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DOE OSTI2020

A simple model to scope out parameter space for indirect drive designs on NIF

In this work, we present a simple model to scope out parameter space for indirect-drive, inertial confinement fusion designs for the National Ignition Facility laser. Because the parameter space is large, simple models can be used to identify regions of parameter space for further study with more sophisticated models and experiments. We include a model for Hohlraum radiation drive and symmetry—both based on empirical scalings from the data. The model for radiation drive is based on assuming that the high atomic number (Z) Hohlraum wall dominates the energy balance during the high power, peak of the pulse (≳ 300 TW). We find that the time-dependent radiation drive flux can be described by the running integral of the laser energy divided by the Hohlraum area multiplied by constant slopes in two distinct time periods. The first period is when the laser power rises rapidly, so the radiation temperature increases due to changes in laser power and wall albedo. The second period is during peak power—here, the laser power is typically held constant—so, the radiation temperature increases only due to changes in the wall albedo. This model is applied to several NIF designs with different Hohlraum sizes, laser pulse length durations, and peak powers and energies. Drive and symmetry models can be combined to find regions of parameter space that have high capsule absorbed energy while maintaining a symmetric implosion. We propose a new metric for evaluating designs based on minimizing the radius at which the maximum implosion kinetic energy is achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar: SUMO Default vs. Radar-Measured CF model Parameters

In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior, including acceleration, deceleration, and time headway distribution. Demand-calibrated SUMO simulations are run using empirical CF parameter distributions, and three CF models are evaluated: IDM, EIDM, and Krauss. By emulating radar data in SUMO and processing simulated vehicle traces, discrepancies between empirical and simulated parameter distributions are identified. Further analysis includes comparisons with default SUMO CF model parameters. The findings reveal that measured accelerations differ from CF model parameter accelerations and using the empirical value ($\mu = 0.89m/s^2$) leads to unrealistic simulations that fail volume-based calibration. Default parameters for all three models reasonably approximate the mean and median of measured parameters, but fail to capture the true distribution shape, partly due to homogeneity when using default parameters. The results show that it is more effective to simulate with the default parameters provided by SUMO rather than using measurements of real-world distributions without additional calibration. Future work will investigate closing the loop between the measured real-world and SUMO distributions using traditional calibration tactics, as well as assess the impact of calibrated vs. default CF parameters on simulation outputs like fuel consumption.

Schrader, Max (ORCID:0000000336737672)↗

DOE OSTI2017

Identification of NPP transients using artificial intelligence - 335

If the accidents happen in nuclear power plants (NPPs), the NPP operators identify the transients through observing the behaviors of the major parameters. However, the integrity of the instrumentation signals is not ensured under the accident circumstances and the major parameters essential in identifying the transients can rapidly change although the instruments generate accurate signals. Thus, to successfully control the accidents by taking necessary measures relatively faster, it is very important to provide the operators with the information that can identify the transients and accidents accurately. In this study, the transients of severe accidents in NPPs are identified and classified using artificial intelligence methodologies. Several transients are identified using support vector classification (SVC) and probabilistic neural network (PNN) as artificial intelligence methodologies. The used data for the transients are the simulation data using the modular accident analysis program (MAAP) code for the optimized power reactors (OPR1000s). The time-integrated values of chosen simulated sensor signals are used as the input variables for identifying the transients. As a result of this study, the proposed models identified the transients quite precisely. Therefore, the quite accurate identification of the transients indicates the excellence of these artificial intelligence methods and they will produce useful supporting information for the operators even under extreme transient circumstances in NPPs. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Understanding Evolution of Lithium Trivanadate Cathodes During Cycling via Reformulated Physics-Based Models and Experiments

Degradation of lithium trivanadate ( Li x V 3 O 8 ) cathodes has been widely reported in the literature, but studies have offered little insight towards developing a detailed understanding of the evolution of the active material, and have been inconclusive as to the root cause of degradation. Here, we refit a validated physics-based model to discharge curves over the course of cycling at C/5, and use the evolution of the model parameters to track evolution of the cathode. A regularization penalty for adjusting model parameters from the validated model is introduced as a framework to identify which model parameters can explain a significant portion of the observed change in the voltage profile over the course of cycling. SEM reveals that lithium trivandate particles fracture upon cycling at C/5, consistent with the results of the parameter estimation, deactivation of lithium trivanadate and faster diffusion of lithium within the active particles. The physics-based model is then used to design modified cycling protocols which identify the phase transformation during discharge of lithium trivanadate as the driver of the particle fracture and capacity fade.

