Abstract This article provides an overview of different modeling approaches used to capture the phenomena present in the additive manufacturing (AM) process. Inherent to the thermomechanical processing that occurs in AM for metals is the development of residual stresses and distortions. The article then provides an overview of thermal modeling. It presents a discussion on solid mechanics simulation and microstructure simulation.

the retrofit lamp or kit manufacturer. Once installed in the mockup facility, the converted luminaires were examined by a NRTL (Nationally Recognized Testing Laboratory) safety expert, who provided feedback on safety issues. In September 2012, a group of lighting designers, engineers, and facility managers were brought in to observe the LED luminaires in comparison to fluorescent benchmarks. This report documents performance in measures that go beyond illuminance values or luminaire efficacy. Dedicated LED troffers are ready to compete with fluorescent troffers in terms of efficacy (lumens per watt), and in many lighting quality issues such as glare, light distribution, visual appearance, and color quality. That is not to say that each one is stellar, but each one tested in this CALiPER study bested the fluorescent benchmarks in terms of efficacy, and almost all were rated highly in several categories -- only one luminaire of twelve performed consistently poorly.

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/SolidMechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. The resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

Adopting additively-manufactured components in conventional supply chains requires an understanding of residual stress effects on typical component quality: dimensional accuracy, mechanical strength, and fatigue performance. Residual stresses are central to these elements of component quality; however, they vary significantly at different locations in additively-manufactured parts. Multiple methods are used to assess residual stresses at critical locations including the build/baseplate interface, the near surface layers, between layers, and typical planes of interest. Exploratory measurements on laser engineering net shaping (LENS) and powder bed fusion (PBF) bosses are performed using the contour method and slitting method. Steep stress gradients and high stresses with limits approaching the material yield strength are reported. These stresses are often compressive at the component interior and tensile near the outer surfaces. Future work is planned to investigate repeatability of both the measurement methods and the ADDITIVE manufacturing processes.

It is well established that the variability in mechanical response and ultimate failure of additively manufactured metals correlates to uncertainties introduced in the build process, among which include internal void structure and residual stresses. Here, we quantify the aforementioned variabilities in 316L stainless steels by conducting simulations in Sierra/SM of the specimens/geometries used in Sandia's third fracture challenge (SFC3). We leverage the simulations and experimental work presented in 6 to construct a statistical representation of the internal void structure of the tension specimen used for material parameter calibration as well as the "challenge" geometry. Voided mesh samples of both specimens are generated given a set of statistical variables, and the physics simulations are conducted for multiple sets of realization to determine the effects of void structure on variability in the fracture paths and displacement-to-failure. Lastly, a series of simulations are presented which highlight the effect of the powder bed fusion additive manufacturing process on the formation of residual stresses in the as-built geometries.

The third Sandia Fracture Challenge highlighted the geometric and material uncertainties introduced by modern additive manufacturing techniques. Tasked with the challenge of predicting failure of a complex additively-manufactured geometry made of 316L stainless steel, we combined a rigorous material calibration scheme with a number of statistical assessments of problem uncertainties. Specifically, we used optimization techniques to calibrate a rate-dependent and anisotropic Hill plasticity model to represent material deformation coupled with a damage model driven by void growth and nucleation. Through targeted simulation studies we assessed the influence of internal voids and surface flaws on the specimens of interest in the challenge which guided our material modeling choices. Employing the Kolmogorov–Smirnov test statistic, we developed a representative suite of simulations to account for the geometric variability of test specimens and the variability introduced by material parameter uncertainty. This approach allowed the team to successfully predict the failure mode of the experimental test population as well as the global response with a high degree of accuracy.

This work proposes a finite element (FE) analysis workflow to simulate directed energy deposition (DED) additive manufacturing at a macroscopic length scale (i.e. part length scale) and to predict thermal conditions during manufacturing, as well as distortions, strength and residual stresses at the completion of manufacturing. The proposed analysis method incorporates a multi-step FE workflow to elucidate the thermal and mechanical responses in laser engineered net shaping (LENS) manufacturing. For each time step, a thermal element activation scheme captures the material deposition process. Then, activated elements and their associated geometry are analyzed first thermally for heat flow due to radiation, convection, and conduction, and then mechanically for the resulting stresses, displacements, and material property evolution. Simulations agree with experimentally measured in situ thermal measurements for simple cylindrical build geometries, as well as general trends of local hardness distribution and plastic strain accumulation (represented by relative distribution of geometrically necessary dislocations).

