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DOE OSTI2014

Using Micro-Synchrophasor Data for Advanced Distribution Grid Planning and Operations Analysis

This report reviews the potential for distribution-grid phase-angle data that will be available from new micro-synchrophasors (µPMUs) to be utilized in existing distribution-grid planning and operations analysis. This data could augment the current diagnostic capabilities of grid analysis software, used in both planning and operations for applications such as fault location, and provide data for more accurate modeling of the distribution system. µPMUs are new distribution-grid sensors that will advance measurement and diagnostic capabilities and provide improved visibility of the distribution grid, enabling analysis of the grid’s increasingly complex loads that include features such as large volumes of distributed generation. Large volumes of DG leads to concerns on continued reliable operation of the grid, due to changing power flow characteristics and active generation, with its own protection and control capabilities. Using µPMU data on change in voltage phase angle between two points in conjunction with new and existing distribution-grid planning and operational tools is expected to enable model validation, state estimation, fault location, and renewable resource/load characterization. Our findings include: data measurement is outstripping the processing capabilities of planning and operational tools; not every tool can visualize a voltage phase-angle measurement to the degree of accuracy measured by advanced sensors, and the degree of accuracy in measurement required for the distribution grid is not defined; solving methods cannot handle the high volumes of data generated by modern sensors, so new models and solving methods (such as graph trace analysis) are needed; standardization of sensor-data communications platforms in planning and applications tools would allow integration of different vendors’ sensors and advanced measurement devices. In addition, data from advanced sources such as µPMUs could be used to validate models to improve/ensure accuracy, providing information on normally estimated values such as underground conductor impedance, and characterization of complex loads. Although the input of high-fidelity data to existing tools will be challenging, µPMU data on phase angle (as well as other data from advanced sensors) will be useful for basic operational decisions that are based on a trend of changing data.

25 ENERGY STORAGE↗

DOE OSTI2020

Structural modeling and validation of laminated stacks in magnetic gearing applications

Laminated structures are commonly employed in magnetic gears based on their ability to direct magnetic flux, while inhibiting eddy currents. Unfortunately, the stiffness of the laminated structure is much lower than a solid part, which can lead to unacceptable deflections, given the large magnetic forces and small air gaps in magnetic gears. Finite element analysis of laminations to accurately predict these deflections can be computationally expensive due to the small elements needed to model the thin lamination dimensions. These analyses also have some uncertainty due to the assignment of bonding stiffness. This paper presents a means of accurately modelling the deflection of a laminated stack with reduced complexity and computational time, which is compared to experimental results. Here, the resulting methods are then used to assess the magnetic and mechanical advantages of different designs for the modulating pieces of a magnetic gear.

42 ENGINEERING↗

DOE OSTI2015

Verification and Validation of the PLTEMP/ANL Code for Thermal-Hydraulic Analysis of Experimental and Test Reactors

The document compiles in a single volume several verification and validation works done for the PLTEMP/ANL code during the years of its development and improvement. Some works that are available in the open literature are simply referenced at the outset, and are not included in the document. PLTEMP has been used in conversion safety analysis reports of several US and foreign research reactors that have been licensed and converted. A list of such reactors is given. Each chapter of the document deals with the verification or validation of a specific model. The model verification is usually done by comparing the code with hand calculation, Microsoft spreadsheet calculation, or Mathematica calculation. The model validation is done by comparing the code with experimental data or a more validated code like the RELAP5 code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Model and Validation of Single-Axis Tracking with Bifacial PV

Single-axis tracking is a cost-effective deployment strategy for large-scale ground-mount photovoltaic systems in regions with high direct-normal irradiance. Bifacial modules in 1-axis-tracking systems boost energy yield by 4%-15% depending on module type and ground albedo, with a global average of 9%. This benefit is in addition to the 15%-25% energy gain already afforded by single-axis tracking relative to fixed-tilt deployments. Here, we compare model results against field performance data for two side-by-side bifacial/monofacial tracked systems - one in Albuquerque, NM, USA, and one in eastern Oregon. The Albuquerque system shows monthly rear irradiance gain of 10%-14.9%, and the Oregon bifacial system has an average performance ratio 9.4% higher than the monofacial system. Both results match bifacial irradiance model results within uncertainty. Simulations show that smart tracking algorithms can offer more than 1% improvement on annual energy yield by adjusting tilt angle under cloudy conditions. Finally, ray-tracing simulations investigated edge brightening, suggesting a 15%-25% increase in rear irradiance at the ends of tracker rows, but up to 20% loss from center-mounted torque tubes, creating multiple shadows.