25 ENERGY STORAGE↗

DOE OSTI2017

Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments

In-situ (scanning) transmission electron microscopy (S/TEM) is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here we show that video shot boundary detection (SBD) can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Identifying sensitive ranges in global warming precipitation change dependence on convective parameters

Abstract A branch‐run perturbed‐physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end‐of‐century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3 mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low‐entrainment range of the parameter for turbulent entrainment in the deep convection scheme. This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive “dangerous ranges.” The low‐entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

ODI notebook additive_manufacturing_video_2022

Additive Manufacturing, video dataset Two-photon lithography (TPL) is a widely used 3D nanoprinting technique that uses laser light to create objects. Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "Automated detection of part quality during two-photon lithography via deep learning." Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures." Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.

Mulakken, NishaJ↗

DOE OSTI2018

Evaluation of non-invasive biomonitoring of 2,4-Dichlorophenoxyacetic acid (2,4-D) in saliva

The objective of this study was to evaluate the potential for noninvasive biomonitoring of 2,4-dichlorophenoxyacetic acid (2,4-D) in saliva. Using an in vitro rat salivary gland epithelial cell (SGEC) system, a collection of experiments investigating chemical protein binding, temporal and directional transport, as well as competitive transport with para-aminohippuric acid (PAH), a substrate for renal organic anion transporters, was conducted to identify cellular transport parameters required to computationally model salivary transport of 2,4-D. Additionally, a physiological protein gradient was implemented to mimic physiologically relevant concentrations of protein in rat plasma and saliva, and under these conditions the transfer of 2,4-D was markedly slower, driven by increased protein binding (i.e. reduced free 2,4-D species available to cross salivary barrier). The rate of transfer was directly proportional to the amount of unbound 2,4-D and demonstrated no indication of active transport. An in vivo assessment of 2,4-D exposure in rats revealed a non-linear protein binding response in plasma, indicating saturated protein binding and increased levels of free 2,4-D species at higher doses. A strong correlation between concentrations in saliva and free unbound species in plasma was observed (Pearson correlation coefficient = 0.95). Saliva:plasma 2,4-D ratios measured in vivo (0.0079) were comparable over dose, but significantly different than ratios measured in vitro (physiological conditions) (0.034), possibly due to 2,4-D concentrations in saliva not being at equilibrium with 2,4-D concentrations in blood, as well as physiological features absent in in vitro settings (e.g. blood flow). We demonstrated that 2,4-D is consistently transported into saliva using both in vitro and in vivo models, making 2,4-D a potential candidate for human non-invasive salivary biomonitoring. Further work is needed to understand whether current sensor limits of detection are sufficient to measure occupationally relevant exposures.

Carver, Zana A.↗

DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

Source record↗

DOE OSTI2015

Evaluation of Cooling Conditions for a High Heat Flux Testing Facility Based on Plasma-Arc Lamps

The new Irradiated Material Target Station (IMTS) facility for fusion materials at Oak Ridge National Laboratory (ORNL) uses an infrared plasma-arc lamp (PAL) to deliver incident heat fluxes as high as 27 MW/m 2 . The facility is being used to test irradiated plasma-facing component materials as part of the joint US-Japan PHENIX program. The irradiated samples are to be mounted on molybdenum sample holders attached to a water-cooled copper rod. Depending on the size and geometry of samples, several sample holders and copper rod configurations have been fabricated and tested. As a part of the effort to design sample holders compatible with the high heat flux (HHF) testing to be conducted at the IMTS facility, numerical simulations have been performed for two different water-cooled sample holder designs using the ANSYS FLUENT 14.0 commercial computational fluid dynamics (CFD) software package. The primary objective of this work is to evaluate the cooling capability of different sample holder designs, i.e. to estimate their maximum allowable incident heat flux values. 2D axisymmetric numerical simulations are performed using the realizable k-ε turbulence model and the RPI nucleate boiling model within ANSYS FLUENT 14.0. The results of the numerical model were compared against the experimental data for two sample holder designs tested in the IMTS facility. The model has been used to parametrically evaluate the effect of various operational parameters on the predicted temperature distributions. The results were used to identify the limiting parameter for safe operation of the two sample holders and the associated peak heat flux limits. The results of this investigation will help guide the development of new sample holder designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1993