This SAND report fulfills the final report requirement for the Born Qualified Grand Challenge LDRD. Born Qualified was funded from FY16-FY18 with a total budget of ~$13M over the 3 years of funding. Overall 70+ staff, Post Docs, and students supported this project over its lifetime. The driver for Born Qualified was using Additive Manufacturing (AM) to change the qualification paradigm for low volume, high value, high consequence, complex parts that are common in high-risk industries such as ND, defense, energy, aerospace, and medical. AM offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this effort.

Laser engineered net shaping (LENS) is an additive manufacturing process that presents a promising method of creating or repairing metal parts not previously feasible with traditional manufacturing methods. The LENS process involves the directed deposition of metal via a laser power source and a spray of metal powder co-located to create and feed a molten pool (also referred to generically as Directed Energy Deposition, DED). DED technologies are being developed for use in prototyping, repair, and manufacturing across a wide variety of materials including stainless steel, titanium, tungsten carbide-cobalt, aluminum, and nickel based superalloys. However, barriers to the successful production and qualification of LENS produced or repaired parts remain. This work proposes a finite element (FE) analysis methodology capable of simulating the LENS process at the continuum length scale (i.e. part length scale). This method incorporates an element activation scheme wherein only elements that exceed the material melt temperature during laser heating are activated and carried through to subsequent analysis steps. Following the initial element activation calculation, newly deposited, or activated elements and the associated geometry, are carried through to thermal and mechanical analyses to calculate heat flow due to radiation, convection, and conduction as well as stresses and displacements. The final aim of this work is to develop a validated LENS process simulation capability that can accurately predict temperature history, final part shape, distribution of strength, microstructural properties, and residual stresses based on LENS process parameters.

The changes experienced in synovial joints with osteoarthritis involve coupled chemical, biological, and mechanical processes. The aim of this study was to investigate the consequences of increasing permeability in articular cartilage (AC), calcified cartilage (CC), subchondral cortical bone (SCB), and subchondral trabecular bone (STB) as observed with osteoarthritis. Two poroelastic finite element models were developed using a depth-dependent anisotropic model of AC with strain-dependent permeability and poroelastic models of calcified tissues (CC, SCB, and STB). The first model simulated a bone-cartilage unit (BCU) in uniaxial unconfined compression, while the second model simulated spherical indentation of the AC surface. Results indicate that the permeability of AC is the primary determinant of the BCU's poromechanical response while the permeability of calcified tissues exerts no appreciable effect on the force-indentation response of the BCU. In spherical indentation simulations with osteoarthritic permeability properties, fluid velocities were larger in magnitude and distributed over a smaller area compared to normal tissues. In vivo, this phenomenon would likely lead to chondrocyte death, tissue remodeling, alterations in joint lubrication, and the progression of osteoarthritis. For osteoarthritic and normal tissue permeability values, fluid flow was predicted to occur across the osteochondral interface. These results help elucidate the consequences of increases in the permeability of the BCU that occur with osteoarthritis. Furthermore, this study may guide future treatments to counteract osteoarthritis.

With osteoarthritis, a complex set of progressive chemical, biological, and mechanical changes occur in both cartilage and bone. The aim of this study is to develop a high-fidelity computational model of the complete bone–cartilage unit to study the evolution of osterarthritis-induced articular cartilage (AC) damage and remodeling of subchondral cortical bone (SCB) and subchondral trabecular bone (STB). A finite element model of spherical indentation was developed with a depth-dependent anisotropic model of degenerating articular cartilage, a calcified cartilage (CC) zone, and SCB and STB remodeling regions. Calcified tissue (CC, SCB, and STB) and AC material regions were integrated to form an evolutionary bone–cartilage unit model. Results indicate that with indentation loading, articular cartilage damage occurs at the articular surface. Furthermore, bone remodeling was predicted to occur with a net stiffening of the subchondral bone plate. Changes in indentation force were minimal (<2%) between initial and final peak indentation loading. However, additional degradation and wear of AC and/or alterations in loading may have more pronounced effects on the mechanical response of the bone–cartilage unit. Bone remodeling and articular cartilage damage predictions are consistent with experimental observations that cartilage damage begins at the articular surface and subchondral bone experiences a thickening (i.e., stiffening) response with osteoarthritis. Our results provide insight into the early-term initiation behavior of osteoarthritis; the potential consequences of evolutions in AC, SCB, and STB with disease progression; and may guide future experimental and computational studies to elucidate mechanisms of osteoarthritis progression.