14 SOLAR ENERGY↗

DOE OSTI2019

Estimation of inflow uncertainties in laminar hypersonic double-cone experiments

We propose herein a probabilistic framework for assessing the consistency of an experimental dataset, i.e., whether the stated experimental conditions are consistent with the measurements provided. In case the dataset is inconsistent, our framework allows one to hypothesize and test sources of inconsistencies. This is crucial in model validation efforts. The framework relies on Bayesian inference to estimate experimental settings deemed uncertain, from measurements deemed accurate. The quality of the inferred variables is gauged by its ability to reproduce held-out experimental measurements. We test the correctness of the framework on three double-cone experiments conducted in the CUBRC Inc.'s LENS-I shock tunnel, which have also been numerically simulated successfully. Thereafter, we use the framework to investigate two double-cone experiments (executed in the LENS-XX shock tunnel) which have encountered difficulties when used in model validation exercises. We detect an inconsistency with one of the LENS-XX experiments. In addition, we hypothesize two causes for our inability to simulate LEXS-XX experiments accurately and test them using our framework. We find that there is no single cause that explains all the discrepancies between model predictions and experimental data, but different causes explain different discrepancies, to larger or smaller extent. We end by proposing that uncertainty quantification methods be used more widely to understand experiments and characterize facilities, and we cite three different methods to do so, the third of which we present in this paper.

Thermophysics↗

DOE OSTI2020

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

In this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery. The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L -1 ) agreed—to within a factor of about 2—with aircraft data at flight levels (-10° to -15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations. The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Model and Validation of Single-Axis Tracking with Bifacial Photovoltaics: Preprint

Single-axis tracking is a cost effective deployment strategy for large-scale ground-mount photovoltaic (PV) systems in regions with high direct-normal irradiance (DNI). Bifacial modules in 1-axis tracking systems boost energy yield by 4% - 15% depending on module type and ground albedo, with a global average of 9%. This benefit is in addition to the 15%-25% energy gain already afforded by single-axis tracking relative to fixed-tilt deployments. Here we compare model results against field performance data for two side-by-side bifacial / monofacial tracked systems - one in Albuquerque NM, and one in eastern Oregon. The Albuquerque system shows monthly rear irradiance gain of 10-14.9%, and the Oregon bifacial system has an average performance ratio 9.4% higher than the monofacial system. Both results match bifacial irradiance model results within uncertainty. Simulations show that smart tracking algorithms can offer more than 1% improvement on annual energy yield by adjusting tilt angle under cloudy conditions. Finally, ray-tracing simulations investigated edge brightening, suggesting 15%-25% increase in rear irradiance at the ends of tracker rows, but up to 20% loss from center-mounted torque tubes, creating multiple shadows.

14 SOLAR ENERGY↗

DOE OSTI2017

Process Modeling and Validation for Metal Big Area Additive Manufacturing

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. Computational modeling can be used to accelerate the development of the mBAAM technology as well as a design and optimization tool for the actual manufacturing process. We have developed a finite element method simulation framework for mBAAM using the new features of software ABAQUS. The computational simulation of material deposition with heat transfer is performed first, followed by the structural analysis based on the temperature history for predicting the final deformation and stress state. In this formulation, we assume that two physics phenomena are coupled in only one direction, i.e. the temperatures are driving the deformation and internal stresses, but their feedback on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Simunovic, Srdjan↗

NASA NTRS2022

Initial Laboratory Demonstration of Multi-Star Wavefront Control at the Occulting Mask Coronagraph Testbed