Optimization of a Centrifugal Impeller Design Through CFD Analysis

This paper discusses the procedure, approach and Rocketdyne CFD results for the optimization of the NASA consortium impeller design. Two different approaches have been investigated. The first one is to use a tandem blade arrangement, the main impeller blade is split into two separate rows with the second blade row offset circumferentially with respect to the first row. The second approach is to control the high losses related to secondary flows within the impeller passage. Many key parameters have been identified and each consortium team member involved will optimize a specific parameter using 3-D CFD analysis. Rocketdyne has provided a series of CFD grids for the consortium team members. SECA will complete the tandem blade study, SRA will study the effect of the splitter blade solidity change, NASA LeRC will evaluate the effect of circumferential position of the splitter blade, VPI will work on the hub to shroud blade loading distribution, NASA Ames will examine the impeller discharge leakage flow impacts and Rocketdyne will continue to work on the meridional contour and the blade leading to trailing edge work distribution. This paper will also present Rocketdyne results from the tandem blade study and from the blade loading distribution study. It is the ultimate goal of this consortium team to integrate the available CFD analysis to design an advanced technology impeller that is suitable for use in the NASA Space Transportation Main Engine (STME) fuel turbopump.

Chen, W. C.↗

DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Source record↗

DOE OSTI2021

Role of peracetic acid on the disruption of lignin packing structure and its consequence on lignin depolymerisation

Peracetic acid (PAA) is an effective oxidant capable of solubilising lignin and efficiently depolymerising it to selective phenolic compounds; however, the specific role by which PAA initiates the depolymerisation is still elusive. Herein, interaction between PAA and the lignin macromolecule and the consequent structural changes of the latter were studied by characterising the lignin packing structure and its associated changes during the oxidation process. While the lignin packing structure and its changes associated with the PAA-mediated oxidation were probed by X-ray diffraction, the impact of the PAA on different chemical functionalities present in the lignin structure was established by 13 C and 1 H– 13 C heteronuclear single-quantum coherence nuclear magnetic resonance (NMR) spectroscopy. Further, combining the NMR spectroscopy results, and the product distribution, we conclude that the predominant reaction pathway for the oxidative depolymerisation of lignin with PAA is the Baeyer–Villiger oxidation of the ketone formed by the oxidation of the benzylic hydroxyl group adjacent to the β-O-4 linkage. The experimental evidence provided herein corroborated that PAA instigates oxygen insertion to the lignin macromolecule resulting in disruption of its packing structures and facilitates depolymerisation. We also investigated various metal oxide and mixed metal oxide catalysts to identify effective catalysts that further enhance the efficiency of PAA-mediated depolymerisation of lignin and produce selective monomeric phenolic compounds. Techno-economic analysis was also conducted to identify the key parameters associated with this oxidative process that need to be considered for possible commercial application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2009

Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean

Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.

SSH (SEA SURFACE HEIGHT)↗

DOE OSTI2011

Analysis of Drought Impacts on Electricity Production in the Western and Texas Interconnections of the United States

