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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Demonstration of low-mode shape control in indirect-drive double shell implosions at the NIF

Double shell inertial confinement fusion is a concept for achieving robust thermonuclear burn that uses dense metal shells to compress deuterium-tritium (DT) fuel to fusion conditions. Double shell implosions are typically indirectly driven and involve a target that consists of a low-Z ablator, a foam layer, and a high-Z pusher surrounding the DT fuel. The goal of the campaign is to achieve a volumetric burn as radiation losses from the DT fuel are trapped by the opaque high-Z shell. The overall performance of double shell implosions relies on the efficient collisional transfer of kinetic energy between layers. The efficiency of this transfer (and therefore the overall performance of a given implosion) is degraded by the presence of low-mode asymmetries. P2 asymmetries are often observed in spatially resolved 2D radiographs of nominal double shell implosions. This work discusses three such experiments: one with an oblate P2 asymmetry, one with a prolate P2 asymmetry, and one with an approximate spherical symmetry. After performing a shape analysis of the oblate and prolate implosions to quantify asymmetries, these experimental results were compared with the results of hydrodynamic simulations for the two experiments. Differences between the experiment and simulation were then used to design an approximately spherical implosion by altering the incident laser cone fraction. Radiographs from the experiment that implemented the modified cone fraction show evidence of an implosion that is approximately spherical until bang time. This design is intended to serve as a point design for future studies that will seek to optimize various aspects of the double shell target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

High Flux Isotope Reactor Low-Enriched Uranium Low Density Silicide Fuel Design Parameters

High Flux Isotope Reactor (HFIR) highly enriched uranium (HEU) to low-enriched uranium (LEU) conversion activities are ongoing as part of the Department of Energy (DOE) National Nuclear Security Administration (NNSA)’s nuclear nonproliferation mission. Design activities studying the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a low density uranium-silicide dispersion (U 3 Si 2 -Al) fuel, which has a uranium density of 4.8 gU/cm 3 . The goal of these studies is to generate several HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. The documented designs will serve as references for fuel fabrication and qualification activities. Recent advancements in modeling and simulation tools enable quick prototyping of fuel designs. Shift, a Monte Carlo neutron transport and depletion tool optimized for high-performance computing (HPC) architectures, is used for efficient fuel cycle and performance metrics calculations. The HFIR Steady State Heat Transfer Code (HSSHTC) is used to vet the thermal safety margin. Also, a new automation tool that connects all fuel design analysis steps, named Python HFIR Analysis and Measurement Engine (PHAME), has been developed to expedite the design study in an efficient and reproducible manner. Leveraging these tools, several candidate fuel designs were selected for varying fabrication complexity. This report provides design feature details for four selected HFIR LEU low density U 3 Si 2 -Al fuel designs and their corresponding performance and safety metrics. Nominal, best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities are provided for candidate fuel designs relevant to framing irradiation experiments to support fuel qualification efforts. Simulations show that the low density U 3 Si 2 -Al, with design features to enhance safety, can meet HEU core performance metrics and safety requirements if the reactor power is increased from 85 MW (HEU) to 95 MW (LEU) and if the active fuel length is increased from 50.80 cm (HEU) to 55.88 cm (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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↗
DOE OSTI2018

Effect of Cellular Lattices, Heat-Exchange Intensifiers, and Coolant Mixing on the Critical Power of VVER FA

The results of one stage in the development of methods for increasing the critical power of water-cooled nuclear reactors – the capacity of a reactor installation with sharp degradation of the heat exchange characteristics of the coolant (crisis of heat exchange) – are presented. This stage included experimental determination of the effect on the crisis of heat exchange of arranging heat-exchange intensifiers in FA and transverse mixing of the coolant flow, for which lattices assembled from properly shaped cellular elements where used. The FA models consisted of an assembly of 19 fuel-element simulators with a non-uniform distribution of heat emission along the length. Freon-12 was used as the coolant. The models of the FA differed by the type of intensifier lattices and the number of FA arranged along the length. The efficacy of the influence of lattices on the critical power as a result of the intensification of heat exchange and transverse mixing of the coolant was determined separately. The optimal rigging of FA with lattices was determined experimentally.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Time-resolved spray characterization via unified optical flow and binarization technique

This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.