Online Abstract: A majority of Sun-like stars, such as the A and B components of Alpha Centauri, have at least one stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument. Multi-Star Wavefront Control (MSWC) is a wavefront-control technique that removes stellar leakage from both stellar components, enabling direct imaging of planets in many binary star systems. We present the latest experimental and modeling results obtained with MSWC as part of the technology development effort focusing on demonstrations conducted on the Occulting Mask Coronagraph (OMC) testbed at JPL. OMC has a layout similar to the Roman Space Telescope coronagraph instrument (CGI), and we used a MSWC mask similar to the one that was contributed to the Roman CGI. Our results represent the first demonstrations of this technique on the OMC testbed, with the ultimate goal of demonstrating full MSWC with validated models at contrast levels relevant to Roman CGI. Technical Review Abstract: A majority of Sun-like stars have at least one stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument, limiting the achievable contrast. These include high-quality target stars such as the A and B components of Alpha Centauri, our nearest stellar neighbor. Enabling direct imaging of binary stars has the potential to increase the scientific yield for coronagraphic instruments planned on NASA's future space missions including the Roman Space Telescope and the next IR/O/UV Flagship recommended by Astro2020. Multi-Star Wavefront Control (MSWC) is a wavefront-control technique that simultaneously removes the (mutually incoherent) stellar leakage from both stellar components, enabling direct imaging of planets in many binary star systems. MSWC is an algorithmic technique and can be used with existing wavefront control systems on coronagraphic instruments (as well as starshades if a deformable mirror is available in the optical path). We summarize the latest experimental and numerical results obtained with MSWC as part of the technology development effort to demonstrate compatibility with existing high-contrast imaging platforms for this technique. The Super-Nyquist regime of MSWC was tested in vacuum at JPL's High Contrast Imaging Testbed (HCIT) on the Decadal Survey Testbed (DST) reaching 8.6e-9 contrast in a 10% band. Recently, the Occulting Mask Coronagraph (OMC) testbed at JPL is being prepared for demonstrations of Multi-Star Wavefront Control. A shaped pupil mask similar to the contributed MSWC mask on the Roman Space Telescope's coronagraph instrument has been recently manufactured including matching Lyot and focal plane masks and being installed on the OMC testbed. The goal of this experiment is a demonstration of MSWC using validated models on a testbed configuration and at contrast levels relevant to the Roman coronagraphic instrument.

High-contrast imaging↗

DOE OSTI2018

An instrument for in situ time-resolved X-ray imaging and diffraction of laser powder bed fusion additive manufacturing processes

In situ X-ray-based measurements of the laser powder bed fusion (LPBF) additive manufacturing process produce unique data for model validation and improved process understanding. Synchrotron X-ray imaging and diffraction provide high resolution, bulk sensitive information with sufficient sampling rates to probe melt pool dynamics as well as phase and microstructure evolution. Here, we describe a laboratory-scale LPBF test bed designed to accommodate diffraction and imaging experiments at a synchrotron X-ray source during LPBF operation. We also present experimental results using Ti-6Al-4V, a widely used aerospace alloy, as a model system. Both imaging and diffraction experiments were carried out at the Stanford Synchrotron Radiation Lightsource. Melt pool dynamics were imaged at frame rates up to 4 kHz with a ~1.1 μm effective pixel size and revealed the formation of keyhole pores along the melt track due to vapor recoil forces. Diffraction experiments at sampling rates of 1 kHz captured phase evolution and lattice contraction during the rapid cooling present in LPBF within a ~50 × 100 μm area. In conclusion, we also discuss the utility of these measurements for model validation and process improvement.

36 MATERIALS SCIENCE↗

NASA NTRS2008

A Capable and Temporary Test Facility on a Shoestring Budget: The MSL Touchdown Test Facility

The Mars Science Laboratory mission (MSL) has undertaken a developmental Touchdown Test Program that utilizes a full-scale rover vehicle and an overhead winch system to replicate the skycrane landing event. Landing surfaces consisting of flat and sloped granular media, planar, rigid surfaces, and various combinations of rocks and slopes were studied. Information gathered from these tests was vital for validating the rover analytical model, validating certain design or system behavior assumptions, and for exploring events and phenomenon that are either very difficult or too costly to model in a credible way. This paper describes this test program, with a focus on the creation of test facility, daily test operations, and some of the challenges faced and lessons learned along the way.

rover↗

DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

DOE OSTI2017

Modeling and Validation of Irradiation Damage in Ni-based Alloys for Long-Term LWR Applications