Electricity generation relies heavily on water resources and their availability. To examine the interdependence of energy and water in the electricity context, the impacts of a severe drought to assess the risk posed by drought to electricity generation within the western and Texas interconnections has been examined. The historical drought patterns in the western United States were analyzed, and the risk posed by drought to electricity generation within the region was evaluated. The results of this effort will be used to develop scenarios for medium- and long-term transmission modeling and planning efforts by the Western Electricity Coordination Council (WECC) and the Electric Reliability Council of Texas (ERCOT). The study was performed in response to a request developed by the Western Governors Association in conjunction with the transmission modeling teams at the participating interconnections. It is part of a U.S. Department of Energy-sponsored, national laboratory-led research effort to develop tools related to the interdependency of energy and water as part of a larger interconnection-wide transmission planning project funded under the American Recovery and Reinvestment Act. This study accomplished three main objectives. It provided a thorough literature review of recent studies of drought and the potential implications for electricity generation. It analyzed historical drought patterns in the western United States and used the results to develop three design drought scenarios. Finally, it quantified the risk to electricity generation for each of eight basins for each of the three drought scenarios and considered the implications for transmission planning. Literature on drought impacts on electricity generation describes a number of examples where hydroelectric generation capacity has been limited because of drought but only a few examples of impact on thermoelectric generation. In all documented cases, shortfalls of generation were met by purchasing power from the market, albeit at higher prices. However, sufficient excess generation and transmission must be available for this strategy to work. Although power purchase was the most commonly discussed drought mitigation strategy, a total of 12 response strategies were identified in the literature, falling into four main categories: electricity supply, electricity demand response, alternative water supplies, and water demand response. Three hydrological drought scenarios were developed based on a literature review and historical data analysis. The literature review helped to identify key drought parameters and data on drought frequency and severity. Historical hydrological drought data were analyzed for the western United States to identify potential drought correlations and estimate drought parameters. The first scenario was a West-wide drought occurring in 1977; it represented a severe drought in five of the eight basins in the study area. A second drought scenario was artificially defined by selecting the conditions from the 10th-percentile drought year for each individual basin; this drought was defined in this way to allow more consistent analysis of risk to electricity generation in each basin. The final scenario was based upon the current low-flow hydro modeling scenario defined by WECC, which uses conditions from the year 2001. These scenarios were then used to quantify the risk to electricity generation in each basin. The risk calculations represent a first-order estimate of the maximum amount of electricity generation that might be lost from both hydroelectric and thermoelectric sources under a worst-case scenario. Even with the conservative methodology used, the majority of basins showed a limited amount of risk under most scenarios. The level of risk in these basins is likely to be amenable to mitigation by known strategies, combined with existing reserve generation and transmission capacity. However, the risks to the Pacific Northwest and Texas Basins require further study. The Pacific Northwest is vulnerable because of its heavy reliance on hydroelectric generation. Texas, conversely, is vulnerable because of its heavy dependence on thermoelectric generation, which relies on surface water for cooling, along with the fact that this basin seems to experience more severe drought events on average. Further modeling analysis will be performed in conjunction with the modeling teams at the participating interconnections (WECC and ERCOT) to explore the transmission implications of the drought scenarios in more detail. Given the first-order nature of this analysis, more detailed study of the potential impacts of drought on electricity generation is recommended. Future analyses should attempt to model the potential impacts of drought at the power-plant level, including potential mitigation strategies; include the effects of drought duration; understand the impacts of climate change; and consider economic impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Multi-area parameter error identification for large power systems

Power grid model parameters may contain errors due to various reasons. Detecting and correcting parameter errors typically requires significant computational effort due to the size and complexity of the parameter database. While the normalized Lagrange multiplier (NLM) method can effectively detect, identify and correct parameter errors, its computational burden could rapidly grow with increasing system size. This paper addresses this issue by proposing a multi-area parameter error identification method. Each area has its own outlier detection tool for detecting the incorrect parameters and measurements within the area. On the other hand, due to the reduced redundancy at area boundaries, parameter errors on branches incident to boundary buses may not be detected. Such errors are subsequently detected by a coordination level estimator completing the system-wide parameter detection procedure. In conclusion, performance of the developed method is demonstrated using the IEEE 118-bus and 2000-bus Texas synthetic systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

DOE OSTI2024

Atmosphere Effects in Laser Powder Bed Fusion: A Review

The use of components fabricated by laser powder bed fusion (LPBF) requires the development of processing parameters that can produce high-quality material. Manipulating the most commonly identified critical build parameters (e.g., laser power, laser scan speed, and layer thickness) on LPBF equipment can generate acceptable parts for established materials and moderately intricate part geometries. The need to fabricate increasingly complex parts from unique materials drives the limited research into LPBF process control using underutilized parameters, such as atmosphere composition and pressure. As presented in this review, manipulating atmosphere composition and pressure in laser beam welding has been shown to expand processing windows and produce higher-quality welds. The similarities between laser beam welding and laser-based AM processes suggest that this atmosphere control research could be effectively adapted for LPBF, an area that has not been widely explored. Tailoring this research for LPBF has significant potential to reveal novel processing regimes. This review presents the current state of the art in atmosphere research for laser beam welding and LPBF, with a focus on studies exploring cover gas composition and pressure, and concludes with an outlook on future LPBF atmosphere control systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