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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Advanced Test Reactor Neutron Dosimetry Report - Cycle 175B-1

Results of neutron dosimetry measurements in ATR for cycle 175B-1 are presented. A single set of cobalt and nickel wires were installed in numerous irradiation locations for the duration of the cycle. The specific activity of these wire segments can be used in conjunction with the presented cycle history information to determine the thermal- and fast-neutron fluence rates for each irradiation position during the cycle using the referenced standard test methods.

175B↗
DOE OSTI2020

Understanding Li-Ion Cell Internal Short Circuit and Thermal Runaway through Small, Slow and In Situ Sensing Nail Penetration

Here we report a small, slow and in situ sensing (3S) nail penetration test method to understand Li-ion cell internal short circuit (ISC) and thermal runaway. The method not only keeps conventional nail penetration's advantage of simple implementation, but also enhances its relevance to field failures and enables detailed in situ diagnosis. It was applied to 3-Ah pouch cells and revealed insights that could not be captured by conventional methods. Most interestingly, multiple in situ temperature peaks were observed during a period of over 100 s before thermal runaway. These initial peaks exceeded safety limit but the temperature rapidly decreased after each peak instead of causing immediate thermal runaway. Further investigation suggested that the initial temperature peaks occurred when nail tip reached aluminum foil current collector to form a low resistance ISC between anode and aluminum foil. The rapid temperature decrease after each peak can be attributed to sudden drop of ISC current, which can be further attributed to rupture of aluminum foil and increase of contact resistance. The findings show that 3S nail penetration test can separate processes of ISC from thermal runaway and provide details of ISC at the level of individual electrode and current collector.

25 ENERGY STORAGE↗
DOE OSTI2022

Innovative Method for Welding in Generation 3 CSP to Enable Reliable Manufacturing of Solar Receivers to withstand Daily Cycling at Temperatures Above 700°C (Final Technical Report)

Inconel® Alloy 740H® (alloy 740H) was the first age-hardenable nickel-based alloy approved by the ASME Boiler & Pressure Vessel Code for use in pressure-boundary applications. Over the past ~20 years the alloy has been optimized for weldability and high-temperature stability, approved for use in different applications. Development of a supply chain combined with the advantageous properties of the alloy (high-temperature creep strength, oxidation and corrosion resistance, etc.) have resulted in the alloy being applied to new high-temperature power cycle demonstration projects, and of particular interest are applications to concentrating solar power (CSP) to enable higher-efficiency Generation 3 CSP systems and the corresponding supercritical CO 2 (sCO 2 ) power cycle components (heat exchangers, piping, etc.). The high allowable stresses of alloy 740H also make it a desirable material for current Generation 2 CSP solar power receivers to improve cyclic capability and/or reduce receiver height. Recent experiences in demonstration projects utilizing alloy 740H identified cracking issues during welding and fabrication. In this project, a detailed study was done to confirm and clarify the Stress Relaxation Cracking (SRxC) mechanism, also known as stress relief cracking or strain-age cracking (SAC), during post-weld heat-treatment (PWHT). This involved detailed microscopy and advanced characterization to understand the root cause(s) of three failures obtained from industry. Based in-part on these findings, a targeted laboratory based SRxC test method was utilized to evaluate variables such as heat-to-heat variations, strain level, PWHT temperature, and starting material condition on three heats of alloy 740H. Industrial shop welding of cold-worked plates was also conducted. The research showed the following: SRxC was confirmed as the cracking mechanism for all field failures; Stress state (from residual stresses, constraint, deformation, and local stress concentrations) was playing a significant role in field failures and laboratory testing confirmed increasing susceptibility for all heats with increasing strain levels. High levels of microstructural strain were identified at crack initiation locations, in some cases leading to local recrystallization; Precipitate free zones (PFZs) at grain boundaries were found at relaxation cracks and crack initiation locations uniquely associated with SRxC in alloy 740H. Laboratory testing reproduced this microstructural feature which had only previously been reported in long-term creep testing of weldments. Advanced nano-scale characterization confirmed the presence of a moving boundary leading to coarsening of precipitates and PFZs where damage accumulated; The research suggested heat-to-heat variations due to local chemistry and processing may influence SRxC susceptibility, but more work is needed to fully clarify these effects. To disseminate the key learnings from this research to the scientific and engineering communities and alloy 740H end users, multiple technical publications and presentations were made, an industrial alloy 740H users meeting was held, and a new industry guideline specification document which can be directly implemented by end-users of alloy 740H was produced.