Grizzly is a multiphysics simulation code under development at Idaho National Laboratory to simulate aging mechanisms and their effects on the integrity of critical LWR components, including Ni-Cr alloy components. Predictions of the LWR component integrity rely on the ductile-to-brittle transition temperature (DBTT) curve to determine the toughness of the alloy after a period of exposure to in-service reactor conditions. The macroscopic DBTT curve is governed by the microstructure evolution of the alloy, thus, a capability to predict the microstructure evolution in response to thermal ageing is being implemented into Grizzly. Within this report section, the implementation of the Avrami equation to estimate the phase fraction of the aged long range ordered precipitates is discussed. The initial evaluation of current crystal plasticity models within Grizzly to model these Ni-Cr alloys is also presented.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Ablator Response Model Development: From Flight Data Back to Fundamental Experiments

The successful Mars atmospheric entry by the Mars Science Laboratory (MSL-Curiosity) combined with the success of the Earth atmospheric entry by the Stardust capsule have established PICA as a major Thermal Protection Systems (TPS) material. We expect that this class of materials will be on the short list selected by NASA for any atmospheric entry missions and that it will be the lead of that list of materials in any planning, feasibility studies or flight readiness studies. In addition to NASAs successes, the Dragon capsule, the successful commercial space vehicle built by SpaceX, uses PICA-X, while the European Space Agency is considering ASTERM for its exploration missions that involve atmospheric entries, both of these materials are of the same family as PICA. In the talk, a high-fidelity model will be detailed and discussed. The model tracks the chemical composition of the gases produced during pyrolysis. As in the conventional models, it uses equilibrium chemistry to determine the recession rate at high temperatures but switches to in-volume finite-rate ablation for lower temperatures. It also tracks the time evolution of the porosity of the material. Progress in implementing this high-fidelity model in a code will be presented. In addition, a set of basic experimental data being supported for model validation will be summarized. The validation process for the model development will be discussed. Preliminary results will be presented for a case where detailed pyrolysis product chemistry is computed. Finally, a wish list for a set of validation experiments will be outlined and discussed.

Mansour, Nagi N.↗

NASA NTRSDate not supplied

Design and Analysis of Shape Memory Spring Tires for Martian and Lunar Rover Vehicles

Shape memory alloys (SMAs) have played an important role in various innovative engineering and medical applications, such as aerospace actuators, vibration damping devices, and coronary stents. In applications, shape memory alloys are commonly utilized in two fundamentally different ways: (i) making use of the superelasticity/ pseudoelasticity (SE/PE) phenomena, as in applications in biomedical engineering, and (ii) taking advantages of the shape memory effect (SME), as is used for actuators. Their ability to act in such vastly different capacities is mainly due to their unique capability to recover large amounts of deformation produced by either applied stresses or temperature changes. One recent emerging application in use of SMAs has been in the area of non-pneumatic tire designs for Martian or Lunar roving vehicles. These vehicles require tires that are capable of traversing rugged terrain while withstanding extreme temperatures and atmospheric conditions. Inspired by the flexible wire mesh tires used on three Lunar Roving Vehicle (LRV) missions to the Moon on Apollo 15, 16, and 17, a new compliant tire technology was developed by the NASA Glenn Research Center (GRC) and Goodyear Tire & Rubber, known as the Spring Tire. The Spring Tire consists of several hundred coiled springs woven into a flexible mesh and formed into the shape of a tire. Like the LRV wire mesh tires, the original Spring Tires were made from spring steel and were prone to permanent deformation when undergoing high localized loads. Later, a new iteration of this technology was invented, known as the ‘Superelastic Tire’. This new technology incorporated the use of superelastic SMA springs, which could effectively undergo approximately 30 times more reversible deformation than the steel spring. It also provided even greater durability and allowed for more flexibility in design, such as the use of other structural forms to reduce mass or increase load carrying capacity. Because of the unique nature of both the SMA material and the complex interactions between the springs, designing Spring Tires for a specific application requires extensive effort. Historically, design decisions have relied on full-scale empirical testing; however, this is very expensive and time consuming, especially when multiple iterations are needed. Therefore, developing a large-scale, robust, and predictive numerical model entailing complex spring interactions and the shape memory material behavior within a tire construct is the first essential step towards a successful design program. The current work focuses on implementation of the user-defined Shape Memory Alloy (SMA) model, otherwise known as SMA-GVIPs, in the Finite Element analysis (FEA) program ABAQUS for large-scale simulations of the GRC-developed Spring Tires made of SMA. The novelty of this work lies in the thorough, detail-oriented, and computationally efficient finite element analysis of full-scale SMA tires. A well-thought material characterization plan followed by model validation and a systemic sensitivity study on SMA tires has never been reported in the previous literature. The main objective of this study is to help the team improve and optimize the structural design of the SMA tires through in-depth numerical analysis and sensitivity studies. Various design variables (wire diameter, coil diameter, pitch, bead angle, and number of springs) were varied to study their influence on the global load-displacement response of the tire construct. A detailed investigation of the three-dimensional stress states was also carried out to enhance our understanding of the local changes as the tire goes through global deformation. It was concluded that a robust numerical model with a good predictive capability, together with a thoughtfully crafted sensitivity study can result in improved design iterations required to reach a desired tire performance while, significantly reducing manufacturing, labor and testing expenses. A summary of the Finite Element (FE) model construction will be presented together with a description of the user-defined SMA model, characterization process, experimental results, model validation, and numerical sensitivity study results.