42 ENGINEERING↗
DOE OSTI2021

Optimal band structure for thermoelectrics with realistic scattering and bands

Abstract Understanding how to optimize electronic band structures for thermoelectrics is a topic of long-standing interest in the community. Prior models have been limited to simplified bands and/or scattering models. In this study, we apply more rigorous scattering treatments to more realistic model band structures—upward-parabolic bands that inflect to an inverted-parabolic behavior—including cases of multiple bands. In contrast to common descriptors (e.g., quality factor and complexity factor), the degree to which multiple pockets improve thermoelectric performance is bounded by interband scattering and the relative shapes of the bands. We establish that extremely anisotropic “flat-and-dispersive” bands, although best-performing in theory, may not represent a promising design strategy in practice. Critically, we determine optimum bandwidth, dependent on temperature and lattice thermal conductivity, from perfect transport cutoffs that can in theory significantly boost z T beyond the values attainable through intrinsic band structures alone. Our analysis should be widely useful as the thermoelectric research community eyes z T > 3.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Impact of reverse flow induced by a sawtooth anode on the performance of an argon Hall thruster

This study reports the performance comparison of the RAIJIN-66 TAL-type Hall thruster with argon propellant, using two hollow anode designs, one with a simple straight shape and another one with a sawtooth shape. Simulations of the rarefied gas in the sawtooth hollow anode region suggest a successful reversal of the direction of neutral particle flow, with an average increase in the neutral particle density by 15.5% when compared to the straight-shaped hollow anode. This contributes to the improvement in performance across a range of discharge voltages that was measured experimentally. When the thruster is operated with a discharge voltage of 150 V and a flow rate of 70 SCCM, the propellant utilization efficiency with the straight anode is 14%, while with the sawtooth anode it is 25.1%. The anode efficiency reaches in the vicinity of 15% with the sawtooth anode in high voltage conditions, exceeding the efficiencies achieved with the straight anode in the same operating conditions. The optimal magnetic field condition for argon operation and the tuning parameters of the sawtooth anode design for RAIJIN-66 are also discussed.

Satpathy, Dibyesh [Univ. of Tokyo (Japan)] (ORCID:↗
DOE OSTI2025

Solid State Transformer Controls for Mitigation of E3a High-Altitude Electromagnetic Pulse Insults

This paper explores the use of a solid state transformer (SST) to mitigate the 𝐸 3𝐴 component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the 𝐸 3𝐴 components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller.

HEMP mitigation↗
DOE OSTI2025

Measurement of the liquid argon scintillation pulse shape using differentiable simulation in the coherent CAPTAIN-Mills experiment

The coherent CAPTAIN-Mills (CCM) experiment is a liquid argon (LAr) light collection detector searching for MeV-scale neutrino and beyond Standard Model physics signatures. Two hundred eight-inch photomultiplier tubes instrument the seven-ton fiducial volume with 50% photocathode coverage to detect light produced by charged particles. CCM’s light-based approach reduces requirements of LAr purity, compared to other detection technologies, such that sub-MeV particles can be reliably detected without additional LAr filtration and with 𝒪⁡(1) parts per million of common contaminants. We present a measurement of LAr light production and propagation parameters, with uncertainties, obtained from a sample of MeV-scale electromagnetic events. The optimization of this high-dimensional parameter space was facilitated by a differentiable optical photon Monte Carlo simulation and detailed photomultiplier tube response characterization. This result accurately predicts the timing and spatial distribution of light due to scintillation and Cherenkov emission in the detector. This is the first description of photon propagation in LAr to include several effects, including anomalous dispersion of the index of refraction near the ultraviolet resonance, Mie scattering from impurities, and Cherenkov light production.