14 SOLAR ENERGY↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Field-Aging Test Bed for Behind-the-Meter PV + Energy Storage

Small DC-coupled battery test systems are deployed at the National Renewable Energy Laboratory to evaluate capacity fade models and report on performance parameters such as round-trip efficiency under indoor and outdoor deployment scenarios. Initial commercial battery products include LG Chem RESU lithium-ion (Li-ion) and Avalon vanadium redox flow batteries. Adapting indoor lab-scale test methods to outdoor systems has challenges, including maintaining constant temperature and fully controlling batteries through standard discharge curves. Initial measurements show the Li-ion battery systems performing within expectations, near 85% round-trip efficiency. Initial lifetime modeling and measurements indicate that battery capacity could degrade by 20%-35% over 10 years at current rates.

14 SOLAR ENERGY↗
DOE OSTI2022

Understanding syringeability and injectability of high molecular weight PEO solution through time-dependent force-distance profiles

Opioid medications play a vital role in treating moderate to severe pain. Unfortunately, many drug misusers and abusers attempt to alter the formulations or properties of these drugs by manipulation, (e.g., crushing, chewing, smoking, snorting, injecting). The intravenous (IV) route is most dangerous to abusers, as the drugs directly enter the circulatory system and produce intense euphoria. To obtain a full understanding of the impact of syringe factors (e.g., needle gauge size, needle length, syringe barrel size), on the ease of injection, we undertook a comprehensive assessment of syringeability and injectability of manipulated abuse-deterrent formulations (ADFs). A texture analyzer-based testing method was developed for the measurement of the resistance force of pulling, holding, and pushing phases of injections. Results showed that the finer needle gauge sizes required higher injection force to withdraw drug solutions. In addition, the syringed liquid volume was highly dependent on needle gauge size, holding time, and sample viscosity. In most cases, a lower needle gauge number and a longer holding time increased the syringed volume. Needle length was highly correlated to injection force (R 2 = 0.99). Using longer needles to inject drug solution requires greater force. Furthermore, large barrel size was correlated to pushing force (R 2 = 0.99); thus, increasing the difficulty of pushing the plunger of a large syringe with one hand. Lastly, relationships between injection force, sample viscosity, and testing conditions were elucidated using a mathematical model, which could be used in the future to assess and predict injection force of solution samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗
DOE OSTI2022

Detailed Compositional Comparison of Hydrogenated Vegetable Oil with Several Diesel Fuels and Their Effects on Engine-Out Emissions

The Coordinating Research Council (CRC) is actively involved in developing and applying advanced analytical techniques to the chemical characterization of transportation fuels. Here, this article complements a 2017 CRC project to quantify and compare the effects of a commercially available renewable diesel fuel (hydrotreated vegetable oil [HVO]) and an ultralow sulfur diesel (ULSD) fuel on engine-out gaseous and particulate matter (PM) emissions from a light-duty vehicle. Results showed that the combustion of HVO fuel had an advantage over ULSD in terms of lowering engine-out emissions (THC, CO, NO x , etc.). Furthermore, this advantage is strongly related to the fuel composition. This article summarizes the results of advanced and comprehensive analytical tests on the same ULSD and HVO fuels and attempts to connect some of the engine-out emissions results to fuel composition and specific chemical structures. A variety of test methods, generally unavailable in combination, were employed, such as one-dimensional (1D) and two-dimensional (2D) gas chromatography (GC), nuclear magnetic resonance spectroscopy (NMR), and high-pressure solid-liquid phase transition experiments. In summary, the ULSD sample was found to have representation across the expected set of hydrocarbon classes typical for the sample type. Interestingly, a high content of cycloparaffins (>50 wt%) and a very low content of diaromatics (~2 wt%) were present. While not without precedent, these are higher and lower, respectively, than typically found for commercial ULSD compositions. In contrast, HVO was found to consist of only two hydrocarbon classes: n-paraffins (~10 wt%) and iso-paraffins (~90 wt%), both predominantly in a narrow carbon atom number range (i.e., C14–C18). HVO engine-out emissions results for the LA-92 and steady-state testing can be tracked to the narrow carbon atom number range of the n-paraffins and iso-paraffins, which result in a high cetane number fuel having a narrow distillation range. Previously, the low-temperature operability of HVO has been a concern, but that appears not be the case for this particular HVO. HVO and ULSD were evaluated at pressures up to ~275 MPa and found to have comparable solid-liquid equilibria despite significant compositional differences.