shape memory alloys↗

DOE OSTI2023

Representative Phenomena of Cyclic Turbulent Combustion in High-Pressure Fuel Sprays

Abstract Cyclic variations in conventional diesel combustion engines can lead to large differences in engine out emissions even at steady operation. This study uses an optically accessible constant-pressure flow chamber to acquire fuel injections in quick succession to analyze mixing, auto-ignition, and combustion of diesel-surrogate n-heptane using multiple high-speed optical diagnostics. Prior studies have utilized fewer injections and/or they rely on analysis of ensemble average behavior. These approaches do not yield information on injection-to-injection variation or provide confidence in utilizing individual injection measurements for high-fidelity computational fluid dynamics(CFD) model validation. In this study, a large set of 500 injections is used to obtain global parameters including liquid length, vapor penetration length, ignition delay time, and lift-off length. Results for multiple injections are presented to illustrate large injection to injection variations. Potential sources for these variations are analyzed to conclude localized, small scale turbulence and rate of injection variations as the likely sources. Then, a statistical method based on z-scores is proposed and implemented to identify instantaneous injections that best represent the bulk data-set of jet boundaries measured independently by three different diagnostics. This synthesis of statistics-guided screening of data set and ensemble-average analysis offers higher confidence for CFD model validation relying upon both a representative single and average injection results.

42 ENGINEERING↗

DOE OSTI2017

Metal Big Area Additive Manufacturing: Process Modeling and Validation

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology for printing large-scale 3D objects. mBAAM is based on the gas metal arc welding process and uses a continuous feed of welding wire to manufacture an object. An electric arc forms between the wire and the substrate, which melts the wire and deposits a bead of molten metal along the predetermined path. In general, the welding process parameters and local conditions determine the shape of the deposited bead. The sequence of the bead deposition and the corresponding thermal history of the manufactured object determine the long range effects, such as thermal-induced distortions and residual stresses. Therefore, the resulting performance or final properties of the manufactured object are dependent on its geometry and the deposition path, in addition to depending on the basic welding process parameters. Physical testing is critical for gaining the necessary knowledge for quality prints, but traversing the process parameter space in order to develop an optimized build strategy for each new design is impractical by pure experimental means. Computational modeling and optimization may accelerate development of a build process strategy and saves time and resources. Because computational modeling provides these opportunities, we have developed a physics-based Finite Element Method (FEM) simulation framework and numerical models to support the mBAAM process s development and design. In this paper, we performed a sequentially coupled heat transfer and stress analysis for predicting the final deformation of a small rectangular structure printed using the mild steel welding wire. Using the new simulation technologies, material was progressively added into the FEM simulation as the arc weld traversed the build path. In the sequentially coupled heat transfer and stress analysis, the heat transfer was performed to calculate the temperature evolution, which was used in a stress analysis to evaluate the residual stresses and distortions. In this formulation, we assume that physics is directionally coupled, i.e. the effect of stress of the component on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Additive Manufacturing↗