Cherenkov detectors↗
DOE OSTI2018

Determination of the Disperse Composition of a PbO Suspension Containing Aggregates of Particles of Lamellar Shape by the Laser-Polarimetry Method

The results of measurements of the scattering matrix at a wavelength of 0.63 μm in the range of scattering angles of 10°–155° are presented for an aqueous suspension of lead oxide containing particles of plate form and their aggregates of monomers with dimensions of ~5 nm. The results of the measurements are compared with the results of calculations for axially symmetric scatterers (ellipsoids of rotation, cylinders). It is shown that the presence of aggregates affects the scattering properties of such a medium. The results of reconstructing the distribution of particles of a disperse medium in sizes from the measurements data of the scattering matrix are presented. The reconstruction of the distributions was carried out by solving the problem of optimizing the sum of the squared deviations of the experimental and calculated values of matrix elements in the framework of the model of axially symmetric scatterers. It is shown that the distribution of particles by sizes is more accurately reconstructed by minimizing the sum of the squares of the deviations for the sum of the diagonal elements. The obtained distribution is compared with the distribution measured by the method of dynamic light scattering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A Survey of Precipitation-Induced Atmospheric Cold Pools over Oceans and Their Interactions with the Larger-Scale Environment

Pools of air cooled by partial rain evaporation span up to several hundreds of kilometers in nature and typically last less than 1 day, ultimately losing their identity to the large-scale flow. These fundamentally differ in character from the radiatively-driven dry pools defining convective aggregation. Advancement in remote sensing and in computer capabilities has promoted exploration of how precipitation-induced cold pool processes modify the convective spectrum and life cycle. This contribution surveys current understanding of such cold pools over the tropical and subtropical oceans. In shallow convection with low rain rates, the cold pools moisten, preserving the near-surface equivalent potential temperature or increasing it if the surface moisture fluxes cannot ventilate beyond the new surface layer; both conditions indicate downdraft origin air from within the boundary layer. When rain rates exceed ~2 mm h –1, convective-scale downdrafts can bring down drier air of lower equivalent potential temperature from above the boundary layer. The resulting density currents facilitate the lifting of locally thermodynamically favorable air and can impose an arc-shaped mesoscale cloud organization. This organization allows clouds capable of reaching 4–5 km within otherwise dry environments. These are more commonly observed in the northern hemisphere trade wind regime, where the flow to the intertropical convergence zone is unimpeded by the equator. Here their near-surface air properties share much with those shown from cold pools sampled in the equatorial Indian Ocean. Cold pools are most effective at influencing the mesoscale organization when the atmosphere is moist in the lower free troposphere and dry above, suggesting an optimal range of water vapor paths. Outstanding questions on the relationship between cold pools, their accompanying moisture distribution and cloud cover are detailed further. Near-surface water vapor rings are documented in one model inside but near the cold pool edge; these are not consistent with observations, but do improve with smaller horizontal grid spacings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Game-Theoretic Approach for Electricity Pricing Between Distribution System Operator and Load Aggregators

Transactive energy has emerged and gained more and more attention in recent years along with smart grid two-way communication technologies. Electricity pricing strategies play a critical role in influencing and shaping the customers’ energy load profile. In this paper, we investigate the electricity pricing strategy between a distribution system operator (DSO) and load aggregators (LAs) by adopting a bi-level Stackelberg game approach. With the purpose of maximizing its own operating revenue as well as better serving its customers, the upper level DSO will determine the price considering how lower level LAs will respond to it. Peak-to-average ratio of the total demand is modeled as a constraint and peak load is penalized at the upper optimization level. Classical backward induction is used to obtain a Nash equilibrium for the formulated bi-level Stackelberg game. Numerical results demonstrate the effectiveness of the proposed game approach in leveraging flexible demand potential to benefit both DSO and LAs.

