Measurement Uncertainty of Surface Temperature Distributions for Laser Powder Bed Fusion Processes.

This paper describes advances in measuring the characteristic spatial distribution of surface temperature and emissivity during laser-metal interaction under conditions relevant for laser powder bed fusion (LPBF) additive manufacturing processes. Detailed descriptions of the measurement process, results, and approaches to determining uncertainties are provided. Measurement uncertainties have complex dependencies on multiple process parameters, so the methodology is demonstrated on one set of process parameters and one material. Well-established literature values for high-purity nickel solidification temperature and emissivity at the solidification temperature were used to evaluate the predicted uncertainty of the measurements. The standard temperature measurement uncertainty is found to be approximately 0.9% of the absolute temperature (16 AC), and the standard relative emissivity measurement uncertainty is found to be approximately 8% at the solidification point of high-purity nickel, both of which are satisfactory. This paper also outlines several potential sources of test uncertainties, which may require additional experimental evaluation. The largest of these are the metal vapor and ejecta that are produced as process by-products, which can potentially affect the imaging quality, reflectometry results, and thermal signature of the process, while also affecting the process of laser power delivery. Furthermore, the current paper focuses strictly on the uncertainties of the emissivity and temperature measurement approach and therefore does not detail a variety of uncertainties associated with experimental controls that must be evaluated for future generation of reference data.

Identifying uncertainty in laser powder bed fusion additive manufacturing models.

As additive manufacturing (AM) matures, models are beginning to take a more prominent stage in design and process planning for AM. A limitation frequently encountered in AM models is a lack of indication about their precision and accuracy. Often overlooked, information on model uncertainty is required for validation of AM models, qualification of AM-produced parts, and uncertainty management. This paper presents a discussion on the origin and propagation of uncertainty in laser powder bed fusion (L-PBF) models. Four sources of uncertainty are identified: modeling assumptions, unknown simulation parameters, numerical approximations, and measurement error in calibration data. Techniques to quantify uncertainty in each source are presented briefly, along with estimation algorithms to diminish prediction uncertainty with the incorporation of online measurements. The methods are illustrated with a case study based on a transient, stochastic thermal model designed for melt pool width predictions. Model uncertainty is quantified for single track experiments and the effect of online estimation in overhanging structures is studied via simulation. The application of these concepts to estimation and control of the L-PBF process is suggested.

Cross-Sectional Melt Pool Geometry of Laser Scanned Tracks and Pads on Nickel Alloy 718 for the 2022 Additive Manufacturing Benchmark Challenges.

The Additive Manufacturing Benchmark Series (AM Bench) is a NIST-led organization that provides a continuing series of additive manufacturing benchmark measurements, challenge problems, and conferences with the primary goal of enabling modelers to test their simulations against rigorous, highly controlled additive manufacturing benchmark measurement data. To this end, single-track (1D) and pad (2D) scans on bare plate nickel alloy 718 were completed with thermography, cross-sectional grain orientation and local chemical composition maps, and cross-sectional melt pool size measurements. The laser power, scan speed, and laser spot size were varied for single tracks, and the scan direction was varied for pads. This article focuses on the cross-sectional melt pool size measurements and presents the predictions from challenge problems. Single-track depth correlated with volumetric energy density while width did not (within the studied parameters). The melt pool size for pad scans was greater than single tracks due to heat buildup. Pad scan melt pool depth was reduced when the laser scan direction and gas flow direction were parallel. The melt pool size in pad scans showed little to no trend against position within the pads. Uncertainty budgets for cross-sectional melt pool size from optical micrographs are provided for the purpose of model validation.

Genomic analysis of human brain metastases treated with stereotactic radiosurgery reveals unique signature based on treatment failure.

Stereotactic radiosurgery (SRS) has been shown to be efficacious for the treatment of limited brain metastasis (BM); however, the effects of SRS on human brain metastases have yet to be studied. We performed genomic analysis on resected brain metastases from patients whose resected lesion was previously treated with SRS. Our analyses demonstrated for the first time that patients possess a distinct genomic signature based on type of treatment failure including local failure, leptomeningeal spread, and radio-necrosis. Examination of the center and peripheral edge of the tumors treated with SRS indicated differential DNA damage distribution and an enrichment for tumor suppressor mutations and DNA damage repair pathways along the peripheral edge. Furthermore, the two clinical modalities used to deliver SRS, LINAC and GK, demonstrated differential effects on the tumor landscape even between controlled primary sites. Our study provides, in human, biological evidence of differential effects of SRS across BM's.

Predictive modeling and optimization of multi-track processing for laser powder bed fusion of nickel alloy 625.

This paper presents an integrated physics-based and statistical modeling approach to predict temperature field and meltpool geometry in multi-track processing of laser powder bed fusion (L-PBF) of nickel 625 alloy. Multi-track laser processing of powder material using L-PBF process has been studied using 2-D finite element simulations to calculate temperature fields along the scan and hatch directions for three consecutive tracks for a moving laser heat source to understand the heating and melting process. Based on the predicted temperature fields, width, depth and shape of the meltpool is determined. Designed experiments on L-PBF of nickel alloy 625 powder material are conducted to measure the relative density and meltpool geometry. Experimental work is reported on the measured density of built coupons and meltpool size. Statistically-based predictive models using response surface regression for relative density, meltpool geometry, peak temperature, and time above melting point are developed and multi-objective optimization studies are conducted by using genetic algorithm and swarm intelligence.