09 BIOMASS FUELS↗
DOE OSTI2020

Measurements of the Flow in the Vicinity of an Additively Manufactured Turbine Leading-Edge Using X-Ray Particle Tracking Velocimetry

X-ray particle tracking velocimetry (PTV) is performed, for the first time, to measure the velocity field inside a leading-edge of a turbine blade made by laser-additive-manufacturing (LAM) process. The traditional showerhead holes were replaced by a porous matrix in the leading-edge. The flow through such a leading-edge piece cannot be faithfully recreated by traditional prototype testing methods due to the surface roughness and imperfections caused by LAM process. Hence, direct measurement is the only option. However, it is difficult to measure flow inside such pieces with traditional velocimetry measurements due to the existence of metallic walls. Moreover, small internal size and high flow speeds call for a measurement technique with high spatial and temporal resolutions. To address these issues, we performed time-resolved X-ray PTV using the Advanced Photon Source (APS) synchrotron facility at the Argonne National Laboratory (ANL). A hydraulic system was constructed to run water, mixed with seeding particles, through the leading-edge piece. A high-speed camera captured the images of the seeding particles, which were later processed to create particle tracks. The time-averaged velocity field showed distinct pairs of vortices located in front of the porous outlet inside the leading-edge piece. The inlet channel showed reversed flow due to partial obstruction by the porous inlet of the test piece. Such knowledge of the flow field inside a leading-edge of a turbine blade will help us to design better cooling paths leading to higher cooling efficiency and increased life-span of a turbine blade.

42 ENGINEERING↗
DOE OSTI2020

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Core Characterization of Bakken Shale from the Bedwell 33-52-1-1H Well, Sheridan County, Montana

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core of the Bedwell 33-52-1-1H well (API 25-091-21920), a wildcat field in Sheridan County, Montana. The primary impetus of this work is to provide a unique dataset to researchers at universities, national laboratories, geological surveys, and other locations for additional analyses. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/bedwell-33-52-1-1h-well. The equipment and techniques used to characterize the full core were non-destructive, enabling future examinations and analyses to be performed on these cores. However, none of the equipment used was suitable for direct visualization of the pore space in fine-grained structures such as those found in shales; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. A selection of samples (Table 1) were cored, sliced, and powdered for additional characterization analyses. These analyses did involve destructive subsampling of the full core at discrete sections, and the results are presented here in the context of the larger core description. Selected sections of the core were removed from the full core for detailed analyses using the following destructive techniques: bulk inductively coupled plasma-optical emission spectroscopy (ICP-OES), isolation of carbon and sulfur, Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and higher resolution CT scan with NETL’s micro-CT scanning systems. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Quantitative Non-Destructive Evaluation of Fatigue Damage Based on Multi-Sensor Fusion

Based on sensor fusion and machine learning, this project developed a novel non-destructive evaluation (NDE) methodology, which consists of a remaining useful life (RUL) prediction framework and regression models for predicting residual stress and full width at half maximum (FWHM). A series of fatigue testing experiments were conducted using 5052-H32 aluminum alloy specimens. All specimens were measured using linear ultrasonic (LU) and nonlinear ultrasonic (NLU) testing methods non-destructively. Machine learning models were developed to use LU and NLU measurements to predict loading condition, fatigue level, residual stress, and FWHM. It was demonstrated that the developed methodology could distinguish new and fatigue specimens with an accuracy of 97.53%. Also, the prediction errors for residual stress and FWHM were as low as 4.73% and 1.62%, respectively. An interactive database was created to publicly share the data generated from the project. It is envisioned that the developed NDE technology will equip manufacturers with a responsive screening system for incoming used metallic components, and potentially lead to a significant increase in using used metallic components for remanufacturing.