Chen, Yang↗
DOE OSTI2019

High-Performance Bi-2212 Round Wires Made With Recent Powders

Multifilamentary Bi 2 Sr 2 CaCu 2 O x (Bi-2212) wire made by the powder-in-tube technique is the only high-temperature superconductor made in the round shape preferred by magnet builders. The critical current density (J C ) of Bi-2212 round wire was improved significantly by the development of overpressure heat treatment in the past few years. Bi-2212 wire is commercially available in multiple architectures and kilometer-long pieces and is a very promising conductor for very high-field NMR and accelerator magnets. Here, we studied the effects of precursor powder and heat treatment conditions on the superconducting properties and microstructure of recent Bi-2212 wires. Short samples of recent wire with optimized overpressure processing showed J C (4.2 K, 15 T) = 6640 A/mm 2 and J C (4.2 K, 30 T) = 4670 A/mm 2 , which correspond to engineering critical current densities J E (4.2 K, 15 T) = 1320 A/mm 2 and J E (4.2 K, 30 T) = 930 A/mm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2018

STATUS OF THE JLEIC ION COLLIDER RING DESIGN

We present an update on the lattice design and beam dynamics study of the ion collider ring of JLEIC (Jefferson Lab Electron Ion Collider). The collider ring consists of two 261.7 degree arcs connected by two straight sections crossing each other. One of the straights houses an interaction region (IR) and is shaped to make a 50 mrad crossing angle with the electron beam at the interaction point (IP) to meet physics requirements. The forward acceptance requirements downstream of the IP in the ion direction lead to an asymmetric IR lattice design. The detector solenoid effects and the multipole fields of the IR magnets further complicate this picture. In this paper, compensation of the detector solenoid effects is considered together with orbit correction and multipole effects. We also study local compensation of the magnet multipoles using dedicated multipole correctors. And an optimization of the betatron tunes is also presented.

Wei, Guohui↗
DOE OSTI2019

A Review on Binder Jet Additive Manufacturing of 316L Stainless Steel

Binder jet additive manufacturing enables the production of complex components for numerous applications. Binder jetting is the only powder bed additive manufacturing process that is not fusion-based, thus manufactured parts have no residual stresses as opposed to laser-based additive manufacturing processes. Binder jet technology can be adopted for the production of various small and large metallic parts for specific applications, including in the biomedical and energy sectors, at a lower cost and shorter lead time. One of the most well-known types of stainless steels for various industries is 316L, which has been extensively manufactured using binder jet technology. Binder jet manufactured 316L parts have obtained near full density and, in some cases, similar mechanical properties compared to conventionally manufactured parts. This article introduces methods, principles, and applications of binder jetting of SS 316L. Details of binder jetting processes, including powder characteristics (shape and size), binder properties (binder chemistry and droplet formation mechanism), printing process parameters (such as layer thickness, binder saturation, drying time), and post-processing sintering mechanism and densification processes, are carefully reviewed. Furthermore, critical factors in the selection of feedstock, printing parameters, sintering temperature, time, atmosphere, and heating rate of 316L binder jet manufactured parts are highlighted and summarized. Finally, the above-mentioned processing parameters are correlated with final density and mechanical properties of 316L components to establish a guideline on feedstock selection and process parameters optimization to achieve desired density, structure and properties for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗
DOE OSTI2018

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of a realistic shaped charge calculation in the presence of voids and solids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these techniques lags behind their development in the lab. This means that material and process development proceeds largely via trial and error. This is sub-optimal since experiments are cost-, time-, and labor-intensive. In this work we propose a machine learning framework, differential property classification (DPC), which enables an experimenter to leverage machine learning's unparalleled pattern matching capability to pursue data-driven experimental design. DPC takes two possible experiment parameter sets and outputs a prediction of which will produce a material with a more desirable property specified by the operator. We demonstrate the success of DPC on AA7075 tube manufacturing process and mechanical property data using shear assisted processing and extrusion (ShAPE), an emerging solid phase processing technology. We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.

advanced manufacturing, machine learning, ShAPE↗