth, as seen in Ti-6Al-4V), residual stresses locked into the part during layer-by-layer cooling, and defects like porosity that result from the manufacturing process itself.
As test costs increase and computational analysis capability advances, lifecycle structural analysis is occurring earlier in the design process. This shift places new demands on our analytical methods and design data. We can no longer rely solely on the decades of institutional knowledge built around forging, casting, and machining.
The phrase "design for additive manufacturing" typically focuses on print orientation, support structure placement, and geometric features that the process can produce. But true design for additive must also encompass structural considerations from the first concept sketch.
How will residual stresses affect distortion? Where will porosity concentrate, and how will it influence fatigue life? What post-process heat treatments are required to achieve the necessary fracture toughness?
These aren't questions to answer after the part is printed. They're fundamental to the design process itself.
Here's the uncomfortable truth: as the aerospace industry seeks to make metal additive manufacturing as common and reliable as modern subtractive and forming processes, we're working with an incomplete playbook.
Traditional manufacturing processes are supported by extensive databases of material properties, design allowables, and decades of service experience. When you machine a part from 7075-T6 aluminum or forge a component from Ti-6Al-4V, you have access to well-characterized static strength, fatigue, and fracture properties validated across multiple suppliers and production lots.
Additive manufacturing lacks that institutional foundation. Material properties are process-specific—the mechanical performance of laser powder bed fusion (PBF) Ti-6Al-4V differs from electron beam melting (a PBF variant) Ti-6Al-4V, which differs from directed energy deposition (DED) Ti-6Al-4V (as summarized in Tables 2-3 of my review). Even within the same process, print parameters like scan speed, laser power, and layer thickness significantly influence porosity levels and microstructure, which in turn affect fatigue and fracture behavior.
Without validated structural methods and design data, the risk is "printing first, analyzing later"—a reactive approach that increases development cost and schedule risk. The role of structural discipline is to define the analytical and testing framework that lets design and certification move forward together, enabling engineers to properly size parts in the design phase for the entire part lifecycle.
Several factors make structural analysis of additively manufactured parts fundamentally different from traditional approaches:
• Process-Driven Properties: Mechanical performance varies with print parameters in ways that have no parallel in conventional manufacturing. The same titanium powder can produce markedly different tensile properties, ductility, and crack growth rates depending on laser power, scan velocity, and build chamber atmosphere. Unlike forged or wrought materials, there's no single "AM Ti-6Al-4V" specification—the material properties are inseparable from the process that created them.
• Defects Are Intrinsic: Porosity isn't an anomaly to be eliminated; it's an inherent feature of the process that must be managed. Research shows two dominant defect types: nearly spherical pores from entrapped gas, and irregular lack-of-fusion voids where powder wasn't sufficiently melted (Figure 1). Studies on powder bed fusion titanium demonstrate that porosity increases at both very low and very high scan velocities, and at both low and high laser powers—a processing window that requires careful optimization (Figure 2).
Figure 1: Different typed of defects: (a) nearly spherical pore due to entrapped gas (b) lack of fusion void (Molaei & Fatemi, 2018)
Figure 2: Influence of PBF process parameters on porosity in Ti6AL4V samples: (a) scanning velocity, (c) laser power (Molaei & Fatemi, 2018)
• Material Models Must Evolve: Traditional fatigue prediction methods—stress-life curves, strain-life approaches—assume material homogeneity. Additive manufacturing challenges that assumption. Columnar grain structures aligned with build direction create anisotropy. Porosity creates stress concentrations. The effective material properties at any location depend on local microstructure and defect distribution, which vary throughout the build.
• Analysis Must Adapt: Predicting fatigue and fracture in AM parts requires accounting for defect morphology, orientation relative to load direction, and spatial distribution. A spherical gas pore and an elongated lack-of-fusion void of the same cross-sectional area have vastly different effects on crack initiation and growth (e.g., lack-of-fusion voids often reduce fatigue life more due to their irregular shape). Furthermore, research indicates that the majority of the influence on crack propagation comes from defects nearest the crack tip—understanding defect distribution isn't just about average porosity percentage, it's about local concentrations in critical regions.
Classical finite element analysis struggles with the discontinuities inherent in additive manufacturing. Modeling individual pores or cracks requires mesh topology that conforms to each defect—a computationally expensive proposition when dealing with hundreds or thousands of pores in a component.
Methods like the extended finite element method (XFEM) overcome this limitation, as reviewed in my paper. XFEM uses enrichment functions that allow discontinuities to be represented without conforming mesh topology, enabling efficient simulation of porosity and crack growth. This capability is essential for AM fatigue prediction, where the interaction between macro-scale cracks and micro-scale defects determines structural performance.
Multiscale approaches further enhance efficiency by separating the problem into coarse-scale and fine-scale domains (e.g., homogenizing micro-defects or projecting fine-scale effects onto macro-models). The global model captures overall structural response without explicitly modeling every defect. A refined submodel in the region of interest—perhaps around a crack tip or stress concentration—explicitly represents local defect distribution and calculates its influence on crack growth rates and direction.
These advanced tools transform structural analysis from a post-design verification step into a design enabler. They allow engineers to explore the sensitivity of structural performance to process parameters, quantify the effect of defect populations on fatigue life, and optimize print strategies before committing to expensive build trials.
For additive manufacturing, structural discipline integrates analysis, testing, and process knowledge throughout the development lifecycle:
• Before Print: Use analysis to assess print orientation effects on anisotropy and residual stress. Evaluate support structure placement to minimize distortion while ensuring the part can be successfully removed. Identify regions where stress concentrations may interact with expected porosity distributions.
• After Print: Leverage CT scanning or other non-destructive evaluation to characterize actual defect populations. Feed this data into defect-informed simulations that predict fatigue life or fracture resistance based on as-built geometry rather than idealized models.
• During Qualification: Develop parametric studies linking process settings to defect characteristics to mechanical performance. Build databases that enable statistical prediction of properties from process parameters. Establish acceptance criteria for porosity that balance structural requirements against manufacturing yield.
• Across the Lifecycle: Treat simulation, testing, and certification as integrated structural substantiation. Use test data to validate models. Use validated models to reduce test matrices. Iterate between analysis and experiment to build the institutional knowledge that traditional materials possess. These practices build on the need for integrated analysis highlighted in my 2018 review, though AM technologies have advanced since then (e.g., better porosity control in modern PBF systems).
In additive manufacturing, the part isn't certified when it's printed—it's certified when it's analyzed.
Additive manufacturing gives us new freedom in shape, but not in physics. The fundamental mechanics of fracture, the statistical nature of fatigue, and the regulatory requirements for flight safety haven't changed. What has changed is the complexity of the materials we're analyzing and the defect populations we must account for.
To make additive manufacturing a dependable production method for flight hardware, it must be guided by the same structural rigor that built aerospace safety over the past century. Knowledge of manufacturing processes, material properties, and defect characteristics is necessary to develop the analysis methods and design data that enable confident structural design.
The next frontier isn't printing faster or building larger parts. It's predicting better—developing the analytical framework and design allowables that let engineers size AM components with the same confidence they bring to traditional designs. That's where structural discipline transforms additive manufacturing from a promising technology into a production reality.
🔗 Download my full 2018 Master's Literature Review & Research Proposal: Structural Analysis of Porosity Effects in Aerospace Metal AM
This article draws from the literature review and research proposal I developed during my master's degree on porosity effects in aerospace metal additive manufacturing, with particular focus on the structural analysis methods required to predict performance in the presence of process-induced defects. The intersection of advanced manufacturing and structural integrity represents one of the most challenging and rewarding frontiers in aerospace engineering.
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