42 ENGINEERING↗
DOE OSTI2024

StructuredFuzzer: Fuzzing Structured Text-Based Control Logic Applications

Rigorous testing methods are essential for ensuring the security and reliability of industrial controller software. Fuzzing, a technique that automatically discovers software bugs, has also proven effective in finding software vulnerabilities. Unsurprisingly, fuzzing has been applied to a wide range of platforms, including programmable logic controllers (PLCs). However, current approaches, such as coverage-guided evolutionary fuzzing implemented in the popular fuzzer American Fuzzy Lop Plus Plus (AFL++), are often inadequate for finding logical errors and bugs in PLC control logic applications. They primarily target generic programming languages like C/C++, Java, and Python, and do not consider the unique characteristics and behaviors of PLCs, which are often programmed using specialized programming languages like Structured Text (ST). Furthermore, these fuzzers are ill suited to deal with complex input structures encapsulated in ST, as they are not specifically designed to generate appropriate input sequences. This renders the application of traditional fuzzing techniques less efficient on these platforms. To address this issue, this paper presents a fuzzing framework designed explicitly for PLC software to discover logic bugs in applications written in ST specified by the IEC 61131-3 standard. The proposed framework incorporates a custom-tailored PLC runtime and a fuzzer designed for the purpose. We demonstrate its effectiveness by fuzzing a collection of ST programs that were crafted for evaluation purposes. We compare the performance against a popular fuzzer, namely, AFL++. The proposed fuzzing framework demonstrated its capabilities in our experiments, successfully detecting logic bugs in the tested PLC control logic applications written in ST. On average, it was at least 83 times faster than AFL++, and in certain cases, for example, it was more than 23,000 times faster.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗
DOE OSTI2020

Observation of Unconventional Dynamics of Domain Walls in Uniaxial Ferroelectric Lead Germanate

Application of scanning probe microscopy techniques such as piezoresponse force microscopy (PFM) opens the possibility to re-visit the ferroelectrics previously studied by the macroscopic electrical testing methods and establish a link between their local nanoscale characteristics and integral response. It is reported that the nanoscale PFM studies and phase-field modeling of the static and dynamic behavior of the domain structure in the well-known ferroelectric material lead germanate Pb 5 Ge 3 O 11 . Here, several unusual phenomena are revealed: 1) domain formation during the paraelectric-to-ferroelectric phase transition, which exhibits an atypical cooling rate dependence; 2) unexpected electrically induced formation of the oblate domains due to the preferential domain walls motion in the directions perpendicular to the polar axis, contrary to the typical domain growth behavior observed so far; 3) absence of the bound charges at the 180 degrees head-to-head (H-H) and tail-totail (T-T) domain walls, which typically exhibit a significant charge density in other ferroelectrics due to the polarization discontinuity. This strikingly different behavior is rationalized by the phase field modeling of the dynamics of uncharged H-H and T-T domain walls. The results provide a new insight into the emergent physics of the ferroelectric domain boundaries, revealing unusual properties not exhibited by conventional Ising-type walls.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Subsampling and DNA pooling can increase gains through genomic selection in switchgrass

Genomic selection (GS) can accelerate breeding cycles in perennial crops such as the bioenergy grass switchgrass (Panicum virgatum L.). The sequencing costs of GS can be reduced by pooling DNA samples in the training population (TP), only sequencing TP phenotypic outliers, or pooling candidate population (CP) samples. These strategies were simulated for two traits (spring vigor and anthesis date) in three breeding populations. Sequencing only the outlier 50% of the TP phenotype distribution resulted in a penalty of <5% of the predictive ability, measured using cross-validation. Predictive ability also decreased when sequencing progressively fewer TP DNA pools, but TPs constructed from only two phenotypically contrasting DNA samples retained a mean of >80% predictive ability relative to individual TP sequencing. Novel group testing methods allowed greater than one CP individual to be screened per sequenced DNA sample but resulted in a predictive ability penalty. To determine the impact of reduced sequencing, genetic gain was calculated for seven GS scenarios with variable sequencing budgets. Reduced TP sequencing and most CP pooling methods were superior to individual sequence-based GS when sequencing resources were restricted (2,000 DNA samples per 5-yr cycle). Only one scenario was superior to individual sequencing when sequencing budgets were large (8,000 DNA samples per 5-yr cycle). This study highlights multiple routes for reduced sequencing costs in GS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Standardization Gaps in Powder Feedstock Characterization and Establishing Acceptability for Reuse in Additive Manufacturing

Characterization techniques for powder feedstocks used in additive manufacturing (AM) have long been relied upon to describe the inputs to an AM workflow. However, functional gaps remain between tests to measure intrinsic and extrinsic properties with the direct performance within AM equipment. Furthermore, the common practice of reusing powder through multiple build cycles introduces effects and changes to feedstock performance that are otherwise difficult to measure quantitatively. Here, standardization and the development of new test methods have not kept pace with the rapid evolution of the AM industry and its reliance on highly coupled process-structure–property-performance relationships.

Characterization and Analytical Technique↗
DOE OSTI2020

Size-dependent stochastic tensile properties in additively manufactured 316L stainless steel

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

316L stainless steel↗